As a veteran of 25-plus IBC Shows over the past nearly 30 years, I can attest that navigating the annual gathering has its own particular quirks that distinguish it from the NAB Show, particularly the tone of the locale. Apart from the fact that Amsterdam is the “wet and humid” show and NAB is the “dry” show (but only when talking about the climate), IBC also represents a more relaxed tone that reflects the nature of the ancient city itself.

Nevertheless, most of the themes were similar, and before we set our sights on the next gathering (NAB Show New York), I wanted to share some of my thoughts around the central themes:

AI: IBC reported 41,225 attendees for the show, which ran Sept. 11-14 at the RAI Amsterdam, down 6% from 2025. Although consolidation, particularly among U.S. broadcasters, is often cited as one of the main reasons for the decline, I also think it represents a cooling off from the past three or four years, when interest was higher after COVID. (That’s not to mention that the number of attendees from the U.S. has declined since trade shows resumed in 2022.)

But I also think artificial intelligence is playing a role, as more processes become automated. I was reminded of this after hearing Grass Valley Chief Technology Officer Ian Fletcher’s rule that “complexity doesn’t go away, it just moves around.” As the process of media management, production and distribution becomes more automated and software-based, more people are moved out of the media production chain.

Seeing a software demo on the show floor can certainly have more impact than over Zoom, but is it still worth the cost of travel?

This is an ongoing issue that won’t be resolved by the oft-repeated trope that those same people who were doing rote tasks are simply being moved to other areas where they can “focus on other more important work.” Attrition is real and growing.

Collaboration: In our industry, companies have a long history of partnering with competitors, but that seems to be increasing—and this is more of a reflection of the increasing focus on software.

Nowhere was this better illustrated than by the growing influence and impact of MXL (Media eXchange Layer), a critical component of the EBU’s Dynamic Media Facility initiative. Tech demos showcasing partnerships between Grass Valley and Lawo, Matrox and EVS, as well as multivendor demonstrations at the Techex, Qvest and AWS stands, just to name a few, demonstrated how quickly MXL is moving beyond the proof-of-concept stage toward real-world deployment.

The EBU-led MXL initiative also received significant recognition at IBC, winning an IBC 2026 Innovation Award in the Content Creation category. The growing number of vendors incorporating MXL into commercial products and demonstrations suggests the technology is increasingly becoming part of the broader software-defined media ecosystem.

Cybersecurity: Alarmed over recent news of disruptions created by “rogue” AI agents, the security of media production systems was also top of mind for many attendees. As more media and media processing moves into the cloud, concern over potential vulnerabilities increases. This has prompted more production to become hybrid-based, with certain content and processes stored both in the cloud and on-prem.

It has also led to more interest in “MCP,” or Model Context Protocol, a framework that allows customers to establish guardrails to limit information accessible to AI agents.

Tariffs: The “T-word” was back, having been overshadowed by AI and the memory and chip shortages that were the talk of earlier shows. With many of the media tech industry’s largest companies based in Canada, President Donald Trump’s recent imposition of a 50% duty on targeted goods has forced some vendors to raise prices. And although some goods are exempt and vendors are attempting to absorb costs, the tariffs—along with the continued pressure on memory and chip availability worldwide—are cause for concern. However, the increased influence of software-defined production is helping to ameliorate the impact.

I’ll share more of my thoughts about my conversations with IBC exhibitors in the October issue of TV Tech.

TiVo has introduced “Agent TiVo,” an AI agent that uses conversational prompts to help users of the Xperi-owned platform discover and engage with TV and streaming content.

Agent TiVo lets viewers interact naturally by voice or text, helping them find content in the way they think and speak, the company said. Instead of relying on traditional keyword searches, viewers can ask questions, refine results through follow-up conversations, receive personalized recommendations and move directly from discovery to action.

“Entertainment choices have expanded dramatically, making content discovery increasingly complex for viewers,” said Kevin Lenhart, general manager of pay TV at Xperi. “Agent TiVo combines conversational AI with TiVo's proven voice, discovery and personalization expertise to deliver an experience built specifically for entertainment. The result is a faster, more personalized experience that helps viewers spend less time searching and more time watching, while giving operators and entertainment platforms a powerful new way to deepen engagement.”

Built specifically for entertainment, Agent TiVo lets viewers search naturally by mood, genre, actor, quote, episode, sports team, source, availability or other criteria. The experience adapts throughout the conversation, helping viewers narrow options, explore alternatives and receive recommendations tailored to their interests and viewing habits.

Agent TiVo combines the power of large language models (LLMs) with TiVo’s voice-recognition technology in a hybrid architecture that intelligently routes queries to the most appropriate models, helping reduce costs and latency. As a result, operators and entertainment platforms can deliver conversational AI experiences without the expense, risk and complexity of an LLM-only approach, while maintaining control over their brands, content experiences and platform evolution.

Other key features include:

• Entertainment expertise: Optimized for entertainment experiences, not general-purpose AI.
• Hybrid architecture: Intelligent model routing helps reduce costs and latency.
• Seamless integration: Extends existing TiVo deployments without major platform changes.
• Brand control: Fully white-labeled to reflect each operator’s brand and content strategy.
• Operational simplicity: Delivers conversational AI without the burden of managing an LLM-only solution.

Agent TiVo reflects Xperi’s ongoing commitment to creating intuitive entertainment experiences that help consumers navigate large, fragmented content ecosystems.

For more information on Agent TiVo, visit the TiVo website.

CHANTILLY, Va.—BIA Advisory Services has updated its 2026 U.S. Local Advertising Forecast and is now projecting that total local ad revenue will reach $186.1 billion, up $1.6 billion (+0.9%) from the firm's April 2026 estimate of $184.5 billion and approximately 9% year over year from 2025.

The increase is driven primarily by higher political ad spending heading into the midterms, along with continued strength in mobile.

The stronger than expected political ad spend is particularly good news for local TV stations as most of the growth has been flowing into TV station broadcasts and TV station digital platforms, the researchers said.

Overall, BIA is now projecting the TV over-the-air and TV digital/OTT ad revenue will hit $19.8 billion in 2026.

The firm also released a preliminary outlook for 2027 that sees growth in mobile and underlying local ad growth, particularly in Legal Services vertical, that will offset the end of the election cycle in 2027 and keep next year’s local ad spend essentially flat compared to 2026.

Excluding political advertising, the 2026 forecast is now $176.4 billion, up $0.3 billion (+0.2%) from the prior estimate of $176.1 billion and 3.9% over 2025, reflecting steady, broad-based growth across the underlying local ad market.

“Political spending came in higher than we anticipated in April, with most of the incremental spending flowing into TV OTA and TV OTT,” said Senan Mele, vice president of forecasting and data analysis, BIA Advisory Services. “Legal Services was also notable in this update, reaching $9.3 billion, up 4.6% from the prior forecast. Despite higher media costs and a more fragmented media environment, law firms continue to invest heavily in television, both linear and streaming, where the ability to reach large audiences and generate qualified leads continues to drive demand.”

BIA now projects $9.7 billion in 2026 for local political spending, up from $8.4 billion in the April forecast, which is an increase of $1.3 billion concentrated almost entirely in video. TV OTA and TV OTT together captured $1.2 billion of that increase, reinforcing broadcast and streaming video's role as a preferred vehicle for political campaigns.

The new data shows that mobile keeps compounding, and AI reshapes search.

Mobile remains the largest local media category tracked by BIA, projected to grow to $45.3 billion in 2026 (excluding political), an 8.9% year-over-year increase. This growth comes as competition intensifies in A.I.-fueled search advertising, a category that local advertisers have traditionally relied on to reach consumers across mobile devices.

“Google, OpenAI, Amazon, and Apple are all positioning themselves to capture a larger share of advertising tied to AI-powered search,” said Mike Boland, executive in residence, BIA Advisory Services. “Google’s Gemini is increasingly becoming an extension of its advertising business, while OpenAI, Amazon, and Apple are developing their own approaches to monetize search and discovery. For local advertisers, the bigger question is where consumer intent will emerge and which platforms will capture it. Mobile will be a critical battleground as that shift unfolds.”

BIA also highlighted some of the growth categories heading into 2027.

BIA's first look at 2027 projects total local ad revenue of $186.5 billion, essentially flat versus 2026. About $9 billion in underlying, nonpolitical growth is expected to nearly offset an $8.6 billion decline in political spending as the election cycle ends. Political spending is projected to fall to approximately $1.1 billion in the 2027 off-cycle year.

BIA’s Mele explained that “political spending will decline sharply after the midterms, but the underlying nonpolitical market has continued to grow and should offset much of that decline. We expect the overall local advertising market to remain essentially flat in 2027, with continued growth across core categories helping to support the market in an off-cycle year.”

Beneath that stable topline, several categories are projected to grow well above the market average. Real estate leads at +9.8%, followed by leisure and recreation (+5.9%), automotive (+5.1%), restaurants and food (+4.4%), and financial services (+3.7%).

“2027 makes clear that the underlying growth in local advertising is broader and more durable than the political cycle alone would suggest,” said Rick Ducey, managing director, BIA Advisory Services. “Political spending has accelerated the market and delivered a strong two-year period for broadcast and streaming video, but the more important story is what happens beneath that surge. Core categories continue to expand their investments across an increasingly diverse media ecosystem. That sustained, multi-platform demand, and the media channels that capture it, will shape the next phase of local media.”

For more information on the data, which comes from BIA ADVantage and to access the updated forecast, contact advantage@bia.com to request a demonstration.

AMSTERDAM—CAMB.AI is introducing its new Streaming SDK and Streaming Dashboard at IBC2026, with integrations into NVIDIA Holoscan for Media open reference architecture

The release gives developers and broadcast teams new ways to integrate, manage and deploy real-time multilingual broadcasting within their existing workflows.

CAMB.AI’s live localization technology has already been used across Ligue 1+, NASCAR and Eurovision Sport, including live AI-dubbed commentary and multilingual subtitling.

CAMB.AI is billing the launch as the “multilingual broadcasting’s first AI agent, now live as an SDK.”

Available for C++, Python, Java and Rust, the SDKs allow developers to start broadcasting in multiple languages with as little as three lines of code, making it easier to integrate multilingual capabilities directly into existing applications and workflows.

CAMB.AI’s live streaming platform supports 150+ languages, producing dubbed audio and subtitles for live content. It supports source-speaker voice cloning, studio voices and custom terminology, allowing names, venues, sponsors and other specific terminology to remain consistent across languages. The release features the latest quality enhancements backed by CAMB’s foundational models MARS and BOLI.

CAMB.AI’s new capabilities will be available within the NVIDIA Holoscan for Media reference architecture as a hybrid SaaS. Holoscan for Media is NVIDIA’s open reference architecture and developer toolkit for building AI-powered live media solutions on NVIDIA infrastructure.

Program audio can be processed by CAMB.AI’s models to produce dubbed commentary in each target language, with outputs returned to the production network or delivered directly to destinations including CDN, OTT and YouTube Live.

For broadcasters, this allows live localization to operate alongside other production applications. It reduces the need to send feeds to a separate cloud localization environment and back, reducing infrastructure hops while allowing media to remain within the broadcaster’s facility or own cloud environment when required.

The new Streaming Dashboard provides a visual environment for building, launching and monitoring multilingual streams.

Operators can configure sources, select audio, set processing profiles, create language pipelines and manage output destinations from a single interface. During a live broadcast, teams can monitor stream health, outputs, runtime and live transcripts, as well as pause and resume dubbing without stopping the stream.

CAMB.AI will preview its new dashboard, and SDKs at IBC2026. Visitors will be able to see live multilingual dubbing in action at the CAMB.AI Booth 5.C24.

BURLINGTON, Mass., and SUNNYVALE, Calif.—Avid and Google Cloud have expanded their strategic partnership with the introduction of browser-based Avid Media Composer and an upgraded Avid Content Core content data platform and are showcasing their agentic workflow at IBC2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

By embedding Google Cloud’s Gemini Enterprise and Google BigQuery directly into Avid’s post-production environment alongside media-specific AI agents and Avid tools, creators can remove the constraints of physical hardware and administrative friction. As a result, editors and directors can collaborate seamlessly from anywhere, automate repetitive tasks and focus on storytelling.

Media production houses today face two competing pressures. Content demand is soaring, yet creative teams remain bogged down by administrative overhead. Editors often spend substantial portions of their day tagging footage, organizing timelines and searching through fragmented archives. Additionally, professional editing historically has required heavy, on-premises workstations, making adoption of remote global collaboration slow and cost-prohibitive.

The next phase of the Avid and Google Cloud partnership embeds Gemini Enterprise directly into Media Composer and Content Core to accelerate the creative process. Connecting an intelligent, searchable media archive directly to a browser-based timeline X streamlines media discovery and timeline organization bottlenecks.

The expanded partnership included four tech integrations, including:

• Browser-based Media Composer and agentic editing, making the editing solution available in the Google Chrome Browser, enabling creators to edit timelines in Avid Content Core. Within Media Composer, agentic AI capabilities in Avid’s Ready to Edit allow editors to use natural language prompts to sync media, transcribe and align dialog and organize project bins, putting the focus back on editorial storytelling.
• Semantic search in Content Core to speed up media discovery. Using Google Cloud technologies to analyze and enrich media as it is imported, Avid Content Core and Gemini Enterprise automatically generate transcripts and semantic descriptions, eliminating hours of manual logging.
• Connected workflows from newsroom to timeline. Through Content Core Insights—built with Gemini Enterprise and BigQuery—organizations can bridge the data gap between how content is produced and how it performs. Newsrooms can plan stories and assign teams in Content Core Planning and Rundown, which coordinate assignments, resources, and program rundowns, while editors can pull matching footage into their timelines via natural language search. Final cuts then sync back to broadcast programming.
• Flexible, secure hybrid cloud deployment. The Avid Content Core Site Engine links customer Google Cloud environments directly to Content Core, ensuring media processing, production intelligence and agentic workflows are managed centrally, while compute and high-res assets remain in the user’s own cloud environment.

See Avid at IBC2026 stand 7.B59 and Google in the Accelerator Program location in Hall 14 and Content Everywhere community in Hall 5.

More information is available on the Avid website.

AWS Elemental has announced that it will be showing four new capabilities that bring AI, personalization, and intelligent monetization to the live video workflow during IBC2026 in Amsterdam Sept. 11-14.

The new capabilities were created in response to the fact that live video audiences now expect content-aware streams, per-viewer personalization, and monetization opportunities that respond to what's happening on screen. But deployments of these features had been difficult in the past because each has historically required its own vendor, its own pipeline, and its own operational overhead and deployments.

The new features on display during IBC2026 are:

1. AWS Elemental MediaPackage Dynamic Multiview – Viewers choose their own multi-camera layout from a single set of encoded sources, delivered to any device over standard HTTP Live Streaming (HLS) or Dynamic Adaptive Streaming over HTTP (DASH), without per-layout encoding costs
2. AWS Elemental Inference Contextual Metadata – AI-generated metadata extracted from live video in real time, powering personalized video experiences and contextual ad decisioning
3. AWS Elemental MediaTailor Yield Optimization – Automated backfill of unfilled ad inventory using Amazon Publisher Services (APS) demand, giving streaming TV publishers incremental revenue with zero setup cost
4. AWS Elemental MediaTailor Low-Latency Ad Insertion – Extends personalized ad insertion of MediaTailor to low-latency streams using Apple's HLS interstitials, so publishers no longer have to choose between fast delivery and ad revenue

In terms of the MediaPackage Dynamic Multiview offering the company noted that multi-feed viewing has become a necessity across live content: multiple camera angles for a single sporting event, simultaneous games on one screen, or curated linear bundles combining different content types like news, sports, or entertainment into a single view.

But existing approaches force trade-offs. Tiled encoding limits reach to High Efficiency Video Coding (HEVC)-capable devices. Client-side compositing demands custom SDKs per device. Server-side compositing requires pre-encoding every layout combination, each costing as much as a new channel. Large operators using server-side compositing vendors spend $2M–$12M per year on infrastructure alone, and most streaming platforms can't justify the investment at any price.

MediaPackage Dynamic Multiview stitches multi-camera and multi-feed layouts on demand from encoded sources, delivered as a single adaptive bitrate stream through HLS or DASH. Sources encode one time through AWS Elemental MediaLive. AWS Elemental MediaPackage assembles layouts in the compressed domain with no re-encoding. The output reaches more than 95% of consumer devices with a single digital rights management (DRM) key and requires no SDK, per-device builds, or new vendors.

"AWS Elemental MediaPackage Multiview lets us deliver multiple synchronized camera angles within a single stream, putting our subscribers in control of how they experience live sports. The server-side composition approach scales this premium experience to over 100 million viewers without multiplying origin complexity or CDN costs, giving us a true differentiator in India's competitive OTT landscape" explained Akash Saxena, CTO (JioHotstar).

By compositing in the compressed domain rather than re-encoding per layout, MediaPackage Dynamic Multiview provides up to 97% cost savings compared to solutions that require a separate video stream for every viewing combination.

In terms of the Elemental Inference Contextual Metadata offering, the company explained that personalizing video experiences requires understanding what's happening on screen. Whether that means surfacing the right highlight clip, recommending related content, or matching an ad creative to the moment, it starts with metadata. Until now, generating that understanding at broadcast scale required either manual tagging or bespoke machine learning (ML) infrastructure.

Elemental Inference Contextual Metadata uses AI to generate rich, scene-level metadata extracted from live video in real time. Computer vision models run in parallel with encoding to identify objects, actions, brands, on-screen text, and sentiment from real video content. The metadata is emitted through a standard API, aligned to the Interactive Advertising Bureau (IAB) content taxonomy and the Global Alliance for Responsible Media (GARM) brand suitability categories. As displayed in the following flow diagram, this powers downstream workflows including automated highlight clipping, content discovery, contextual ad decisioning through Elemental MediaTailor, and content moderation, all without custom ML infrastructure.

In terms of Elemental MediaTailor Yield Optimization, this feature fills available ad slots from Amazon Ads inventory during ad insertion, turning dead air and slate video into monetized impressions. It delivers incremental revenue with no cost to enable and no additional infrastructure. Because the ads are inserted server side (stitched directly into the stream before it reaches the viewer), they play seamlessly on every device, can't be blocked, and transition without buffering. At launch, MediaTailor Yield Optimization is available to APS streaming TV publishers.

"Our team set out to monetize low-latency streaming without giving up the latency itself, which had not been done on our platform before. Through DSPORTS's coverage of the FIFA World Cup 2026, we held six seconds glass-to-glass with ads running across every match, built on AWS Elemental MediaTailor and Amazon CloudFront," explained Claudio Rodrigues da Silva, head of IT (Streamco)

The capability is built for large-scale live events like professional league championships, with low latency and fast response times. It remains brand safe by filtering demand by category to avoid competitive conflicts within the same break. For example, if a sports drink brand is running a direct-sold spot, MediaTailor Yield Optimization won’t fill an adjacent slot with a competing beverage advertiser. Publishers set their own price floors and category rules throughout.

In terms of monetizing low-latency streams with MediaTailor Low-Latency Ad Insertion, the company noted that AWS Elemental MediaTailor already delivers personalized, server-side ad insertion at scale.

MediaTailor Low-Latency Ad Insertion now extends that capability to low-latency streams, using HLS interstitials, a server-guided ad insertion (SGAI) approach. As audiences increasingly expect streams to keep pace with social (a goal scored, a breaking headline, a viral moment), publishers can no longer afford latency that lets the timeline spoil the moment before their stream delivers it.

AWS also stressed that these four capabilities share a design philosophy: intelligence layered inside the video pipeline, not bolted on after.

They all run within the same AWS Elemental services that power millions of live streams globally, with the same 99.9% service level agreements (SLAs), the same operational model, and no new vendors to onboard.

The value compounds across the stack. AWS Elemental Inference generates metadata that enriches yield decisions, MediaPackage Dynamic Multiview delivers personalized viewing and ad experiences at scale, and MediaTailor low-latency insertion help to avoid impressions being left behind regardless of how fast the stream moves.

Visit AWS at IBC 2026 in Amsterdam (September 12–15) to see live demonstrations.

LONDON—NDI is collaborating with NVIDIA to develop AI-powered workflows that enable broadcasters to create and distribute multilingual content in real-time, the company said.

By combining NDI-native media connectivity with NVIDIA AI technologies, including NVIDIA NIM microservices, the companies are making content immediately accessible to audiences in their preferred language, from live events and breaking news to sports, entertainment and corporate communications.

NDI and NVIDIA are working to enable multiple language experiences to be generated from a common media stream. For broadcasters, this means the same source content can be adapted for different audiences without replicating production operations for every language.

During internal testing of a workflow of 10 languages, the new method was able to achieve the same results with eight times less video carried.

"Broadcasters have spent decades trading audience reach against distribution cost," said Miguel Coutinho, head of NDI. "Together, NDI and NVIDIA are enabling a fundamentally different model, where a single media workflow can support multiple language experiences. This has the potential to significantly reduce bandwidth and distribution costs while making multilingual content accessible to far larger audiences."

The workflows support real-time translation, lip-synced dubbing and regional language adaptation, with the potential to support localized advertising as well. They are designed to fit into existing broadcast and media production environments, so organizations can add AI-powered localization without having to rebuild their current operations.

The solution is currently being tested. Proof-of-concept demonstrations at IBC 2026, Sept. 11-14, in the RAI Amsterdam Convention Center, can be scheduled in advance by contacting NVIDIA or NDI representatives.

See NDI at IBC 2026 stand 10.A41 and NVIDIA at stand 14.FT26 (in the Future Tech Zone.)

More information is available on the NVIDIA and NDI websites.

SAN JOSE, Calif.—Adobe will highlight new AI-based tools to enhance video editing, effects and audio processing during IBC2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

The company will unveil a new generative media tool that enables Adobe Premiere editors to select a video or audio as well as a video and audio gap in their timelines, describe what is needed and generate clips that fit the context of the edit.

Similarly, the AI Assistant in After Effects, now in public beta, allows motion designers to describe what they want in their on words and carry out the steps required from reorganizing projects with thousands of layers to creating motion effects and expressions without writing code.

New AI audio tools help editors clean up recordings by separating sound sources, adjusting reverb, removing unwanted elements like unlicensed music and splitting overlapping dialog into independent tracks for separate mixing and editing.

The intuitive new Generative Media Tool in Premiere generates context-aware, editable video and audio clips. Editors may choose from Adobe Firefly, Google Veo, Kling, Runway and Luma model to create with.

Among the tools available in the Premiere task bar are Generate Video, Generate Sound Effects, and Generate Soundscape and Generate Music, both of which are in beta.

New AI audio tools in Premiere enable editors to clean up noisy recordings, bad takes and overlapping dialog. The tools include Enhance Audio, offering noise reduction and independent control over dialog, sound effects and other audio characteristics of an individual clip; Separate Crosstalk to split speakers into their own tracks; Dynamic Audio Ducking to balance dialog and music automatically; as well as other sound tool improvements.

Adobe is also leveraging AI to address workflow challenges in After Effects. AI Assistant, available in beta for After Effects, offers newer users a more intuitive way to work in the program and gives experienced users a way to execute once tedious, multi-step operations more quickly.

AI Assistant enables users to describe what they want in plain language and reorganizes large projects without requiring code to be written.

See Adobe at IBC2026 stands 13.D501 and 7.B35.

More information is available on the company’s website.

HACKENSACK, NJ—LiveU, a global provider of live IP-video solutions, announced today that The Associated Press will deploy LiveU Ingest, LiveU Transceivers and LiveU IQ connectivity across its global operations—including the industry's largest deployment of LU900Q intelligent production units—bringing AP’s global LiveU hardware fleet to over 100 encoders.

The LU900Q uses new AI-driven connection management and eSIM technology to draw on mobile data networks around the globe. The technology will support a range of AP operations, from live feeds to editorial and multicamera workflows used by the global news organization’s production arm, AP 360.

"We’re excited about expanding our work with LiveU to equip our journalists with the technology to transmit live wherever the story takes them,” said Matthew Durbin, director of video technology and operations at AP. “Additionally, using LiveU Ingest with our MAM system gives us greater flexibility and speed, allowing us to move even faster and more efficiently from capturing content to distributing it to our customers around the world.”

Alongside the LU900Q deployment, AP has integrated LiveU Ingest with its cloud-based MAM system. Supporting up to 10 simultaneous live channels, the integration streamlines how content moves from the field into AP’s workflows, helping teams get to near-live and on-demand output more quickly.

AP is also transitioning its infrastructure to a SMPTE ST 2110 IP environment, deploying five LiveU servers alongside a dedicated SDI server. LiveU Transceivers enable AP to send and receive feeds with content providers as needed, giving teams flexible access to live sources across the network.

LiveU IQ's intelligent network switching continuously optimizes across available network operators in real time, helping maintain consistent transmission quality as connectivity conditions change.

AMSTERDAM—swXtch.io, a global provider of software-defined networking solutions for media, has launched an AI-based broadcast engineer platform which it says is designed to remove the infrastructure and networking complexity behind live media workflows.

abbe removes the requirement for operators to configure networks, cloud infrastructure, compute resources, and AI software in media routing and interface workflows, according to the company.

abbe takes a conversational description of the desired outcome and deploys the necessary infrastructure, networking, and software required to make the workflow run and does so in the most economical way while meeting performance requirements.

abbe is a cloud-agnostic orchestration layer, able to deploy live media and AI workflows across any provider including Microsoft Azure, Oracle Cloud Infrastructure (OCI) and Amazon Web Services (AWS). Workloads are located based on user requirements including optimizations for cost and latency, without forcing the operator to design a different solution for each cloud environment.

The initial capabilities being shown at IBC focus on two areas where live media teams face significant operational complexity: managing live media transport and deploying AI into production workflows.

For live media networking, abbe provides SRT management and control, enabling operators to ingest, monitor and distribute streams globally without manually configuring the underlying infrastructure. abbe is designed to automate decisions around where and how live media moves, helping operators maintain reliable, high-quality feeds while reducing the manual intervention traditionally required to respond to changing network conditions.

For AI workflows abbe will demonstrate a live audio processing workflow using NVIDIA models and other select partners. An operator can describe the desired outcome and abbe stands up the cloud infrastructure, networking, security, and software required for the audio processing use case.

The future of abbe is much broader than the initial iteration being shown at IBC, swXtch.io said.

abbe treats AI models as interchangeable components within a live workflow. Operators can select and test different models, chain models together, compare performance, and swap from one model to another easily and quickly. abbe separates what an operator wants to accomplish from the increasingly complex infrastructure, networking, and knowledge required to accomplish it.

NVIDIA models provide the foundation for abbe's initial real-time AI capabilities and swXtch.io is already expanding abbe's support across additional NVIDIA AI models and capabilities over time.

“The AI models are becoming incredibly capable but putting them into a live production still requires expertise across networking, cloud infrastructure, and AI software,” said Brent Yates, CEO of. “abbe is designed to remove that complexity. You describe what you want to accomplish, and abbe stands up everything needed to make it work. And because workflows are not locked to one model, you can easily optimize it as the technology changes. abbe simplifies AI for live media.”

NORTH SYDNEY, Australia—AI-Media will showcase its latest advances in multilingual AI, demonstrating how broadcasters and media organizations can caption, translate, voice and localize content at scale across live and recorded workflows, during IBC 2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

AI-Media will showcase the complete LEXI Suite, two new LEXI Encoders, LEXI Direct and an expanding ecosystem of technology integrations as well as innovations under development that point to new ways audiences can experience multilingual content.

“As broadcasters look to reach increasingly global and multilingual audiences, language is becoming a critical part of the media technology stack,” said Tony Abrahams, CEO of AI-Media.

“What differentiates AI-Media is our ability to bring together a comprehensive AI language platform, broadcast-grade infrastructure and deep integration across the media ecosystem. Whether customers connect through our encoders, directly to LEXI or through the technology platforms they already use, we’re making it easier to deploy multilingual capabilities at scale.”

At the center of AI-Media’s IBC presence is the LEXI Suite spanning LEXI Text for real-time AI captioning, LEXI Translate for multilingual captions, LEXI Voice for AI-powered multilingual voice, LEXI AD for audio description and LEXI Recorded for captioning, translation and localization of recorded content.

Together, the LEXI Suite provides broadcasters with a scalable platform for applying AI-powered language and accessibility capabilities across live and recorded content.

Making their European debut at IBC 2026 will be AI-Media’s new LEXI Text Encoder and LEXI Voice Encoder, purpose-built to bring AI-powered language capabilities into professional broadcast environments.

Supporting SDI, IP and ST 2110 workflows, the new encoders give broadcasters greater flexibility, through increased processing power, to deploy AI-generated captioning, translation and multilingual voice within existing infrastructure while supporting the transition to next-generation IP-based production.

Beyond AI-Media’s own hardware, LEXI Direct provides direct, programmatic access to LEXI, enabling its AI-powered language capabilities to be integrated into third-party platforms, applications and workflows.

AI-Media is also expanding its European infrastructure, with EU-based data processing for LEXI planned to be available by January 2027.

IBC visitors will also get an early look at LEXI Link, a proof of concept that delivers live captions, translations and multilingual AI-generated audio directly to viewers’ devices.

A photo accompanying this announcement is available at:https://www.globenewswire.com/NewsRoom/AttachmentNg/cdaa0981-2db5-4da3-8666-1b30bea36f6d

See AI-Media at IBC 2026 stand 5.C34.

More information is available on the company’s website.

MILAN, Italy—Brightcove has launched Brightcove Gen 2, the next generation of its platform designed to give video teams more capacity to create, distribute, engage and monetize content at scale.

The update includes more than 22 new enhancements and 30+ platform advancements and is designed to allow media companies to reach more audiences, increase engagement and unlock more revenue; automate work, streamline workflows and reduce complexity and combine a more powerful, reliable and secure platform with faster innovation across the entire video workflow, Brightcove said.

These capabilities build on a year’s worth of new solutions and features across the platform. Recent additions include the redesigned Prism user interface, expanded monetization tools, new localization and accessibility capabilities, Next-Gen Live, and AI-powered features that help automate workflows and reduce manual work.

Among the features completely new to Gen 2 is the AI Agentic Hub, which will be unveiled at IBC 2026, Sept. 11-14 at the RAI Amsterdam. The Hub enables teams to move beyond step-by-step tasks by allowing users to define an outcome and have AI agents coordinate the actions and workflows needed to achieve it, according to the company.

AI agents can work across Brightcove’s functionality, meaning they can analyze video data, generate insights, and take action on those insights across the platform—from managing content and metadata to optimizing workflows and configuring experiences. Users interact with the agents through a chat-based interface, making it possible to automate complex, cross-platform workflows and move from insight to action faster.

The AI Agentic Hub is already available to customers in production.

Brightcove will be in Stand 5.A90 at the RAI Amsterdam.

BERKELEY, Calif.—Eluvio today announced its plans for the 2026 IBC Show, Sept. 11-14 at the RAI Amsterdam, focusing on new advanced features in its Global Broadcast Fabric, the latest generation of the Content Fabric protocol and global infrastructure, as well as new advances in its Universal & Dynamic Video Intelligence architecture and Eluvio Video Intelligence Editor (EVIE)

At IBC, Eluvio will demonstrate the Global Broadcast Fabric’s live broadcast distribution architecture—a decentralized, zero-copy system that replaces satellite distribution, fiber point-to-point connections, and ground-to-cloud multi-point egress for live broadcast feed distribution, extended with new live-operations and monetization capabilities. One decentralized Content Fabric distribution simultaneously serves every downstream taker just-in-time — B2B broadcast affiliates and D2C consumer endpoints — from a single ingest workflow without duplication, according to the company.

Eluvio says Content Fabric “is powering thousands of D2C live games and streaming events and hosts hundreds of thousands of live, archive, and library titles for premium brands and creators — with 10x cost savings over legacy CDN and media cloud infrastructure at scale.

Improvements include :

• 8x increase in live stream cross-variant serving; <=30ms segment delivery latency; up to 4x scale of DRM encryption variants; zero-impact global maintenance; and instant-on HFR streaming.
• Stereoscopic HFR 4K (SBS and MV-HEVC), Dolby Vision and Dolby Atmos, HDR/HDR10+, full Widevine parameterization, AV1 (upcoming), optimized asset structure for hundreds of language and subtitle tracks.
• Powered by new Media Wallet v3 and Creator Studio CMS, allowing Eluvio to provide best-in-class TV, browser, and mobile native white label D2C OTT properties with advanced UX branding, interactive experiences, and configurable live, VOD and clip based content presentation and management.
• The ability to configure and deploy unlimited D2C OTT streaming and archive monetization apps for TV/mobile/browser, B2B portals, and Pocket TV microsites with fast multi-view, integrated DVR, automatic live and VoD content slating, and up-next autoplay. New multi-view sidebar, “In This Video” AI data panel, and expanded entertainment and sports layout options provide a flexible and outstanding UX experience for fans with no code deployment. Fully integrated with the Eluvio Video Intelligence Editor (EVIE), browse and publish zero-copy EVIE clips and compositions.
• Full SVOD/TVOD (rental and ownership) entitlements, match-based live entitlements, seamless JWT/SSO, and fully integrated Apple Pay, Google Pay, and Stripe in a single checkout flow. CableLabs-compliant Title Metadata API with territory-based offers and delta-only global updates.
• A fully white-labeled microsite for live and episodic content sales with zero friction: no login required, single-click Apple Pay and Google Pay, and magic links for return access. No PII collected. Instantly embeddable as a URL in any social post, paid ad, or CRM email. Deployed by a Tier 1 US broadcast network in 2026.
• Real-time analytics spanning B2B SRT/TS and D2C HTTP streams; global receiver map with per-receiver performance stats; expanded audience metrics; client-side QoS stats; and sales transaction reporting by currency, product, and country.

Eluvio will also showcase Eluvio AI and Eluvio AI and the Eluvio Video Intelligence Editor (EVIE), a new architecture for universal dynamic video intelligence.

According to the company, Eluvio AI is "the first commercially available inline, frame-accurate, multimodal AI built natively into a media platform — running inference on live and VOD content at frame and segment level with zero file copies, zero file movement, and zero transcoding, across open-source, custom, and third-party models."

The Eluvio Video Intelligence Editor (EVIE) provides the media-facing application layer for this intelligence, allowing users to inspect, search, validate, edit, and act upon AI data while remaining synchronized to the underlying video. The new EVIE Titles & Events experience brings the complete AI stack together around a title—such as a film or television program—or an event, such as a live sports match.

“Eluvio AI is fundamentally different from point AI solutions because the intelligence runs inline, with frame accuracy, across live and archival content — without the cost and delay of copying and re-transcoding media before it can be processed and ensembling the power of individual models with frame-accuracy,” said Michelle Munson, CEO and co-founder of Eluvio. “The AI is built directly into the video pipeline of the Content Fabric, rather than added afterward as a separate cloud workflow.

“Everything from identifying action, players, celebrities, speakers, or brands to turning that intelligence into highlights, vertical videos, compliance reels, or personalized content happens in place against the source media and has no limits on size, duration, or ensemble scale,” Munson added. “The result is dramatically greater efficiency and speed, while making AI intelligence immediately actionable for personalization and monetization. At IBC, we’re excited to show broadcasters and rights holders these capabilities running across both live sports and premium content.”

Eluvio will be in Stand 8.MS5 at the show. For more details, visit https://ibc.eluv.io.

BERLIN—TiVo today unveiled significant enhancements to its TiVo OS media platform, expanding generative AI-powered content discovery experiences, more free streaming content, enhanced sports experiences, interactive commerce capabilities and platform optimizations that the company says could reduce costs for smart TV manufacturers.

TiVo, a wholly-owned subsidiary of Xperi, also announced the appointment of Tal Bone as senior vice president and general manager of TiVo OS. Bone, who brings more than a decade of experience building and scaling global smart TV and entertainment platforms most recently served as vice president of global product and chief technology officer at VIDAA, Hisense's smart TV operating system.

The company made its announcements in advance of the the IFA 2026 tech show, which takes place Sept. 4-8 in Berlin.

Expanded TiVo Channels Offering
TiVo announced that it has added hundreds of new global and local FAST channels to its TiVO Channels platform and added a new mini guide for faster channel navigation and personalized content carousels that offer relevant programming based on viewers’ preferences.

TiVo has also enhanced sports discovery across search, recommendations and the home screen on its OS, allowing viewers to more easily discover, follow, and access live games and sporting events through improved surfacing of sports content and real-time event promotion directly within the TiVo OS experience.

And in a nod to expanding its presence overseas, particularly in Europe, TiVo also announced that its OS now supports DVB-I, a protocol that adds IP capability to the DVB standard. DVB-I enables broadcasters to deliver television content over the internet while simplifying access for consumers. The enhancement allows viewers to discover and watch local broadcast channels without requiring a traditional aerial or antenna.

TiVo has also significantly reduced the TiVo OS memory footprint, enabling deployment on devices with as little as 1 GB RAM and 4 GB eMMC. These improvements are designed to help reduce bill-of-material costs, allow for more efficient hardware configurations, and expand deployment opportunities across a wider range of smart TVs and connected entertainment devices, the company said.

AI Enhancements
TiVo is also collaborating with IRCODE in a partnership that now combines AI and computer vision technologies to recognize on-screen content and enable immediate viewer interaction on its OS, unlocking “new opportunities for commerce, content discovery, advertising and companion experiences, allowing consumers to engage with content in entirely new ways while creating new monetization opportunities for partners,” according to the company.

TiVo said it plans to implement the soon-to-be released AI-powered discovery product, Agent TiVo, which is designed to enable consumers to navigate entertainment through natural conversation and help them discover content more intuitively and efficiently. Rather than relying on traditional keyword searches, viewers will be able to describe what they're looking for and receive personalized recommendations and guidance, creating a richer and more engaging content discovery experience, the company said.

LEXINGTON, Mass.—Signiant will showcase the latest evolution of the Signiant Platform at the 2026 IBC Show, Sept. 11-14 at the RAI Amsterdam.

Topping the list is Media Shuttle's new Intelligent Transport, which allows customers to take greater advantage of all their high-bandwidth infrastructure with multi-threaded and multi-gigabit transfers that adapt to live network conditions.

Also new is Signiant Pulse, a new line of secure connected services designed to help media organizations work with content where it sits.

Signiant Pulse includes:

• Pulse Essentials: Unified content visibility, access, and action across every connected storage location, included free with the Signiant Platform
• Pulse Review & Approve: Collaborative, frame-accurate content review without needing to upload or download content
• Pulse Plus: AI-generated descriptions, tags and transcripts using the customer's chosen AI provider rather than a vendor-hosted model
• Pulse AI Studio: Multi-step AI agent workflows across enriched content libraries, with MCP-governed access and usage-based cost controls
• Signiant MCP Server: Connects MCP-capable AI clients, including ChatGPT, Claude and Gemini, enabling agents to search, validate and route content while operating within existing permissions and audit controls that govern transfers

Signiant will also showcase Signiant Verify, which enables media to be checked against delivery specifications before it is transferred. Content that fails validation can be held and suppliers will be notified before submission, rather than after delivery as well as Verify aiQC, which extend Verify’s capability with deeper inspection of the picture and sound.

Signiant will be in Stand 5.C74.

BRUSSELS, Belgium—Mediagenix, a provider of smart content solutions “Mediagenix Curation,” a new solution for managing content presentation and discovery across streaming services.

The announcement comes a year after the company announced the integration of Spideo’s humanized content recommendations, personalized discovery, and catalog exploration capabilities into its flagship Title Management solution. Mediagenix acquired Spideo in 2024.

The company says Mediagenix Curation solves the complexities of delivering personalized experiences at scale by combining editorial control with automation and personalization “to execute content presentation strategies at scale.”

Integrated across the Mediagenix ecosystem, the new curation solution helps media companies unify editorial and algorithmic curation by combining human creativity and editorial control with data-driven recommendations in one workflow; give editorial and product teams direct control over content presentation; launch and iterate pages and rails faster without engineering dependency, and increase engagement and retention by surfacing the right content at the right time for the right audience.

“Streaming has moved beyond the question of simply having great content; the challenge now is making sure every viewer can discover the right content at the right moment. That creates a tension between the scale and intelligence that automation can bring, and the editorial judgment that gives a service its identity. With Mediagenix Curation, we’re bringing those two forces together, giving editorial teams the control to shape the experience while using automation and personalization to execute their strategy at scale,” said Patricia Blanco, Product Manager of Mediagenix On Demand and Curation.

“Over time, our ambition is to connect that viewer experience much more closely with the wider content lifecycle, so that what audiences discover and engage with can help inform how media companies plan, schedule and ultimately get more value from their content.”

Mediagenix will demo Mediagenix Curation at Stand 1.B57 during the 2026 IBC Shoiw, Sept. 11-14 at the RAI Amsterdam.

DENVER, Colo.—Comcast Technology Solutions (CTS) today introduced a comprehensive suite of end-to-end AI-powered workflow applications for broadcasters, content owners and operators worldwide and announced it will showcase them during IBC 2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

Building on the foundation of CTS’ VideoAI platform, these new applications deliver AI as practical, integrated solutions to real-world content production and management challenges.

CTS provides end-to-end, production-ready workflow integration that embeds AI capabilities into complete, deployable applications requiring no additional specialist AI knowledge or developer requirements. The new applications are designed to work across the company’s full product portfolio, including Comcast Media360 for broadcasters and content owners, Comcast Sports360 for sports rights holders and standalone deployments of CTS’ Cloud Video Platform (CVP) for operators.

“The video industry is ready to move past AI hypotheticals and onto production-ready applications that solve real problems, generate new business opportunities and integrate seamlessly into the workflows they already rely upon,” said Bart Spriester, senior vice president and general manager of streaming, broadcast and advertising at CTS.

The next-gen AI applications from CTS include:

• Video Verticalization: Using AI-driven smart cropping technology, CTS can automatically convert landscape video content into portrait format for social media syndication, intelligently identifying the action center of each scene and making intelligent cut or pan decisions. 
• Localization of Regional Languages: Leveraging AI-generated voices, CTS can automate dubbing workflows that previously required human voice talent. The application can extract audio from soundtracks, preserve ambience and music, translate dialog, select appropriate voice matching, relay the finished audio back into the content and generate automated captions.
• Smart Chapters: For distribution-ready workflows combining content and ad insertion, CTS can create AI-driven detection of intros, credit rolls, and ad break candidates, enhanced with weighting algorithms to select the optimal set of ad break points and automatically trigger stream conditioning, transcoding, and packaging.
• Metadata Enrichment: CTS will automatically generate scene and asset-level metadata and pass it into Cloud Video Platform metadata files, enabling semantic and natural language search capabilities. 
• Automated Quality Control: CTS will also offer AI-powered virtual eyes-on-glass QC checks, including black screen detection, missing audio identification and other content integrity verifications. 
• Intelligent Clipping: CTS will also offer natural language query-driven clip identification and selection, allowing editors to find key moments within long-form content. 

CTS’ new applications are integrated into CTS’ Cloud Media Processing (CMP) engine, a flexible, programmable workflow orchestration layer. Processors can be inserted as pre-processors, content manipulation steps or post-processors, enabling users to activate individual AI capabilities within their existing workflows without rebuilding their technology stack.

See Comcast Technology Solutions at IBC stand 5.C80.

More information is available on the company’s website.

Alongside the many technological changes occurring in this era, robotics continues to evolve with new capabilities in artificial intelligence. Of those more recent advances and updates, generative AI took the lead, but there’s a new tech in town and it’s going “fully autonomous.”

In my Cloudspotter’s Journal columns, I have shown by example that the basics of next-generation cloud computing now include an advanced “cloud” infrastructure, shifting toward AI integration, edge computing and cross-cloud federation (coming up in October). Crucial elements include “AI-first architectures,” “agentic data systems” and “distributed cloud-to-edge” connections and their associated networking.

The importance of connecting the cloud to the world of AI cannot be underestimated. At first, it seems to be a bit far-fetched and beyond the reach of everyday use, but hold on—artificial intelligence is now “everywhere,” with a wider definition and an expanded dimension touching all walks of life. Most evident today is the explosion of data center activity popping up everywhere. Only a few see this as an important element of our tech future, but the data centers of today and tomorrow are “the cloud,” with compute power, storage and interconnection across the globe.

In the not-too-distant future, these new data centers will be self-managed and, in many cases, autonomous in nature. They will become the backbone for AI activities as their integration grows.

In this installment, we take a broad overview perspective of some new AI-related terms and how they generally apply to workflows, data centers and AI:

• Artificial Intelligence Integration: Based upon custom AI agents, robust LLM integration and AI-data engineering. As stated in Google Search, “AI integration is the process of embedding artificial intelligence into existing systems, workflows and applications to automate processes, generate insights and optimize performance.”
• AI Systems Integration: The fundamental elements associated with this widespread migration, modernization and optimization of services using a leaner stack are being accomplished with zero disruption. An “always-on digital workforce” is a key element, constructed as a unified platform built on at least three integrated layers: Data Quality, Agentic AI and Plain-Language Interfaces.

Data Quality (DQ)
Data Quality (DQ) encompasses elements of trust and Autonomous Data Engineering—the automation of jobs for data analysts, data engineers and operations (see workflows depicted in Fig. 1). DQ aims to improve the accuracy, completeness, consistency and reliability of the data used to train, test or run machine-learning models and AI systems. DQ generally includes model accuracy, which aims to ensure all AI outputs are trustworthy and to prevent error factors where poor data leads to biased or incorrect results.

DQ concepts include machine learning models that depend on “clean inputs”—free of duplicates, errors or misrepresentations, aka missing values or skewed anomalies.

Modern platforms use other AI tools to automate DQ checks and build validation rules that scale. Validation rules are those surrounded by an AI simulation of human intelligence in machines specifically programmed to think, learn and make decisions—i.e., utilizing building blocks typical to AI systems that include data (i.e., numbers, characters, media images—audio, video, etc.) and operations which are performed by using compute processes.

• Algorithm(s): Basically a sequence of calculations or rules used to solve a problem employing data that is “optimized in terms of time and space.” Such relative data should fit the time, place and application, and must provide suitable results that resolve the problem constructed of appropriate prompts with sufficient depth to properly answer the question “posed” of the associated content. 
• Model: Sometimes referred to as an “agent,” a model is a combination of data and algorithms used to generate the response. Once you have a model, you can constantly provide it with new data and algorithms and continuously refine it. Fundamentally, the goal is to perform these actions autonomously.
• Response: Outputs generated as responses from models, otherwise known as the results.
• Ethics: The “moral principles” and “guidelines” from responses. These and related fundamental principles ensure that the responses (replies, reactions and/or outputs) from the AI systems “contribute to positive social, economic, and environmental impacts of the organization and the community.”

One significant application of AI is automating tasks that do not necessarily require human intervention during routine operations. This brings on some relatively new definitions for workflow and actions—e.g., idempotent, which means an operation that can be applied multiple times without changing the final result beyond the first time, and Customer Lifetime Value (CLV). When combined, idempotency and CLV can match analytics or calculations without double-counting revenue or corrupting historical cohorts—i.e. the use of past records to identify groups of people with or without a specific exposure.

The latest evolution in AI-driven automation is known as Agentic AI.

Agentic AI for RPA
Agentic AI is the next step in automation. Autonomous or semiautonomous artificial intelligence systems can independently plan, make decisions, use external tools and execute multistep workflows to achieve a specific goal with minimal human supervision. Robotic Process Automation (RPA) is rule-based, using software “bots” to mimic human actions. RPA automates repeated tasks (invoicing, inputting data, extraction and validation) which have since evolved with new AI capabilities. In principle, that evolution has stepped into various levels of agentic automation used to aid in determining the level of agents your organization may need; agentic workflow automation in action, or how those AI-powered agents perform; and how to scale agentic automation—responsibly and securely—while autonomously evaluating foundational skills aimed at end-to-end task completion.

The main types of automation (in robotics) include:

• Attended RPA: Bots that run on a user’s computer to help with live tasks like customer calls. 
• Unattended RPA: Bots run on servers in the background to complete large batches of work automatically.
• Hybrid RPA: Blends both attended and unattended approaches so humans and bots can work together on complex jobs.

In addition to those RPA/human modes, those rational and easily manipulated sets of actions or instructions—including reporting and outputs—are orchestrated in plain language instead of software-driven expressions in specific forms of new or complex terms that must first be thoroughly learned and trained.

Plain Language
For an AI interaction to be “conversational,” the prompts and stages should repeatedly master the following steps in its sequences:

• Removes Jargon: Finds hard-to-read technical words, acronyms, or legalese and swaps them for everyday terms, with “audience identification” obviously being a prime focus on both output and delivery. For example, a response for a lawyer would be output differently for an administrator without a legal background.
• Shortens Sentences: Breaks down long, tangled sentences into short, direct thoughts aimed for a C-level executive set, TV/radio news reporter or professional-level manager.
• Active Voice: A sentence structure where the subject performs the verb’s action, following a clear pattern: actor, verb—targeting its searches for passive phrasing and changing it to clearly show who is doing what.
• Layout Improvement: Outputting clear headings and bullet points so text is easy to scan and reading for understanding is elevated smoothly and rapidly.

Assuring Data Quality
A part of maintaining and assuring Data Quality is documentation (especially if auto-generated). Docs are a foundational principle in assuring Data Quality and are extremely important when assembling any AI platform. Having a consistent and accurate reference set that includes the stages and steps discussed is essential to the AI system’s intelligence for long-term maintenance of the large model learning system, for both immediate and future or long-term support of the system overall. Instructions on documentation integrated with the “checks and values” portions of a system are essential.

Elements crucial to AI-developed outputs (Fig. 2), based on the prompts submitted and the audience you are addressing, include accuracy, where data matches real-world values and facts; completeness, with no essential fields or values missing; consistency, where all information matches across different systems, tables or equations; that data is fresh and timely, appropriate to the topics and audience and easily available when needed; and validity, where data follows defined (business) rules, formats and constraints, is unique and does not contain duplicate records.

Appropriate expectations are part of the primary requirements in qualifying the validity of an AI system and integration. These are some of the guidelines most solutions or outputs will produce with a properly utilized agentic AI or general practices as modeled across many levels of industry—providing a good checklist and process for relatively effective and useful autonomous applications and solutions.

The old-fashioned, one-screen display monitor in TV studios, OB trucks and master control rooms (MCRs) had to evolve technologically because it did only one thing. Or, to be more accurate, because it showed only one thing. The result was the multiviewer, which was—and still is—able to show multiple image sources simultaneously.

While that was a massive step forward and made for more extensive and efficient monitoring, the multiviewer itself is now evolving further. The demands of modern broadcasting and streaming call for something that not only displays pictures but is part of an overall production and distribution infrastructure.

The multiviewer has evolved from a simple “display wall” to a “software-defined monitoring and intelligence platform,” said Suzana Brady, senior vice president of worldwide sales and marketing at Cobalt Digital. This allows operators and engineering teams to monitor ever more complicated infrastructures, she explained. “The focus has shifted from simply seeing signals to helping operators monitor, manage and respond to increasingly complex workflows efficiently,” she said.

Shifting Focus
The change is driven by three current trends in broadcast technology: hybrid SDI/IP facilities becoming the norm; the continuing expansion of remote/cloud production; and broadcasters wanting fewer dedicated monitor systems and more integrated tools for monitoring, operations and processing, she said.

Another transformation in how multiviewers are expected to operate is identified by Lawo Product Evangelist Paul Scott. Bigger broadcasters are looking for more flexibility from their monitoring displays, which are often fixed multiviewer installations—typically one per studio—and can be expensive in terms of capex when multiple studios and events are involved, he said.

Manufacturers now offer various options to reduce capex for multiviewing. Lawo’s HOME IP management platform, which includes a range of specialized apps, is based on readily available COTS hardware and works with native cloud and containerization technologies, including NATS and Docker, and monitoring tools like Grafana or Prometheus.

The word “hardware” might seem incongruous when multiviewers are now described as either “software-based” or “software-defined,” Scott agreed. However, he explained, the shift has been away from dedicated processing hardware that performs only one function.

More Formats
A big shift since last year has been the expansion of formats users now work with, said Ketan Patel, project manager for multiviewer systems at Evertz.

“People want to have the mixed signal monitoring or multiviewing of the mixed signals, whether it’s ST 2110, SDI or compressed feeds,” he said. “But now JPEG XS is getting added to the mix due to interfacility connections.

“On top of that, we are noticing customers looking for more integrated systems,” Patel added. “They want a single surface where they can manipulate the multiviewers, do their routing and analyze the signals. It’s more like dashboarding, so they want one surface to bring that all together and simplify day-to-day operations.”

John Mailhot, senior vice president for product management, playout and infrastructure at Imagine Communications, confirmed “more functionality” is being “dashboarded” and moved into the multiviewer. This has made multiviewers “the most important part of the facility,” he said, because they connect the operations team to what they are doing.

“The multiviewer is becoming more of an information hub,” he explained. “This is driven by a need for economy within the television operation. In a historical small TV station, you’d have one master control operator running the channel.

“Now that same operator is trying to manage the main channel, cable distribution, OTT, a side channel and ENGs [electronic newsgathering],” Mailhot continued. “Multiviewers are where that all comes together.”

As for the signal formats, Mailhot also predicted the hybrid model would be adopted, adding that SDI will “be with us forever—or at least another 10 to 20 years.”

SDI is among many signal formats that today’s multiviewers must accomodate. As Brady observed, these also include ST 2110, compressed IP streams and cloud feeds. But though the market “has shifted increasingly toward software,” she pointed out, it has not moved entirely to the cloud—relying on gateways between different formats and IPMX, which supports the convergence between broadcast and Pro AV workflows.

The Home MCR
IP and internet connectivity have also furthered adoption of “MCR at home,” where operators working remotely can access all sources and functions they would have on-prem. This technology is typically deployed as a distributed MCR rather than a completely remote setup, Brady said, with the critical signal processing taking place in a secure data center or broadcast facility while operators work through browser-based interfaces on an IP connection.

Lawo’s Scott said MCR at-home functionality can be facilitated through a second output from the multiviewer head as an SRT (Secure Reliable Transport) feed. The company has seen more demand for remote video monitoring, for which it has introduced Workspaces, an HTML-5 virtual user interface that can be used on desktop and laptop computers, tablets and phones, he added.

Evertz has also adopted the MCR at home. To do this, according to Patel, all the necessary controls—not just the multiviewer function—have been integrated and made available on a single browser. Alongside this, Evertz is integrating AI capability into the analytics feature set, including alarm and telemetry data.

“Those are being analyzed to make smarter decisions to present to the users,” Patel explained. “We haven’t automated it completely [to the point] where AI is driving everything, [but] those will be future steps.”

Agentic AI is the form of the technology most suited to multiviewing and monitoring, as it has the capacity to learn what to do. AI agents are “one of the most significant developments in the multiviewer market over the next few years,” Cobalt Digital’s Brady said.

“Everybody is in the experimenting phase” with AI, said Mailhot, noting that Imagine is running “a number of initiatives” around how AI systems within a facility interact with other equipment. “And designing how that works in a way that is both repeatable, reliable and correctly safeguarded,” he added. “You want to make sure these agentic systems can do something useful but, at the same time, that they don’t do anything to endanger your production.”

At this rate—and with the perceived potential of agentic AI—it is likely that multiviewers will have moved on considerably by this time next year.

I have written about supercomputers in the pages of TV Tech for more than six years. I even had an ABC director tell me my musings on computer dominance in broadcasting were pure folly and that I was “full of it.” However, my earliest contemplations did not take into account learning models which, to me, now further legitimize the possibilities of AI in broadcasting.

Let’s use my friend at ABC as an example. Bob has less than a dozen cuts in his directing repertoire, with only a handful of permutations between them—very predictable. Now, if you take it to the next level, Bob-Bot can remember these camera sequences and their outcomes, plus how effective their entertainment value was. You could even teach Bob-Bot the patterns of different directors and producers and mix up a pretty good show.

FIFA World Cup soccer and Host Broadcast Services have led the way in advancing sound quality and also in developing computer-assisted sound.

Not only was the concept of mixing matches in the broadcast center’s master control developed at the World Cup, but Lawo also created a mixing algorithm that compares sound intensities from different microphone positions, selects the best ones and creates the most desirable sports sound. I wrote in the pages of TV Tech that I thought the 2022 World Cup was the best-sounding World Cup ever and better yet, the best-sounding sporting event ever!

From Assistant to Controller
The difference between the early AI systems and current (and future) systems is that AI brings the ability for the computer to learn and remember. For example, a machine model can combine audio sources and create a mix from the existing data. A learning model will be able to elevate the entertainment value with more and better permutations each learning cycle.

Computer-assisted is quickly moving to computer-controlled. It is easy to see how the entire production chain can be computer-controlled. Cameras do not need operators anymore, with autofocus and simple commands like “follow the ball” or “follow car No. 6.” I was resistant to “audio-follow-video” for many years because I thought the switch did not sound very good and subjective control was the job of the mixer. Basically, my prejudices were ego-related and not engineering-related.

The Lawo “mixing assist” compares sound levels from different microphones and adjusts mix levels for the most desirable combination of sounds. So, what about computer-generated sound fields and sporting sound effects, like what Ben Shirley and Rob Oldfield of Salsa Sound have been developing? The Salsa program not only can mix, but can change the timbre, texture and composition of sounds. I imagine a ball kick with a little thunder or dynamite explosion added to it. That is entertaining!

Entertainment vs. Reality
When gaming came along, I realized my role as a sound mixer was to entertain the audience and not necessarily document the sound image. Some sounds were boring or not easily captured, which is why, in the early ’80s, I started to use a sound sampler—a primitive analog computer to play back and enhance the sound field—everything from pit sounds and tire squeals to canoe rows and crowds. Engaging sound, camera work and graphics drive broadcast retention, but also cost money, unless perhaps there is a heavy dose of generative computer influence and output.

Every sport can develop an audience via the internet, and there is clearly an abundance of content that is captured and streamed. Not only are supercomputers good at automating tasks and improving efficiency, but they are capable of creating realistic content. How about nude beach volleyball? How will content production keep up? Through AI.

Supercomputers with learning and adapting capabilities are known as “generative,” where computers create new content using similar or existing data. Think about the commentators. You rarely see them, and they tell the viewer what they just saw and then read something about the person, place or thing that was just shown. It is called play-by-play and color, and I think these folks are on the way out.

I have read postings on LinkedIn for audio practitioners to train AI algorithms. That makes sense, since the power of artificial intelligence lies with its ability to ultimately learn and think for itself. It also seems that the best models have a deep reservoir of knowledge to build on.

A Better Model Me
But where is this knowledge coming from? Well, one significant avenue has been through theft of intellectual property.

America has long had a beef with China over intellectual property theft, but it is happening right here in the United States—with impunity. I don’t know who is to blame—the publisher or the AI company.

I heard on the news recently that Anthropic, a leading AI company that I thought had scruples, has settled a class-action suit for copyright theft, which included two of my broadcast publications with Focal Press. If you are going to train a computer to do my job, then learning the fundamentals of signal processing as well as the aesthetics of signal balancing will make a better Model Me.

All sound disciplines are changing and the evolution probably will not stop. No doubt, analytical tools for quality control are soon to arrive, if they are not already here. Things like distortion, phase and loudness are easily quantified and corrected. While working on this article, one of my sources said they have developed a profanity eliminator that works basically in real time and even in different languages.

I used to think the safest jobs in television were held by those who set up and maintained the equipment. I don’t see that as the case anymore when I see stories of Chinese robots playing soccer. Television broadcasts are not hard to set up, and any deficiencies can be compensated or covered up by the computer.

Are you scared yet?

CYPRESS, Calif.—For-A has announced the expansion of viztrick AiDi into an overarching AI technology brand encompassing two dedicated products: Go Vertical! AiDi and AiDi Sports Hub. Developed by Nippon TV and delivered globally by For-A, viztrick AiDi brings advanced AI capabilities directly into live production workflows, with on-device processing designed to deliver the speed and responsiveness live content demands.

The new product structure makes it easier for broadcasters, sports producers, and other content creators to choose the AI tools that fit their needs, according to the company. Go Vertical! AiDi addresses the growing demand for mobile-first video delivered in a 9:16 format, while AiDi Sports Hub applies AI to create more engaging live coverage with tools that provide additional context.

“AI is becoming an increasingly practical part of live production, but customers don’t need technology simply for technology’s sake,” said Hiro Tanoue, Director, Alliance Department at For-A Company Limited. “They need tools that solve real production challenges without adding complexity. By establishing viztrick AiDi as our overall AI technology brand and introducing Go Vertical! AiDi and AiDi Sports Hub as dedicated products, we can make it much clearer for customers to identify the capabilities that can make a difference in their workflows.”

Previously introduced at the 2026 NAB Show as a feature of viztrick AiDi, Go Vertical! AiDi is now a dedicated product built around AI-driven, real-time 9:16 cropping, For-A said. The system analyzes live video and automatically creates vertically formatted output optimized for social media and mobile viewing.

For broadcasters and content owners, that means existing 16:9 programming can be adapted for mobile audiences as the action happens, without creating an entirely separate production workflow. Go Vertical! AiDi supports automated tracking modes for sports including basketball, soccer, and baseball, as well as group subjects. Operators can also identify and track specific subjects, with the system automatically resuming tracking if a registered subject temporarily disappears.

The technology operates on-device rather than depending upon cloud processing - an important advantage when immediacy matters. Go Vertical AiDi features near-real-time processing for live 9:16 production, avoiding the five-to-ten-second delay associated with some competing approaches.

Go Vertical! AiDi also supports mobile-first coverage of news, conferences, red carpets, entertainment programming, and other live events where audiences increasingly consume content vertically.

AiDi Sports Hub takes viztrick AiDi technology in another direction, giving sports production teams AI-assisted tools that can add information, context, and visual storytelling to live coverage.

The system's capabilities include telestration, player tracking, player speed, distance and angle measurement, baseball runner speed, automated score graphics, and facial-recognition graphics. For-A said it is also developing additional capabilities including 2.5D/3D graphics, ball-trajectory visualization, sensor-based golf-ball trajectory, and AI-assisted automated program production.

Both Go Vertical! AiDi and AiDi Sports Hub are now available globally.

For more information about viztrick AiDi, Go Vertical! AiDi and AiDi Sports Hub, visit www.for-a.com.

MALAGA, Spain—At IBC 2026, Tedial has announced that it will demonstrate how broadcasters and media organizations can transform their operations through an AI-driven Media Supply Chain that combines intelligent automation, composable business services and user-centric experiences.

By combining AI, automation and composable architectures, Tedial said its solutions enable organizations to improve operational efficiency, accelerate content monetization and unlock new business opportunities.

“Our message is clear at this year’s show: Tedial powers the AI-Driven Media Supply Chain.” says Julian Fernandez-Campon, CTO, Tedial. “We help media organizations move beyond isolated AI tools to intelligent operations, where AI, people and workflows work together to deliver real business value, while maintaining the flexibility, governance and freedom to evolve as their business and AI technologies continue to advance.”

Tedial stressed that the future of media operations is not about adding AI tools onto existing workflows. It’s about reimagining the entire Media Supply Chain as an intelligent, connected ecosystem — one in which content, metadata, people and AI agents collaborate seamlessly, transforming media operations from manual and reactive processes into intelligent and proactive systems capable of operating at enterprise scale.

Tedial said its platform lets organizations automate complex media processes end-to-end using agentic AI, connect content silos across the enterprise, enrich assets with AI-generated intelligence, accelerate content discovery and reuse, and let users interact through natural language — all without coding.

This “AI Everywhere” approach allows organizations to adopt AI incrementally while retaining full control over governance, security and operational policy, choosing whichever tool or vendor suits each purpose.

Key AI capabilities on show at IBC from Tedial include:

• Automated metadata generation
• Speech-to-text and multilingual transcription
• Content summarization
• Scene and object recognition
• Entity extraction
• Content classification
• AI-assisted workflow automation
• AI-driven recommendations and decision support

AI-Powered Semantic Search

Traditional search depends on manually created metadata and predefined taxonomies. Tedial's AI-powered Semantic Search instead lets users discover content based on meaning, context and intent rather than exact keywords, using natural language queries such as “find interviews discussing sustainability”, “show all goals scored in the final ten minutes”, or “locate content featuring a specific brand or person.”

By leveraging AI-generated embeddings and semantic understanding, users can surface valuable content that would otherwise remain hidden within large media repositories — resulting in faster content discovery, increased asset reuse and greater monetization opportunities.

Introducing MCP: Model Context Protocol

At IBC 2026, Tedial will introduce MCP (Model Context Protocol), a framework that allows external applications, AI assistants and business tools to interact intelligently with the Media Supply Chain. Rather than relying solely on traditional integrations, MCP provides contextual access to content, metadata, workflows, business processes and operational actions, allowing external systems and AI agents to:

• Search content repositories
• Retrieve metadata and contextual information
• Trigger workflows
• Perform operational actions
• Execute business processes
• Collaborate across multiple platforms
• MCP extends the Media Supply Chain beyond system integration, enabling a new generation of AI-driven operational experiences.

Beyond Integration

Media organizations have spent years integrating systems. Tedial's approach goes beyond integration by connecting not only applications, but also business processes, users, content, metadata and AI services — creating an intelligent operational fabric in which information flows seamlessly across the organization. With a portfolio of more than 180 available integrations and over 300 systems integrated across Tedial's history, the result is a more agile, adaptable media ecosystem capable of responding rapidly to changing business requirements.

Composable Media Business

Tedial enables a Composable Media Business approach through its portfolio of smartPacks — preconfigured business solutions that combine workflows, metadata models, user experiences, integrations and AI services around specific media use cases, including Social Media, News, Sports, Localization and Content Delivery and more. Each smartPack delivers complete operational capability while remaining fully interoperable within the broader Media Supply Chain.

Built on Tedial’s NoCode platform, smartPacks enable organizations to configure and extend capabilities quickly, introducing new business processes in weeks rather than months to continuously while protecting existing investments.

By combining composability, AI and NoCode configuration, Tedial enables organizations to build a Media Supply Chain that adapts to their business, not the other way around.

New Media Portal for Content Exchange and Distribution

At IBC 2026, Tedial will also showcase a completely redesigned Media Portal, enabling broadcasters and media organizations to securely publish, distribute and monetise content with partners, affiliates, rights holders and external stakeholders.

Key capabilities include modern user experience, branded partner portals, advanced search and discovery, secure content sharing, self-service content access, AI-powered content discovery, and integrated review and collaboration workflows.

The new Media Portal transforms how organizations make content available to external ecosystems while maintaining governance and control.

At IBC2026, Tedial exhibiting at Stand 1.C64.

More information is available at www.tedial.com.

NOVI, Mich.—Enco Systems will feature its latest advances in five key areas, including captioning, translation, AI production tools, automation and virtual production during IBC2026, set for Sept. 11-14 at the RAI Amsterdam Convention Center.

Several solutions will debut at IBC as Enco demonstrates how broadcasters can apply AI, cloud technologies and intelligent automation across the content life cycle. Highlights include the next generation of Enco’s enCaption technology, the European debut of its enSpeak real-time voice translation solution, new AI tools for television and radio and the IBC debut of the latest Qimera Virtual Production innovations.

IBC highlights will include:

• Captioning: Enco will demonstrate the enCaption suite for automated, highly accurate live captioning. The company will also demo its next-generation enCaption Sierra platform, which offers flexible on-premises and cloud deployment and improvements in language support and accuracy, as well as its Raptor cloud captioning encoder.
• Translation: Enco will show how enTranslate and enSpeak can expand standard captioning capabilities into multilingual text and audio. The enTranslate tool converts live captions into translated text in real time, while enSpeak enables natural-sounding low-latency voice translation.
• Artificial Intelligence: Enco will preview a new AI-powered video solution that automatically identifies and extracts compelling segments from long-form programming for repurposing across social and digital platforms. It will also demonstrate SPOTai, an AI tool that rapidly generates professional video advertisements for television, digital and social media.
• Automation: The company returns to IBC with its VDESK system for visual radio and video production applications and its streamlined A-LIST TV automation system.
• Virtual Production: Enco will showcase Qimera, its Unreal Engine-based real-time 3D compositing platform for immersive virtual environments, augmented reality graphics and dynamic live productions. It will complement Qimera with a whisper-quiet robotic pan/tilt head engineered to position larger camera and lens payloads precisely while supporting VISCA-over-IP control. 

“Broadcasters everywhere are being challenged to do more with less, and Enco offers intelligent, easy-to-use technologies to caption and translate content, create and repurpose programming, automate daily operations and produce compelling live television and radio broadcasts,” Enco President Ken Frommert said.

“European broadcasters operate within very specific staffing and business guidelines, so technology that simplifies workflows and enables smaller teams to accomplish more can have an immediate impact,” he added. “Our IBC showcase demonstrates how Enco is applying AI for audience accessibility and automation/production tools to help broadcasters work more efficiently and increase audience size.”

See Enco at IBC2026 Stand 7.A34. More information is available on the Enco website.

Akta Tech will demonstrate a unified AI-first video platform designed to replace the collection of tools media companies use to move, understand, repurpose and measure content during IBC 2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

Akta can ingest and distribute live signals, analyze video in real time, enrich metadata, identify and create high-value clips, and turn operational and audience data into prescriptive insights—all within one cloud platform, enabling a continuous, signal-to-audience workflow.

The company’s IBC demonstrations will include:

• Cloud signal distribution across broadcast, streaming, FAST, OTT, digital and social destinations.
• Real-time AI enrichment that identifies speech, people, objects, scenes, sentiment and events.
• Automated metadata generation and standardization to improve discovery, production and monetization.
• Intelligent clipping for sports, news and live events, with automated and human-in-the-loop workflows.
• AI-powered media analytics spanning playback quality, audience engagement, ad delivery and fill rate.

“Media companies no longer need separate tools to move, understand, enrich, repurpose and measure their content,” said Alper Turgut, chairman of Akta Tech. “Akta brings those capabilities together in one AI-first platform, helping customers create more content, reach audiences faster and improve operational and commercial performance.”

Akta is a high-end digital video platform powering video offerings for broadcasters and media companies for both live streaming and video-on-demand. Akta's turnkey technology streamlines video from ingest to playback and monetization.

See Akta Tech at IBC stand 3.DiamondLounge.

More information is available on the company’s website.

WASHINGTON—The Motion Picture Association and the Chinese tech giant ByteDance have reached Memorandum of Understanding (MOU) on a shared framework to protect intellectual property on generative AI video and image models like Seedance and Seedream, which is offered by TikTok, the TikTok USDS Joint Venture, CapCut, Dreamina and others.

ByteDance founded and is the owner of TikTok outside the U.S.; it currently owns 19.9% of the social media platform’s U.S. business. It launched Seedance 2.0 in February of 2026 and the first iterations of Seedream in 2025.

In February the MPA, which is backed by the U.S. studios and major streaming players, sent a cease and desist letter to ByteDance in connection with Seedream 5.0 Lite and Seedance 2.0.

That led to “constructive conversations” between ByteDance and the MPA, the two parties said.. More recently, the launches of Seedream 5.0 Pro and Seedance 2.5 have reflected improved IP protections.

“Today’s agreement illustrates our belief that copyright is a cornerstone of the film and television industry – and reinforces our commitment to protect creative content,” said MPA chairman and CEO Charles Rivkin. “For the past several months, we have had constructive engagement with ByteDance to implement meaningful guardrails on Seedance and Seedream, and this MOU reflects our shared determination to continue our work together to further fortify those guardrails.”

“ByteDance respects the intellectual property rights that underpin creative industries around the world, and we believe responsible innovation in AI goes hand in hand with meaningful protections for rightsholders,” said John Rogovin, general counsel, ByteDance. “We appreciate the productive engagement with the MPA and its members as we continue to strengthen safeguards across our generative AI services. This MOU establishes an important framework for continued collaboration as the technology evolves, across a variety of products and platforms.”

The MOU is an important step forward in establishing that IP can and should be protected in the generative AI space, and it formalizes meaningful progress in recent months to further strengthen safeguards on ByteDance’s platforms, the MPA said.

The MPA’s member studios are: Netflix, Paramount Pictures, Prime Video & Amazon MGM Studios, Sony Pictures, Universal Studios, The Walt Disney Studios, and Warner Bros. Discovery.

As the world of broadcast TV news moves into the AI era, station groups like Scripps are using the technology not only to help improve news coverage and viewer engagement, but also to reform and enhance how reporters and anchors spend their days—focusing on new workflows and adapting to how consumers stay informed.

That was the impetus behind Scripps Media’s announcement several weeks ago that it would adopt a “digital-first” approach to news coverage, in which it would prioritize streaming breaking news rather than waiting for scheduled daily newscasts. This approach reflects the reality of how consumers get their news—a development that is long overdue, according to Dean Littleton. Littleton recently became president of media for Scripps, combining leadership of the company’s enterprise television and broadcast operations in a newly created role.

The company plans to roll out its new process to a dozen of its smaller markets, with plans to increase deployment to all markets over time.

'We've Got to Change Our Business'
The changes were revealed at the same time the station group announced that 268 positions across the company were being eliminated. Littleton says Scripps had to make these changes, noting that core revenue across its approximately 60 local broadcast TV stations in more than 40 markets and 22 states is down 30%–50% from 20 years ago. The station group announced a nearly 5.4% drop in core revenue in its latest fiscal quarter, compared to the same quarter a year ago.

“A year ago we sat down and said, ‘We've got to change our business,’” Littleton told TV Tech. “So we took a step back and said, ‘What is our true north?’ And our true north is journalism. It's the journalism that will sustain us.

“So we looked at all of our processes and completely set about reinventing all of them with a focus on the consumer and how they consume content across broadcast, digital, streaming, and social platforms.”

Littleton says today’s news production process isn’t all that different than what it was 30 years ago and that, despite past promises to focus more on digital and streaming, broadcasters were not moving forward fast enough.

“I remember sitting in these meetings talking about strategy, and as much as we would walk out of those meetings and all say, ‘We're digital-first,’ we'd go right back to working on our 5:00, 6:00, or 10:00 newscast,” he said. “Meanwhile, the consumer left the party in large part, and that's been a mistake. I think we lost sight of the consumer.”

Littleton also wanted to move beyond the walled garden of a station news “app,” calling that approach “overly simplistic.”

He says Scripps needs to go where consumers are when it comes to news—giving them access to “journalism that's delivered on the platforms of their choosing, in formats native to that platform, and delivered on a schedule that fits the consumer's schedule.”

Littleton emphasizes that Scripps is increasing its focus on local news despite the recent layoffs by tapping into new AI processes that automate more of the production process.

“We are essentially reallocating resources from the production of newscasts to the development of journalism,” he said. “[We’re] moving resources from the process of creating the traditional newscast, and then investing in resources to create original reporting in our markets.”

Littleton says he wants to increase the number of reporters in local markets and believes Scripps will expand its local coverage rather than reduce it, as some critics have claimed.

“We'll see more reporters and MMJs, not fewer, with them having geographic beats so that they build expertise, and their stories are told with relevance and context in the communities that they serve,” he said. “And these communities that they're serving often are communities that have been 'news deserts' up until the point that we assigned a reporter.”

“At the end of this process, we'll have more MMJs and reporters overall than what we have today,” Littleton added.

Scripps has developed a new workflow to support its digital-first approach, according to Littleton.

“We've invented a whole new process for operating our newsrooms, where a story gets completed, and the story immediately goes into the live stream,” he said. “The technology that we've built constantly ‘stacks’ and ‘restacks’ the shows on the live stream, and the stories are prioritized based on tags that human beings assign to those stories, so the technology knows how to prioritize the content.

“Therefore, my experience as a consumer watching that live stream at 2:00 in the afternoon is different than it would have been at 1:00, because as new content has moved into the stream, the technology ‘restacked’ it based on priorities that human beings gave it,” Littleton added.

New Role: 'Executive Reporter'
Along with more automated production processes, Littleton also says the management of how news is handled is changing, with the creation of a new “executive reporter” role in each newsroom.

“This person leads the reporting resources inside each newsroom, they have a reporting background, and so their goal is to help improve the storytelling and the journalism, and their focus is on that all day long,” he said. “So we've had to rethink how management works in our newsrooms to support what is an entirely new workflow and process inside our buildings.”

To put the power of AI behind its new news workflow, Scripps developed its own news production platform called "Stacker," according to Christina Hartman, vice president of emerging technology operations at Scripps.

Producers working with Stacker create templates based on their focus—whether it be news, weather, business, or sports—and connects those subjects to local community concerns so news reports better reflect local issues.

“Stacker is the platform we built that is responsive to a template that a producer builds, as a reflection of the content strategy of the newsroom, whether it’s heavy on weather, leading with community connection stories, etc.,” she said. “The producer sets the template, and then Stacker as a platform will read what stories we have available and meet the criteria for slotting in the platform, and then it produces a draft or suggested rundown based on that daypart's template.

“It allows the producer to intuitively move stories around if they don't like the suggested order, or if they want to change some of the timing content, they could do that really easily through the platform,” Hartman added.

Better Use of Time
Hartman reiterated Littleton’s assessment of the need to use AI to free up a reporter’s time during the day.

“The amount of time that our reporters have been able to spend being in the field versus doing the shooting, editing, and versioning for social media and the web—the time spent actually with news gathering has shrunk, and the day has gotten longer,” she said. “We remind people that more and more of your day is going to things that aren't why you got into this business.”

Given the level of automation now involved in news production, Hartman stressed that everything aired is still approved by humans.

“Nothing is published or goes to air without human review and affirmative approval, and everything that we publish or take to air is originally reported, substantively written, and reviewed and approved by a human journalist,” she said. “What we have brought AI in to assist with are really the production components: the versioning, the metadata tagging, the sort of rough-cut edit, and the layout of the rundown in a suggested capacity. So from a guardrails point of view, it's structurally built into the process.”

As Scripp’s chief advocate for AI development within the company, Hartman shares her initial skepticism about AI, noting that when ChatGPT was launched nearly three years ago, her first thought was, ‘how do I keep this as far away from our newsroom as possible?’

“It's why I proposed forming AI governance,” she said. “So we started from sort of a ‘protective condition.’” she said. “What I found though is that if I was writing the guardrail and the rules around use of AI, I better know what I'm doing and be using it so that I can understand what the traps and the and the pitfalls were.”

Hartman responded to criticisms that Scripps is using AI as an easy way out to justify downsizing its news staffs.

“If this were purely a financial exercise, there are many other models that that I will tell you candidly would have been so much easier to pursue,” she said. “We could have dripped down to five-minute newscasts. We could have killed reporting and reporting roles, and maintained the facade of a newscast where you have talent that isn't even local, putting on the appearance of a local broadcast. But none of those alternatives would be true to Scripps’ value and Scripps’ promise to its communities.”

With a digital-first approach, a news story is not a finished product, but rather an evolving element that Littleton believes can help make viewers part of the narrative.

“What we are now seeing our newsrooms do with this process where you create a story and you immediately upload it and it goes into the stream, that happens throughout the day so viewers get to go along with the reporter as they develop a story,” he said. “[As the reporter] walks out of the newsroom, they record video that explains what their story is for the day, and as that story gets updated, those videos are created, and they go into the stream also. So the person watching at home gets to go along with the reporter as the story develops throughout the day.”

The fact that news workflow is being built around AI is not new, but technical changes are just one factor in the decision to the shift, according to Hartman, who characterized the new direction as “as much cultural as it is technological.”

PARIS and NEW YORK—Moments Labs will showcase Studio, an intuitive editing workspace with AI-based capabilities that helps production companies turn moments from their existing video catalogs into branded, publish-ready content, during IBC 2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

Studio closes the gap between discovering valuable moments in a video catalog and activating them at scale.

“Audiences increasingly find and follow their favorite shows on social and video-sharing platforms, yet the content that could engage them and build loyalty often remains buried in an IP owner’s archive,” said Phil Petitpont, Moments Lab CEO and co-founder. “Getting short-form content out quickly and consistently has traditionally required very manual work across multiple tools. Now, teams can find the right clips to edit, brand and publish, all without leaving Moments Lab.”

Studio brings clips into the editing workflow from Moments Lab using the company’s Discovery Agent. Teams can assemble a story, pick a one-click hook and use AI to support the rest of the process, including automatic vertical reframing, captioning, branded text and overlays. Finished clips can be published directly to social platforms, without the need for export or re-upload.

At IBC2026, Moments Lab will also unveil the latest improvements to MXT, the multimodal AI that underpins the platform’s editorial intelligence. It now understands scenes, actions and show-specific context in greater depth, while processing videos up to 50% faster.

Together, Studio and the latest AI improvements help social and digital teams move from finding the right moment, to creating and publishing branded social video in one connected workflow.

See Moments Lab at IBC 2026 stand 1.D12.

More information is available on the company’s website.

PARIS—Dalet has announced it will be participating in the IBC2026 Accelerator Media Innovation Program as part of a project exploring the future of AI in sports production.

During the Program, it will be collaborating with Astro Malaysia, Middle East Broadcasting Company (MBC), Tata Consultancy Services (TCS), AWS (Amazon Web Services), ITV, Google Cloud and other industry leaders on AI for Live Sports and Beyond: Rewiring Live Media via Agentic AI Orchestration and "meCast."

Located in Hall 14 at Stand 14.D25 in the Future Tech Zone, the project explores how agentic AI can automate live media workflows, enabling real-time content adaptation, personalization and new monetization opportunities for sports and other live productions.

As part of the demonstration, Dalet will showcase how its media-aware AI platform, Dalia, together with Dalet Flex and Dalet InStream, orchestrates live workflows from ingest through AI-powered analysis, compliance review and publishing, helping sports organizations accelerate production while maintaining editorial oversight and governance.

For sports organizations, broadcasters, leagues and rights holders, the ability to rapidly create, personalize and distribute live content is fundamental to enhanced audience engagement and revenue generation.

Dalet already supports sports customers with media workflows that accelerate highlight creation, content discovery, repurposing and multi-platform publishing, enabling teams and rights holders to maximize the value of every live event.

The IBC2026 Accelerator project showcases these capabilities by exploring how AI can intelligently orchestrate complex live production workflows while keeping humans in control.

The Accelerator demonstration complements Dalet's broader showcase at IBC2026, where the company will present innovations across Dalet Flex, Dalet Pyramid and Dalia, demonstrating how trusted, media-aware AI is transforming media operations from production through distribution.

Visitors to the Dalet stand will see how the latest innovations help media organizations modernize production and content supply chains, accelerate news workflows, improve content discovery, and streamline sports production through AI-assisted highlight creation, intelligent media management and automated publishing.

Attendees will also learn how Dalet's open, media-aware AI architecture enables organizations to deploy trusted AI while maintaining governance, operational control and flexibility through support for multiple large language models.

Dalet will be exhibiting at IBC2026 in Hall 7, Stand A43. For more information, visit https://www.dalet.com/events/ibc/.

TORONTO—Nolia Studios, a new AI-native film studio has launched under the leadership of award-winning filmmaker Bob Gaudette and veteran TV producer and creative director Kirk Hipkiss.

The launch follows the international success of Gaudette’s short film “A Face Only a Mother Could Love,” which has emerged as one of the most recognized AI films of the year. The eight-minute film earned the $50,000 Grand Prix at the 2026 Runway AI Festival, Best Picture at the OMNI International Film Festival, Best AI Film at the New York International Film Awards and the David Harold Blackwell Award for AI & Emerging Technology Film at The Eudaimonia Project Film Festival. It was also named a finalist at the 2026 Reply AI Film Festival in Venice.

Building on that momentum, Nolia Studios has been established as a dedicated, slate-driven production company focused on original intellectual property across film, television and emerging formats. The company formalizes a creative partnership that has been developing over the past year between Gaudette and Hipkiss through AI-driven film and broadcast projects.

Nolia Studios is currently developing a slate of original projects spanning short-form, feature and serialized content. Among these is “The Little Cloud Thief,” an animated property in development for both feature and episodic adaptation.

The launch of Nolia Studios is supported by Hipkiss’ broader production infrastructure through Radical Point Media, an established animation, visual effects, motion graphics and generative AI studio. The company is currently delivering CG and AI-driven production work for major broadcasters and platforms, including projects for Netflix, Warner Bros. Discovery and A+E Global Media, while continuing to support original IP development alongside client productions.

More information is available on the studio’s website.

Science-fiction writers, who love to write about artificial intelligence taking over the world by exterminating humanity, rarely address a far more pressing and mundane issue that many engineers face every day: What happens when things begin to get too complex for humans to understand?

“The biggest complication everyone has is that we have more devices all the way down the line, from intake acquisition to live production to master control to delivery and OTT, processing media flow than we’ve ever had in our history,” said Thomas Carlisle, senior solutions architect at TAG Video Systems. “And that complexity is only going to increase.”

With some important caveats, this mind-boggling complexity, which can potentially cost companies revenue and trigger massive regulatory problems, is accelerating the use of AI by providers of test, measurement, QC, monitoring and compliance solutions.

“The big tech companies have given us this ‘big hammer’—which is AI—and have spent a lot of time looking for problems it can solve,” said Mediaproxy CEO Erik Otto, who is bullish on using AI to improve monitoring and the quality of experience for viewers, but cautions that clients want to move beyond the hype and see real applications and results. “But if AI is a big hammer, not everything is a nail. Not everything makes sense.”

Cloud-Based Complexity
While the interest in AI isn’t new—many of the main suppliers have been using it for years—the ongoing shift toward software-, IP- and cloud-based solutions is making it easier to deploy and apply AI-based technologies in test, measurement, QC, monitoring and compliance solutions.

“All the components are there for file-based,” cloud and IP workflows, Matthew Driscoll, vice president of product management at Telestream, explained. “And it is progressing fast for live, particularly for sports. That gives you this flexibility and burst capacity for things like the World Cup, but it also adds to the complexity. You have all these complex changes from SDI to IP. You’re asking these same teams to now leverage the cloud, so you have all these more permutations of things that could go wrong.”

To handle those challenges, Telestream has developed two new solutions: Pulse, a software-defined IP monitoring platform for ST 2110 signals, and Lens, a cloud-native solution that unifies all of its monitoring capabilities.

Ashish Basu, executive vice president, worldwide sales and business development at Interra Systems, agreed there is a growing demand for solutions to help monitor IP- and cloud-based infrastructures and that this shift is impacting the use of AI.

“One of the major market segments that we are seeing emerge as a very big opportunity is in sports,” he said, noting Interra is working with several major professional leagues and with major events like the World Cup, which pose many complex QC and monitoring challenges.

“We are focused on the end-to-end visibility of the content workflow and as a result are very focused on root cause analysis,” Basu said. As part of that push, Interra is developing an AI chatbot to help users identify the source of problems. “We want users to know that a problem occurred, how to fix it and how to avoid it in the future,” he added.

No ‘Winner Take All’ Scenario
Others caution that the market is likely to remain fragmented, with measurement and monitoring solutions needed for many different IP, cloud and baseband infrastructures. This fragmentation will also have an impact on AI use.

“There are big clients where the flexibility of IP is a godsend that really helps you speed up your setup,” Lynx Technik Chief Technical Officer Vincent Noyer said. “But in other cases, the gain is not so obvious. SDI is still easy to work with. I don’t see it as a winner-take-all scenario where everything is all-IP or all-cloud. We are still seeing strong demand for our products from clients who are focused on broadcast quality.”

This fragmentation is important in applying AI to tackle measurement and monitoring problems, with deployments that work best in cloud environments that can handle the massive processing and power requirements of LLMs.

“If you are in the cloud, you are not constrained by power and by computing resources; you can do many things,” Noyer added. “But in other environments you can be limited. If you can’t support a 500-watt GPU, then other approaches, simpler products and technologies, will work better.”

Another major issue with LLMs and some of the newer AI approaches is the need for massive amounts of data for accurate results.

“AI is going to matter, but you do also have to be careful,” said Triveni Digital President and CEO Mark Simpson, adding that his company has used what might be called AI for 20 years. “Effective AI requires tremendous observations and historical knowledge in terms of big data sets. The question is, do we have enough data yet in this industry? The underlying system really must provide very detailed observations for the AI to use.”

Another example of the market fragmentation and complexity that will affect how AI might be applied to test, measurement, QC, monitoring and compliance systems for broadcasters is the transition from ATSC 1.0 to 3.0 in the U.S. and other advanced broadcast standards internationally.

IP and Hybrid Complexity
ATSC 3.0 and similar standards are IP-based and can meld broadcast feeds with internet streams to provide interactivity, dynamic advertising and a host of other features. While this will let broadcasters better compete with digital media, it also creates additional complexities.

To handle those, TV Globo in Brazil recently deployed solutions from Triveni designed to handle the unique features of that country’s new TV 3.0 standard. “This has made it much easier for them to detect problems,” and will help them take advantage of the new standard’s features, according to Simpson.

All this fragmentation and complexity raises a longstanding issue—the need
to simplify monitoring, measurement and QC processes.

“A lot of operations, engineering and leaders come to us and say we need one, one piece of glass,” TAG’s Carlisle stressed. “They don’t want to go to four or five different products. I want a unified, simple platform.”

In addition to simplifying the monitoring process, Carlisle and others believe AI can proactively analyze networks to solve issues before they might occur, greatly improving the viewing experience, which in turn would help retain audiences and subscribers.

Mediaproxy’s Otto noted that his company’s products, used by the major U.S. broadcast networks and hundreds of TV stations, allow customers to monitor hundreds of outputs, including encrypted ATSC 3.0 feeds and YouTube offerings that have been difficult to track.

“We can join together hundreds of thousands of sources,” he said. “And we are getting to the point where we can employ AI to do more interesting things to improve the quality of experience, which can have a direct impact on revenue, costs and audience. That is where we are directing a lot of our attention with AI.”

A person is scrolling through social media and stops on a video of a real human being making a plausible claim. Nothing about the clip looks obviously fake. The lighting feels normal. The voice sounds right. It may even be genuine footage.

How does that person decide whether to believe it?

That is the real question now: not whether media can be manipulated—we already know it can. Not whether synthetic media will continue to improve; it will. The harder question is how belief gets formed when authentic-looking media is abundant and context is fragile amid constant technological innovation.

Since my column “Content Provenance: Audience Trust Is at Stake” in the December issue of TV Tech was published, confidence in the telecom sector continues to fall. According to a 2025 Gallup poll, a record-low 28% of Americans expressed a “great deal” or “fair amount” of trust in mass media (see chart below). The conversation around the importance of the verifiability of content authenticity, i.e. content provenance, has become pivotal.

This article does not argue that provenance can solve the trust problem; that challenge depends on a multitude of factors, including effective marketing, brand and customer strategy, as well as human emotion, environment and temperament. Rather, we argue that provenance is now a necessary infrastructure for making digital content more transparent and defensible. The need for authenticity is not coming soon; it is already here.

Over the past two years, meaningful progress has been made on provenance technology. The Coalition for Content Provenance and Authenticity (C2PA) is an industry standard for attaching provenance metadata to digital content so people can verify where media came from and whether it has been edited. It has become the center of gravity for content credentials.

As synthetic media becomes easier to create, and AI-generated images and videos become more commonplace, regulators are beginning to insist on machine-readable transparency. Article 50 of the European Union AI Act becomes enforceable on Aug. 2, and California’s AI transparency rules are moving in a similar direction. For media companies, provenance is more than a best practice. It is a capability they will need to operationalize.

Why Trust Cannot Be Engineered
People trust institutions. They trust familiar people. They trust sources their communities already recognize. They trust what aligns with their prior experiences more readily than what disrupts them. And while technology may modify some of these patterns, it does not replace them.

This is why propaganda still works in a world where authenticity tools are improving. A message does not need to be fake to be manipulative. It only needs to be framed effectively, repeated often enough and delivered by a messenger the audience is predisposed to trust. Conversely, a piece of information can be authentic in a narrow technical sense and still mislead. A real clip can be selectively edited. A true quote can be stripped of context. A genuine image can imply something false.

This is the core limitation that provenance cannot solve.

C2PA is designed to certify the history of content, not its inherent truthfulness. It can help establish where a file came from and whether its recorded history has been altered. It does not determine whether the message is honest, persuasive, manipulative or fair. It is a transparency layer, not a truth engine.

The news industry has been dealing with versions of this problem for years. User-generated content has long been highly valuable and highly risky. It feels authentic because it is often captured by real people in real moments. But that makes it easy to over-trust. “Shot by a real person” is not the same thing as “reliably framed,” “fully contextualized” or “immune from manipulation.” In some ways, that is precisely why provenance matters. In other ways, it is precisely why provenance is not a silver bullet.

AI Makes the Problem More Visible
AI has not so much created the trust problem as made it harder to ignore. For broadcasters, the more immediate issue is not whether AI can generate convincing content. It is how to preserve confidence in the provenance of content as it moves through increasingly complex production and distribution chains.

The healthiest relationship with provenance is pragmatic: use it to strengthen verification, not to outsource judgment.

That becomes especially important in broadcasting because the chain is only as strong as its weakest link. Content may be signed at capture, but downstream platforms and intermediaries can still strip or distort metadata during re-encoding or distribution. In practice, that means provenance can disappear before the audience ever sees it. For broadcasters, that means provenance technologies cannot be treated as a point solution. It must be operationalized across capture, editing, publishing, metadata management and governance.

C2PA is not a trust substitute. It is an enterprise capability that supports trust at scale.

The future is unlikely to produce a universal trust layer that makes belief automatic. That is asking too much of any technology. What it can do is provide better information.

For media executives, this creates a practical agenda.

First, treat provenance as infrastructure. Second, start where the risk is highest, especially around UGC and breaking news workflows. Third, build governance around what you capture, expose and retain. And fourth, prepare for provenance to become part of compliance architecture, not just editorial experimentation.

That is where the real opportunity lies. Not in claiming technology can manufacture trust, but in building systems that make trust easier to earn and easier to defend.

Technology can tell us where information came from. It cannot tell us what to believe. Even if it could tell us what to believe, would we?

It’s impossible not to notice that generative AI is the hot topic right now, and its explosive popularity means newsrooms of all types—especially those that broadcast images to the world—face authenticity challenges that go far beyond traditional issues of whether a certain clip is fake or doctored.

Newsrooms must now grapple with whether they can show how and where a particular clip came from, the process by which it reached the edit and whether the version that viewers see still matches the material it claims to represent.

In our increasingly low-trust media landscape, AI blows everything up at a time when many major broadcasters can scarcely afford more reputational harm and attacks, especially around the basics of authenticity and provenance.

A Delicate Balance
On both sides of the trust equation, the balance is becoming more delicate. Currently, AI tools can make scarily convincing images, video and audio in moments, a far cry from the stodgy, copyright-infringing outputs of even 12 months ago.

C2PA, or the Coalition for Content Provenance and Authenticity, is one attempt to shift that work earlier in the broadcast chain. The group, formed in 2021 and designed to protect content by building an open, industry-wide cryptographic standard to map the origin and history of digital media, features most of the heavy hitters in tech, including Google, Microsoft, Meta, OpenAI, Adobe and Amazon.

Rather than asking journalists, platforms or audiences to spot every possible fake after the fact, it creates a way to attach tamper-evident provenance information to media as it is captured, edited, distributed, and displayed.

To many broadcasters, the appeal of the C2PA solution should be obvious. In theory, a piece of video could carry a technical record of its journey from camera to newsroom, through the edit, out to publication, and eventually into a player or TV app.

In practice, thorny questions remain over whether that chain can survive the real broadcast workflow—from ingest to playout, streaming and social distribution—and the messy hand-offs that are a natural part of this process.

What C2PA Can Prove
At a basic level, C2PA is best understood as a way to preserve the history of a piece of media, rather than as a tool that decides if a story is true.

C2PA lets a validator check that a signed manifest belongs to a particular asset, whether the asset still matches that cryptographic binding and what the signer has asserted about its creation or editing history. It does not independently prove that every assertion is accurate, that nothing happened before the first signature or that the signer should be trusted.

In other words, C2PA is nowhere close to a panacea, and the most useful way to think about it is as a chain of custody.

As a Sinclair spokesperson put it: “Authentication and provenance answer questions such as: Where did this content come from? Who created it? Has it been altered? They do not independently determine whether every claim within the content is accurate or true.

“Editorial standards, fact-checking, reporting, and journalistic judgment remain essential,” the spokesperson said. “Provenance is a valuable tool that supports trust, but it does not replace the work of journalism.”

Bruce MacCormack, chair of the International Press Telecommunication Council (IPTC) Media Provenance Committee and co-founder of Project Origin, a consortium of global news organizations formed to combat digital disinformation by establishing a secure, end-to-end process to prove the integrity and origin of digital news and journalistic content, summed it up nicely: At both ends of the broadcast chain—ingest and output—knowing the provenance of media files is vital.

At ingest, signed content from a trusted camera, newsroom, agency or partner can help verification teams triage material more quickly; unsigned footage does not automatically become suspicious, but it may need extra manual checks.

“The issue is the increased fact-checking burden created by the wide availability of tools to generate or manipulate media,” MacCormack said. “C2PA can provide an ‘express lane’ for media that is signed by trusted parties.”

At output, the same infrastructure can help a broadcaster defend its own material once it leaves the newsroom, especially when clips are reposted, embedded or shared on third-party platforms.

A valid signature is therefore only part of the calculation. Newsrooms also need to establish who signed the credential—a camera, application, agency or publisher—and whether that identity is trusted in the relevant context. A credential from an unknown signer can be cryptographically intact without carrying much editorial weight.

Signing at the Source
The cleanest and earliest place to start that chain is in the camera.

If a newsroom can verify a video or image file only after it has been edited, compressed or pulled from a platform, it is already fighting a losing battle. Camera-side authentication aims to move the first trust signal as close as possible to the point of capture.

For Sony, that means building provenance into the camera (or media capture device) itself.

According to Martin Lindsay, head of networked solutions at Sony Electronics, Sony signs the captured file inside the camera, binding the media to the device so that downstream systems can validate its origin and integrity.

C2PA-compliant credentials then provide a standard way to record how and when media was created. In Sony’s case, capture time can help establish when the material was recorded, while 3D depth data—where supported—can add evidence the image came from a physical camera capture, rather than a generated or artificially constructed scene.

Camera-side signing is only the first link, though. Lindsay said provenance is strongest when it remains attached “from camera capture all the way through editing, storage, and distribution workflows.”

The challenge is that real-life broadcast media rarely travels in a straight line. “Provenance can be lost when content is exported, transcoded, compressed, screen-recorded or moved between systems that do not yet support these standards,” Lindsay said. “That is why industry-wide adoption and workflow integration are critical. Authentication needs to become part of the normal production pipeline rather than an additional step.”

Sony is also trying to move verification out of standalone tools. Lindsay said Camera Verify and its Image Verification Pre-Check SDK can be integrated into newsroom or media-management systems, allowing routine checks to run without requiring journalists to process every file manually.

Because news footage is rarely broadcast exactly as captured, the edit must become part of its provenance record.

Adobe Premiere and Media Encoder can attach Content Credentials at export, including verified identity and linked accounts. Premiere can also scan supported imported assets for existing credentials, while sequences containing supported Adobe AI-generated material receive credentials automatically in compatible export formats.

Adobe: Through the Edit
A clip may be trimmed, captioned, color-corrected, combined with other footage or prepared for several platforms before it reaches an audience—all of which are completely standard processes. Those changes do not make the media suspicious by default, but they do need to be carried out honestly if provenance is going to remain useful.

Each handoff still must understand what it is receiving, and cross-compatibility remains a potential stumbling block.

Adobe itself acknowledges that it cannot guarantee every publishing destination will support Content Credentials, which neatly captures the wider broadcast problem: one system can preserve provenance, but the chain only works if the next system does. too.

Any handoffs become more complicated inside a professional broadcast environment.

Much of the public conversation around C2PA has focused on capture, publishing and consumer-facing formats, but broadcasters work across a much messier chain of file formats, live signals, production tools, playout systems and distribution routes.

For Thomas Bause Mason, director of standards development at the Society of Motion Picture and Television Engineers, that means provenance has to be considered across the standards that already hold broadcast workflows together.

“SMPTE does not want to invent its own CPA specification but rather make sure that SMPTE standards are ready to support the CPA solution the market will choose,” he says. “That may be C2PA.”

In practice, the question is whether the systems used for professional editing, media exchange, IP production, legacy video links, and compression can carry a provenance record without losing it along the way.

The Material eXchange Format (MXF) is becoming more widely used for professional editing and distribution, but Bause Mason said no single format or handoff can solve the problem on its own. Broadcast workflows are made of many connected systems, and each one needs to know how to preserve the trust chain.

Bause Mason’s broader argument is that professional media infrastructure is not yet prepared to support content provenance end to end. Existing standards and systems need ways to carry manifests, identifiers or other durable links to provenance data before C2PA can move from controlled demonstrations into routine broadcast operations.

Editing, VFX, transcoding and format conversion can strip or break provenance, but they should also be able to add their own assertions to the manifest so the credential reflects what actually happened to the media.

Multiple Layers
Provenance also must represent several layers of origin. From a broadcaster’s perspective, the producer may be the source, but the audience may need to know which channel, platform or publisher endorsed the final version.

As one might imagine, this creates some difficult broadcast-specific questions.

Bause Mason helpfully frames some of them: Should authentication work frame by frame or shot by shot? How should provenance remain synchronized with the content during live production? What happens when contribution feeds from OB trucks are cut into a program, sent to consumer outlets and then passed to affiliates for further edits?

As he elegantly put it, “Only if the whole ecosystem is trusted glass to glass can the consumer be sure to receive content they as well can trust.”

When The Chain Breaks
A broken provenance chain cannot become a verdict in itself. If C2PA is going to work in a newsroom, it has to support editorial verification rather than replace it.

For broadcasters that handle user-generated video, archive footage, agency or wire material, social clips and content from third parties—in other words, many of them—this point is especially salient.

Some of the content may never have had credentials attached in the first place; some may have passed through systems that stripped or corrupted metadata before it reached the newsroom; and so on.

A newsroom may encounter media that was never signed, media whose manifest has been stripped, a credential that fails validation or a perfectly valid credential from an unfamiliar source—four different cases requiring different editorial responses.

As Marcos Armstrong, senior specialist, content provenance and integrity at CBC/Radio-Canada put it: “When dealing with user-generated content, archival assets, or third-party wire material that lacks a cryptographic signature, broadcasters cannot rely on data alone.”

At CBC/Radio-Canada, that means provenance sits alongside more traditional verification work. Armstrong points to visual vetting, geolocation, satellite imagery, public records and other open-source intelligence techniques used to check visual material when credentials are absent, incomplete or broken.

Armstrong said CBC/Radio-Canada is also exploring watermarking and perceptual fingerprinting as ways to reconnect broken credentials to their original manifests.

CBC/Radio-Canada has also tested more complete provenance workflows, including an in-house signing tool, the EBU’s C2PA-enabled video player, a C2PA-enabled Sony PXW-Z300 and Adobe Premiere in demonstrations of how a “glass-to-glass” workflow might operate.

Provenance can also fail for ordinary reasons. A genuine piece of footage may lose its credentials during compression or resizing, while a misleading video can still carry a clean technical chain.

For broadcasters, C2PA adds another signal to the verification process, helping newsrooms see where confidence is stronger, where the chain has gaps and where human judgment still needs to take the lead.

Reaching the Viewer
Even if provenance survives the production chain, it must still reach the audience in a form people can understand. Sinclair sees that display layer as central to adoption.

“For content authentication to become a routine part of broadcast news and production workflows, the standards work needs to move beyond carrying provenance in technical metadata and ensure that the end viewer can actually see and understand it,” a spokesperson for the station group said.

Authenticated enterprise identity needs to be shown consistently in media players, televisions, and software players, the broadcaster said. Without that, a piece of content may carry valid provenance data, but the viewer may never see that it came from Sinclair or another trusted source.

There is a UX problem here as well as a standards problem.

Armstrong said CBC/Radio-Canada has been exploring how Content Credentials should appear on its digital platforms without overwhelming users or making routine edits look suspicious, a delicate balance.

CBC’s proposed model uses progressive disclosure: an unobtrusive icon or banner first, followed by an expandable plain-English summary for users who want more detail. The interface would distinguish routine technical changes, such as resizing or colour-profile normalisation, from edits that can affect context, such as a heavy crop, and from transformative changes involving generative AI.

For provenance to become routine, it has to disappear into the workflow. C2PA only becomes useful to broadcasters at scale if it is built into cameras, editing tools, asset-management systems, CMS platforms, distribution chains and players.

From Trial to Broadcast Infrastructure
MacCormack argued that media provenance should become a feature rather than a standalone product—something built into capture, edit, distribution and display systems rather than handled by specialist signing or validation tools outside the normal workflow.

Armstrong makes a similar point from the broadcaster side, saying that the goal is to move away from manual resigning and embed provenance natively into common tools.

For Bause Mason, the standards challenge reaches across the professional media ecosystem, with each transformation point preserving the credential or identifier while adding its own record of what changed.

Broadcasters are not there yet. Workflows are mixed-vendor, format-heavy and full of hand-offs that were never designed to preserve cryptographic manifests. Social platforms, browsers, operating systems, televisions and software players also need to recognize and display provenance consistently before audiences can benefit from it.

C2PA will not replace newsroom judgment or settle every dispute over whether a piece of media is trustworthy. Its value is more practical: If the chain can hold, broadcasters gain a way to show where media came from, how it moved through production and why viewers can have confidence in the version they are watching.

NEW YORK—The IAB Tech Lab has released AAMP 2.3, a notable update to the Agentic Advertising Management Protocols that are designed to help organizations deploy AI agents within existing advertising infrastructure.

More specifically, AAMP 2.3 expands the open framework for Agentic Advertising with enterprise-ready deployment, integrated privacy diligence, stronger pricing integrity, broader platform support, and the finalization of key industry standards.

“The industry has already shown what's possible with AI agents,“ IAB Tech Lab CEO Anthony Katsur said. “Now, the focus is making them reliable in the environments where advertising actually happens,. Organizations need infrastructure they can trust. They need AI agents that work across systems, respect consumer privacy regulations, and make decisions with repeatable accuracy. AAMP 2.3 gives the industry that foundation, moving agentic advertising into everyday business.…

The release comes as agentic advertising is making rapid progress, with AI agents demonstrating how they can automate planning, buying, selling and optimization.

AAMP 2.3 is designed to accelerate the next phase of that development by providing the industry with a common framework that enables those capabilities to operate within the technology environments companies already use. It lets organizations deploy model-agnostic agentic stacks that connect to major inventory sources while remaining interoperable across the broader advertising ecosystem.

The release also introduces new capabilities making production deployments more practical. Organizations can deploy AAMP through Amazon Bedrock AgentCore; expand buying across additional platforms, including Metal integrate Google Ad Manager reporting; and build on new open-source contributions from HyperMindz and Mixpeek. Together, these enhancements give buyers, sellers, publishers and technology providers greater flexibility to integrate AI agents into existing workflows using the systems they already have in place, the IAB Tech Lab said.

As AI agents begin handling more transactional decisions, confidence in the information being used becomes increasingly important, IAB Tech Lab said.

To address that issue, AAMP 2.3 integrates the IAB Diligence Platform and SafeGuard Privacy directly into the Buyer Agent, helping organizations embed privacy diligence into agent workflows. Enhanced pricing guardrails also improve the accuracy and integrity of transaction data, IAB Tech Lab said, creating greater confidence for buyers and sellers as agentic advertising moves into production.

Beyond that, the IAB Tech Labs reported that Agentic Audiences are now ready for fully programmatic and agentic transactions, extending standardized agentic workflows into audience activation.

New features and developments in AAMP 2.3 include:

• Enterprise-ready deployment through Amazon Bedrock and Databricks.
• Deterministic negotiation guardrails with proven end-to-end real negotiation.
• Server-side trust verification on every price-moving path.
• Support for Meta buying.
• Google Ad Manager reporting integration.
• IAB Diligence Platform and SafeGuard Privacy approval gate integrated into the Buyer Agent.
• Enhanced pricing guardrails that improve pricing accuracy across Buyer and Seller Agents.
• Any path that commits spend is deterministic and provable with human approvals outside of value-based thresholds.
• Inventory availability is always based on real, not derived, numbers.
• Fully conforming to the OpenDirect open standard and validated against the spec.
• Deals Sync API MCP Server contributed by HyperMindz.
• Content Taxonomy Parser contributed by Mixpeek, adding semantic IAB Content Taxonomy v3 classification, contextual inventory discovery and enrichment and brand-safety scoring.
• Agentic Audiences v1.0 ready for transactions.

To learn more, visit the IAB Tech Lab website.

To address the problem that artificial intelligence can generate videos so realistic that distinguishing them from authentic footage is becoming increasingly difficult, a computer science team led by researchers at UC Riverside has developed a tool that moves beyond simply identifying whether a video is fake. It also determines which AI system created it.

The new framework identifies visual patterns within fake video frames that were unintentionally introduced by AI video generators, providing a forensic path to identifying the systems that created the videos.

“The patterns are like fingerprints that the generative model leaves behind, and our goal here was to find out if the signatures are distinct amongst different generators. It turns out that, yes, there are distinct fingerprints there,” said UCR doctoral student Rohit Kundu, who led the research under the guidance of Professor Amit Roy-Chowdhury in collaboration with researchers at YouTube and Google DeepMind.

The new framework is called SAGA — short for Source Attribution of Generative AI Videos. It represents one of the first large-scale efforts to trace AI-generated videos back to their origins.

The innovation comes as generative AI systems are rapidly improving and synthetic videos are increasingly being used in entertainment, advertising, education, social media, and politics. At the same time, concerns are growing about their misuse in misinformation campaigns, fraud, and other deceptive activities.

“Knowing that a video is fake is often not enough,” the researchers wrote. “The critical need has shifted from whether it’s fake to what is its source?”

The ability to identify the source of AI-generated content could help digital forensic investigators track misinformation campaigns, assist regulators in enforcing transparency requirements, and aid technology companies in understanding how synthetic media spreads online.

Unlike still images, videos contain motion and temporal information with visual elements changing from one frame to the next over time. Different AI video generators produce subtle patterns in those changes, creating distinctive artifacts.

To detect those artifacts, the team analyzed both spatial details within individual frames and temporal relationships across entire video sequences. Rather than examining a single frame, the system studies how visual information evolves from moment to moment, the researchers explained.

A key innovation is a technique called Temporal Attention Signatures, or T-Sigs. These signatures visualize the unique patterns associated with different video generators. By averaging patterns across many videos produced by the same AI system, SAGA generates a characteristic profile that helps distinguish one generator from another.

The researchers tested SAGA using public datasets containing videos generated by 19 different AI video generators. These included both text-to-video systems, which create videos from written prompts, and image-to-video systems, which animate still images.

The system can determine whether a video is real or synthetic, identify whether it was created from text or images, distinguish among different versions of underlying AI models, and even identify the development team behind a model.

Click here for more information.

The AI creative platform OpenArt and kids content startup, NovaLand, have announced an agreement that will see NovaLand’s animation studio use the suite of OpenArt’s creative AI tools.

As part of the partnership, NovaLand will use OpenArt's newly launched Director platform to create high-quality animation focused on social-emotional learning for preschool and early grade audiences, both neurodivergent and neurotypical.

Some early examples of their content are focused on a major problem for parents and families: helping these younger kids transition from screentime.

“At NovaLand, we believe every child deserves stories that don't just entertain them, but also help them grow. OpenArt is helping us achieve our goal of creating content that helps children navigate big emotions and gives families practical support during some of their most challenging everyday moments,” explained Helena Shi, co-founder and CEO of NovaLand, which is a member of the Harvard Innovation Labs and a Novab Social Impact Fellow. “It is helping us build an entirely new production workflow that allows a small team to create cinematic-quality content faster than ever before on a fraction of the budget traditional animation requires. For an impact-driven startup like ours, OpenArt enables us to contribute something truly meaningful to the communities we serve”

“We are passionate about mental health and wellbeing, especially when it comes to little ones,” added Ermin Monzon, head of content and education at OpenArt, said. “We are gratified to partner with NovaLand, who is not only utilizing our tool creatively, but also making a difference for so many families.”

NovaLand’s production team is led by award-winning director William Lau (Emmy Award-winning series The Last Kids on Earth, Barbie, Batwheels, My Little Pony) and CTO Cheng Zhao (former Tech Lead at Meta). The first episodes from NovaLand can be viewed on YouTube here.

NovaLand aims to build the next generation of children's media, using original stories designed to help children develop emotional skills through characters they love. In its content it is paying particular attention to one of the most challenging moments for families, the transition off screens.

To address that issue, NovaLand combines storytelling with child-development expertise and evidence-backed design to create content for both neurodivergent and neurotypical families. The company is currently collaborating with clinics, neurodivergent organizations, and educational partners to bring its stories to families.

OpenArt Director, OpenArt debuted last month, enables longer-form AI storytelling to become conversational rather than prompt-based.

Through the platform’s “vibe directing” interface, creators simply describe the feeling, story, characters, set environments, and pacing, and then OpenArt Director renders it to life, in whatever genre the user wants, from live-action realism to numerous animation styles.

After generation, users continue directing through conversation, editing scene by scene to make targeted changes without the video being regenerated from scratch.

This is a notable change from other AI video tools that would recreate the entire piece when edits were made, frequently changing key details like character appearance or settings that a user didn’t want changed.

Learn more at thenovaland.com and https://openart.ai/home.

Olympic Broadcasting Services (OBS) has revealed some of its plans for the next Summer Olympics, taking place in Los Angeles in 2028.

At a meeting of rights holders last week, OBS said it intends to provide approximately 3,800 to 4,000 hours of competition and Ceremonies coverage.

The host broadcaster added it is expanding its use of first-person-view (FPV) drones, real-time 360° and stroboscopic replays, point-of-view (POV) cameras, microphones on officials and coaches, dynamic graphics, back-of-house access and enhanced digital content at LA28.

The broadcast ecosystem will be designed around virtualization, cloud-based workflows and AI-ready infrastructure, said OBS, to deliver increased flexibility, resilience and operational efficiency across broadcast operations.

Plans include expanded cloud services, AI-assisted production workflows, enhanced digital content delivery and new approaches to content distribution.

Work on the IBC fit-out will begin in early 2027, added OBS.

This article originally appeared on TV Tech sister brand TVBEurope.

BRUSSELS—Mediagenix will showcase its vision for the Real-Time Media Enterprise at IBC2026 IBC 2026, Sept. 11-14, at the RAI Amsterdam Convention Center.

The Mediagenix platform connects content strategy, title management, scheduling and personalization through Semantic Intelligence and trusted agentic workflows, enabling decision intelligence across the media lifecycle. The platform is built for digital transformation, offering faster, better-informed editorial decisions, more engaging audience experiences and continuous operational optimization. At IBC2026, the Mediagenix Real-Time Media Enterprise showcase will feature:

• Title Management from Content Repository to Content Intelligence Platform, providing a single source of truth for content-driven media companies powering content metadata workflows, enrichment, discovery, and monetization.
• Schedule Optimization, leveraging smart automation for linear, FAST, and VOD channels, capable of building weeks of programming in minutes.
• Personalization and curation to create experiences that keep audiences engaged. Combines editorial engagement with intelligent recommendations powered to help audiences discover more content, increase engagement, and improve retention.
• Trusted agentic AI workflows in which agentic workflows are safely operationalized with new AI capabilities across channel operations—from title management and rights to personalization and curation.

At the gathering, Mediagenix will unveil new innovative workflows and capabilities, including content-aware scheduling, performance-based scheduling, intelligent curation, trusted agentic media operations and advanced personalization.

"Media organizations don't need more isolated automation. They need connected decision intelligence," said Emmanuel Müller, chief product officer at Mediagenix. "By continuously connecting editorial decisions with audience insights, media organizations can move beyond disconnected workflows toward intelligent, continuously optimized operations that adapt in real time to changing business priorities, audience behavior and market conditions. That's the foundation of the Real-Time Media Enterprise."

See Mediagenix at IBC 2026 stand 1B.57.

More information is available on the company’s website.

‍Waymark has announced that Cox Media Group (CMG) is deploying Waymark's AI-powered video platform at stations in nine markets.

By combining multiple generative AI models, Waymark has developed an end-to-end video creation platform that allows anyone to produce ready-to-air commercials suitable for TV, streaming, and digital platforms.

That makes it easier for local advertisers and businesses who might not have the tools to create traditional ads, which in turn can help increase local ad sales.

The deal adds Cox Media Group to Waymark’s growing roster of national broadcast and media partners, which includes Comcast, Spectrum Reach, FOX TV Stations, Sinclair Broadcast Group, E.W. Scripps, Gray Media, Paramount, and Nine Entertainment (Australia).

“What we’re seeing with Cox Media Group represents how broadcasters help clients grow and unlock revenue,” said Alex Persky-Stern, CEO of Waymark. “When a platform can help reps open doors, close deals, and deliver finished creative, the impact compounds. CMG’s teams have proven that video drives campaign revenue throughout the sales cycle.”

As part of the agreement, CMG stations are tailoring Waymark to its own workflow and market conditions to shorten sales cycles and increase the number of local businesses running television campaigns.

“We’re always looking for ways to help our clients meet and exceed their business goals,” said Darren Moore, CMG’s chief sales officer – TV. “Waymark helps us have better initial conversations, reduce the time between those conversations and the advertising launch, and create targeted and compelling content. We’re better – and our clients share in that – because of Waymark.”

STAMFORD, Conn.—As part of a broader push to capitalize on the potential of AI in its ad sales and other operations, Charter’s AI and data commercialization business unit Spectrum Intelligence Ventures has announced its first product, a household intelligence platform called Latis.

Built on information spanning digital engagement, TV viewership, and connected device activity across approximately 30 million U.S. households and 500 million connected devices, Spectrum said that Latis is designed to transform real-world activity into intelligence that will help companies and organizations better understand consumer intent, context, emerging trends and shifting demand at national scale.

“The transition from data to intelligence is one of the most important shifts happening across technology and business today,” said John Lee, head of Intelligence Ventures for Spectrum. “Latis is designed to help power this next generation of AI-driven systems by transforming large-scale household signals into continuously evolving real-world intelligence that organizations can use to improve decisioning, automation, personalization and business outcomes.”

Spectrum reported that Latis continuously models household activities across digital, video and device signals, transforming household-level data into pseudonymized mathematical and privacy protected representations of household activity patterns.

This will help advertisers, companies and organizations better understand changing consumer intent, priorities, responsiveness and likely future actions across such industries as retail, automotive, financial services, travel, media, telecommunications and consumer goods.

For example, traditionally, a clear sign of a consumer’s interest in travel typically only becomes available only after a consumer has taken a clear transaction-oriented step, Spectrum explained.

Latis is designed to help identify emerging travel-related interests earlier in the consumer journey by transforming household-level activity patterns—such as destination research, engagement with travel-related content, and comparison of vacation options—into a pseudonymized and privacy protected sense of intent, interest, affinities and trends.

Spectrum also reported that Latis is designed to support a broad range of enterprise and AI-native use cases, including:

• Consumer insights and segmentation
• Media targeting, optimization and measurement
• Data clean room collaboration and enhancement
• Personalization and decisioning
• Model training
• Agentic AI acceleration

Spectrum said that Latus was designed with a privacy-forward architecture and governed access framework.

It enables organizations to obtain intelligence through secure collaboration environments, controlled integrations and governed infrastructure models designed to support enterprise privacy, security and governance requirements. Partners may use the intelligence outputs for permitted business purposes, such as advertising, marketing, measurement, research, customer engagement, analytics, personalization, and improving AI-driven tools and services, but the underlying household-level data stays within Latis’ controlled environment and is privacy protected.

Spectrum Intelligence Ventures is currently selecting a limited group of partners for beta participation. Beta programs include collaboration with Spectrum Reach to provide select partners early access to Latis intelligence combined with Spectrum Reach and wider media inventory to improve targeting and business outcomes. Broader availability is planned for the second half of 2026.

Warner Bros. Discovery has announced that it is working with its preferred cloud provider Amazon Web Services (AWS) to develop next-generation advertising experiences built with AWS agentic AI.

As part of the effort, WBD is expanding its advertising technology stack on AWS and deploying an agentic AI-driven approach to how premium inventory across its U.S. linear and digital channels is planned, activated, optimized, and monetized.

By rebuilding its longstanding traditional internal workflows from the ground up with automated, data-driven processes on a single platform, WBD reported that it is reimagining its infrastructure for advertisers in ways that unify "the buying experience across previously siloed business units and enable automated campaign optimization."

"We're embarking on the next frontier of advertising where convergence brings linear and digital together on a single platform – each retaining its own essence, yet with the fluidity to plan, package, and optimize across both — all measurable and optimizable at cloud scale with agentic, AI-native decisioning," said Dr. Nage Sethu, senior vice president of technology - converged advertising and linear systems, Warner Bros. Discovery. "Building with AWS has been critical to streamlining the buyer’s experience across linear and digital, powering critical layers of our data, forecasting, and next-generation agentic advertising stack."

In 2026, WBD began rolling out a new generation of capabilities, including agentic automation for direct response and commercial workflows, advanced audience forecasting, and enhanced measurement and attribution.

Building on those rollouts, WBD said it will introduce unified media planning in Q3, followed by a phased rollout of composable order management, pricing, and stewardship in Q4.

"AWS is proud to deepen our relationship with Warner Bros. Discovery at such a transformative moment in media and advertising," said Samira Panah Bakhtiar, general manager, media, entertainment, games & sports, Amazon Web Services. "By combining WBD's iconic content portfolio and rich audience signals with AWS's cloud and agentic AI capabilities, we're enabling a new era of intelligent, automated advertising that delivers better outcomes for brands and viewers alike."

More specifically, WBD’s new platform features autonomous AI agents for intelligent planning, dynamic forecasting, real-time optimization, and closed-loop measurement. These agents continuously self-optimize, learning from outcomes to drive better results for buyers and sellers alike with every campaign. The system enables flexible targeting approaches, allowing buyers to focus on specific brands or audience segments across linear and digital, with WBD providing optimal inventory allocation recommendations.

The platform streamlines the ad buying process for WBD inventory so that advertisers can more effectively allocate budgets across multiple platforms and brands. Additionally, advertisers can more easily leverage new ad formats, including interactive ads, while viewers receive more customized ad content.

Underpinning WBD's new advertising technology implementation is a composable data and interoperability layer that gives WBD's AI agents the real-time context they need to act, integrate seamlessly across the ecosystem, and deliver buyer transparency. Key AWS services powering the platform include:

Amazon Bedrock hosts the various foundation models employed in WBD’s closed instance

Amazon SageMaker provides the tools for training custom machine learning models for WBD’s exclusive use and in compliance with WBD data protection, segmentation and security controls

Amazon Simple Storage Service (Amazon S3) stores data in the Apache Iceberg format for the underlying data lake.

In addition, Amazon Elastic Container Service (Amazon ECS) powers application hosting and Amazon Quick provides a personalized, proactive AI assistant that enables Ad Sales teams to interact with data through natural language, uncover actionable insights, receive proactive recommendations, and make faster, data-driven decisions.

CHESEAUX-SUR-LAUSANNE, Switzerland, and PHOENIX, Ariz.—Nagravision has launched Nagra Venturi, a new intelligence-led streaming security offering that helps service providers and rights holders detect threats, combat piracy, and safeguard revenue.

Nagra Venturi brings Nagravision’s streaming security capabilities together under a single intelligence-led model, shifting anti-piracy from fragmented, reactive tools to coordinated, data-driven offering.

“With AI in the hands of pirates, the market has reached an inflection point,” said Morten Solbakken, executive vice president and COO at Nagravision. “As piracy becomes faster, more automated, and increasingly intelligent, the industry needs a new approach. Nagra Venturi is built to fight AI with AI, giving operators and rights holders the ability to move faster and with greater precision, providing the clarity to see the full picture, the focus to target the threats that matter, and the impact to protect revenue and the audience experience.”

The new offering is designed to address the fact that today’s pirate operations are automated and increasingly AI-assisted, scaling illegal services globally within minutes and targeting live sports during the narrow window when content is most valuable. That has put operators and rights holders in the difficult position of managing growing volumes of data and alerts, without clarity on which actions will make the biggest difference.

Nagra Venturi answers that challenge by transforming security data into prioritized, decisive action. It aggregates and analyzes data from across the streaming ecosystem to create a real-time view of piracy activity, identifies the highest-value threats, and coordinates targeted intervention where it will have the greatest business impact. Rather than reacting to every signal, teams can focus on the threats that matter most to their business.

Through its managed service option, Nagra Venturi includes Nexus, the Nagra Anti-Piracy Center, where analysts coordinate monitoring, intelligence, investigation, and enforcement against a global view of piracy activity. Because Nagravision tracks the wider ecosystem rather than a single network, it can uncover pirate infrastructure and leaked content that individual operators may never see, then coordinate disruption across multiple points at once to maximize impact. Individual solutions, including forensic watermarking and multi-DRM, remain available as standalone solutions within the Nagra Venturi portfolio.

“For more than 30 years, Nagravision has protected the world’s most valuable content,” adds Solbakken. “Built on that heritage—and informed by decades of front-line anti-piracy intelligence—Nagra Venturi moves content protection from a reactive, tool-based model to a proactive, intelligence-led one designed for today’s piracy landscape. Nagravision is proud to be leading the charge to help its customers demonstrate the impact of their anti-piracy strategy—one that proves its value in commercial terms, not just technical ones.”

To learn more about Nagra Venturi, visit nagra.vision.

LONDON—Cascade Studio has announced the Open Beta launch of Cascade, an AI-native production platform that aims to democratize storytelling by bringing Hollywood-grade storytelling infrastructure to creators of any size.

"Too many great stories never make it to screen – and we built Cascade to change that," said Simon Windsor, CEO of Cascade Studio. "We didn't set out to build another AI generation tool. That's not what the industry needs. What we've created is the all-in-one production environment we wished we'd had throughout our careers.”

Cascade was co-founded by Simon Windsor, co-founder and former co-CEO of Dimension Studio; Junaid Baig, former lead of DNEG rendering and pipeline whose credits include “Avengers: Endgame”, “Tenet”, “Fantastic Beasts”, and “No Time To Die”; and Darren Hopkins, technology entrepreneur, former CFO of Dimension Studio, and CEO of AI-focused investment firm Mollyroe PLC. The company has also appointed games industry pioneer Dominic Wheatley, co-founder and former CEO of Eidos, as Chairman.

Described by its founders as "the Unreal Engine of storytelling", the Cascade platform is powered by a proprietary agentic AI framework that acts as a creative co-pilot throughout production, helping creators develop ideas, build assets, manage projects and orchestrate workflows through natural interaction, while keeping every creative decision firmly in human hands.

Cascade Studios stressed that the platform has been built for scaling productions and IP. Its unique asset-based system enables creators to maintain character consistency, visual coherence and IP integrity across entire projects – from shot to shot, series to series, and across expanding story worlds and sequels. Cascade brings AI-generated content, existing creative assets and live-action production together seamlessly in a single platform.

The result is a scalable production environment where solo creators or agile teams can build everything from teasers, trailers and advertising campaigns to episodic series, animation, films and music videos without juggling multiple tools, subscriptions or disconnected workflows.

"The creativity has always been there, but what the industry has been missing is a platform that connects everything – one that supercharges high-grade production while respecting the creative process and helping storytellers bring ambitious ideas to life,” Windsor added. “That's what Cascade is. The production platform modern storytelling has been waiting for. We're redefining who can make films, how fast they can make them, and at what quality."

The Open Beta of Cascade is available now: Sign up at www.cascadestudio.ai.

State associations representing broadcasters in all 50 states as well as groups in District of Columbia and the Commonwealth of Puerto Rico have sent a letter to Congressional leaders supporting the "Nurture Originals, Foster Art, and Keep Entertainment Safe" or NO FAKES Act of 2026.

Amid the ongoing, rapid expansion of generative artificial intelligence (“AI”), the NO FAKES Act would create important guardrails for the use of digital replicas without unduly restricting the potential benefits that generative AI can contribute to the broadcast and creative industries now and in the future, the groups said.

The letter was sent to John Thune Senate Majority Leader, Chuck Schumer Senate Minority Leader, Mike Johnson House Speaker, and Hakeem Jeffries House Minority Leader.

“This bipartisan legislation would protect the voice and visual likeness of all individuals, including the most trusted broadcast news anchors and local on-air personalities, from unauthorized computer-generated recreations made by generative AI,” the letter said. “It would also provide important exclusions for use of digital replicas in certain bona fide news reporting and broadcasting, as well as commentary, criticism, scholarship satire, parody, and other First Amendment speech.”

Nothing that “nonconsensual voice and image clones can sever that trust, ruin reputations and careers, and distort our public disclosure,” the letter argued that the “NO FAKES Act would create a federal remedy, while also preserving certain state laws, for individuals to fight back against abusive and manipulative deepfakes that threaten to disrupt that trust. And while combatting misinformation, disinformation, misappropriation of content, and deepfakes is a multifaced problem, the NO FAKES Act is a step in the right direction.”

DOWNINGTOWN, Pa.—PTZOptics and LayerJot will demonstrate how prompt-based AI, robotic camera control, and high-performance computing can work together to identify, follow, and respond to objects and events in real time at InfoComm 2026, June 13-19 in Las Vegas.

The demonstrations, which run on Intel Core Ultra Series 3 processors, combine LayerJot’s purpose-built AI software application with PTZOptics’ SimplTrack3 cameras, featuring advanced auto-tracking capabilities. The demos will show how natural-language prompting can guide the system to identify and/or track objects in the room, then use PTZOptics camera control to respond automatically.

The collaboration is designed to show integrators, educators, broadcasters, and pro AV teams a practical path for building on-site AI video workflows, according to the companies. By pairing PTZOptics camera robotics with Intel Core Ultra Series 3 -powered compute and LayerJot’s agentic AI application layer, both exhibitors will demonstrate how Visual Reasoning can move from concept to deployable workflow without requiring large teams, custom hardware stacks, or cloud-only processing.

"AV and enterprise buyers today are asking the same question: how do we deploy AI that actually works in our environment, without building a data center or waiting on the cloud?” said Dr. Ben Cope, Principal Engineer, Intel. “Intel Core Ultra Series 3 processors were purpose-built with that reality in mind, delivering the on-device AI compute performance that makes local visual reasoning practical at scale. Collaborating with PTZOptics and LayerJot lets buyers take that compute capability and turn it directly into deployable, prompt-driven camera workflows. Together, we're removing the barriers between AI potential and operational reality."

Visual Reasoning
For PTZOptics, the demo is part of its broader Visual Reasoning initiative, which focuses on turning video into actionable data by combining camera robotics, AI, and open integration. Visual Reasoning is designed to help systems describe, count, understand, and trigger actions based on what cameras see, supporting workflows across broadcast, pro AV, education, healthcare, manufacturing, houses of worship, and live events, the company said.

“Visual Reasoning becomes powerful when integrators and developers can adapt it to the needs of everyday environments,” said Matt Davis, CTO, PTZOptics. “This partnership shows what is possible when robotic cameras, local AI compute, and prompt-driven automation come together. Our goal is to inspire the pro AV community to build customized solutions faster, more affordably, and with more flexibility than ever before.”

LayerJot’s Agentic Visual Application (AVA) connects to the PTZOptics SimplTrack3 camera and uses AI prompting to identify and/or track objects in the space. The demonstration will show how developers can create custom AI workflows that connect directly to camera control, while giving users the freedom to direct camera actions using natural language.

“We’re focused on delivering advanced visual AI solutions that combine scene understanding, automation, and natural-language interaction to support critical workflows in real-world environments,” said Etay Gafni, CEO of LayerJot. “This demonstration shows how scene understanding and natural-language instructions can drive meaningful actions in live operations, enabling users to interact with complex systems in a more intuitive and efficient way.”

Example workflows include prompting the system to identify an object or person in the room, directing the camera to track that target, and showing how similar logic could be adapted for classroom automation, event production, training spaces, and other applications where small teams need consistent video coverage.

The demonstration also reflects a larger shift in the AV industry, the companies said. Cameras are no longer limited to passive capture. With Visual Reasoning, robotic cameras can become intelligent endpoints that help systems interpret what is happening, make decisions, and trigger workflows in real time. PTZOptics says it is working with a wide range of partners and integrators to combine their own domain expertise with PTZOptics cameras via open APIs – supporting teams and improving operations across multiple industries.

The live demonstration will be available at PTZOptics’ booth N8227 during InfoComm 2026. For more information, visit https://ptzoptics.com/book-a-demo/

ALBANY, N.Y.—The New York State Senate and Assembly has passed landmark legislation (A.11292/S.9934A) protecting news media from being bombarded by deceptive “stealth crawlers” from tech companies.

“By protecting broadcast news operations from unauthorized access by Big Tech, the legislation ensures the economic foundations of producing original, local news by broadcast stations throughout the Empire state,” David Donovan, president of the New York State Broadcasters Association, said in hailing the legislation, believed to be the first of its kind in the country. “It prohibits using ‘stealth crawlers’ to extract a broadcaster’s news content without permission or payment. In addition, the legislation requires AI systems to disclose when crawlers are employed to extract content from broadcasters.”

The legislation addresses a longstanding problem faced by broadcasters and news sites. Some AI systems use “stealth crawlers” to hide their identities and secretly access digital services owned by newspapers and broadcasters. This practice imposes substantial burdens on local newspapers and stations, which are often overwhelmed by millions of bot hits each day. It can also devalue the website traffic figures that news websites rely on to sell advertising.

“The New York Assembly and Senate just took a strong stand for transparency and the health of our information ecosystem,” said Danielle Coffey, president and CEO of the News/Media Alliance. “Right now, news websites are drowning in bot traffic. Bad bots are disguising their identities to overload publisher servers and access the quality content on our sites, hurting our ability to serve readers. This bill will be a simple, common sense solution to this problem. By requiring transparency and accountability for bad actors, the New York Stealth Crawler Prohibition Act gives publishers the tools they need to defend themselves and continue providing quality and critical information.”

Diane Kennedy, president of the New York News Publishers Association, also lauded the precedent-setting legislation: “News publishers invest substantial resources of labor, skill, and capital in producing original journalism. The proliferation of stealth crawlers — automated bots that access news sites without identifying themselves or disclosing their purposes — enables technology companies and other actors to access the fruits of that investment without consent or transparency. This legislation prohibits crawlers from disguising their identity when accessing covered news sources and creates a meaningful private right of action for journalism providers to enforce that obligation.”

The three associations thanked “Assemblyperson Steven Otis, Chair of the Internet Assembly Science and Technology Committee (A.11292) and Senator Mike Gianaris, Deputy Majority Leader of the NY State Senate (S.9934A) for sponsoring this important legislation. Through their extraordinary efforts citizens in New York will continue to access original local news by their favorite newspapers and broadcast stations.”

Lenovo has detailed how its deployment of a near-real-time AI-powered infrastructure platform for this year’s FIFA World Cup will enable ultralow-latency IPTV, better operational control and new fan experiences for billions of viewers.

As FIFA’s official technology partner, Lenovo has deployed servers and other solutions at the International Broadcast Center in Dallas to support the most expansive broadcast operation in FIFA World Cup history.

More than 17,000 Lenovo and Motorola devices and 200-plus engineers deployed across venues and Team Base Camp training sites will help ensure professional execution, Lenovo said.

The deployment is part of Lenovo’s larger push to expand its sports technology investments. In March, it launched a dedicated sports vertical designed to support organizations operating live, global and mission-critical environments. By integrating AI infrastructure, edge computing, devices, and services into a unified model, Lenovo said it aims to help sports organizations shift from fragmented systems to real-time, end-to-end operational control.

For this year’s World Cup, Lenovo’s technology solutions have reduced latency within IPTV infrastructure, with IPTV delays now under five seconds, enabling near-real-time access to live match action and more synchronized viewing experiences, the company said.

Lenovo ThinkSystem SR635 V3 servers and technology will also help manage massive volumes of live video data coming in from stadiums across North America and power FIFA’s IPTV live feed by ingesting, processing, and distributing all match content in close to real-time via ten channels to over 1,000 screens throughout FIFA venues.

Beyond broadcast, Lenovo’s technology will be deployed at FIFA’s Technology Command Center in Miami and the Tournament Operation Center for the duration of the World Cup. This hub, where all the technology powering the games is monitored and managed in near-real-time by experienced engineers and FIFA management, serves as the central “mission control” for the tournament.

With the help of Lenovo’s enterprise solutions, FIFA’s Technology Command Center and Tournament Operation Center will ensure organizers can quickly observe and address operational issues across a tournament footprint of 16 venues across the United States, Canada and Mexico.

“Lenovo’s AI infrastructure is redefining the FIFA World Cup experience, delivering near real-time highlights, multi-angle views and insights at unprecedented global scale,” said Ashley Gorakhpurwalla, president of infrastructure solutions at Lenovo. “Together with FIFA, we are running AI under the world’s most demanding conditions—solving latency concerns and bringing billions of fans closer to the action than ever before, setting a new standard for live sports.”

The 2026 FIFA World Cup will also showcase Lenovo’s real-world AI advances in sports production, the company said. Lenovo products will manage complex on-premise edge computing, the company said, significantly reducing latency in cases where cloud-only solutions failed to meet broadcast requirements.

More specifically, during the World Cup, technologies powered by Lenovo ThinkSystem servers, engineered for high-density, mission-critical environments requiring massive throughput, and near real-time operational performance will support:

• Near real-time monitoring of stadium and tournament wide tech systems
• Live broadcast, streaming, and IPTV delivery
• Rapid incident detection and issue resolution to minimize disruption and downtime
• Enhancing the fan experience with real-time insight and transparency

Lenovo said it is also enabling a more immersive and understandable viewing experience through AI-driven innovations.

AI-enabled 3D player avatars will provide clearer, real-time visualization of complex decisions such as offside calls, Lenovo said. Built using advanced GenAI and real-world player data, these avatars are designed to help fans better understand the game as it happens. These avatars will also be an additional value input to support FIFA match officials in their offside decision-making during matches, Lenovo said.  

To improve the in-venue experience across three countries, Lenovo said it will deploy solutions designed to enhance safety, efficiency,and engagement, including: AI-driven navigation systems to reduce congestion and improve movement across venues; AI-driven stabilized “Referee Views” to give a first-person perspective with up to 50% less motion distortion; and immersive digital and holographic experiences to create new ways for fans to engage with the game.

In addition, Lenovo will deploy the FIFA AI Pro platform, a next-generation AI-powered knowledge assistant giving tactical insights to coaches, players and analysts. Built using Lenovo’s AI Factory, the platform will be provided to all 48 competing teams.

RESTON, Va.—As media companies continue to grapple with the impact that AI is having on digital audiences and traffic, Comscore has released its first AI Intelligence Report for 2026 with new data highlighting a number of emerging trends.

The report shows the scale of breakout growth from Anthropic’s Claude platform. Based on Comscore’s panel data, the Q1 report revealed that Claude recorded 1,858% growth in desktop conversations between March 2026 and October 2025. While ChatGPT continues to lead the AI assistant category up 55% year over year, the report shows consumers are using a wider range of options.

The report also found that women are emerging as key drivers of mobile AI adoption across major generative AI tools. In March, women posted mobile index scores of 113 for ChatGPT, 123 for Copilot, and 118 for Gemini, the data showed. Men across those respective platforms had scores of 87, 77 and 82 over the same period, Comscore found. These findings further highlight the influence AI is having on a consumer’s on-the-go and day-to-day behavior.

“Comscore is providing some of the industry’s first visibility into AI-influenced intent behavior, as AI rapidly becomes the prime gateway for consumer awareness, attention, and decision-making,” said Smriti Sharma, executive vice president of analytics and managing director of Custom IQ at Comscore. “For brands and publishers, understanding how AI shapes discovery, which sources it references, and how those interactions translate into measurable business outcomes will be increasingly critical in the evolving digital landscape.”

Other key findings from the Comscore Q1 2026 AI Intelligence include:

• ChatGPT remained the category leader, reaching 244 million desktop conversations in March, up 55% year over year.
• ChatGPT also led in March with 87 million desktop visitors, compared to 44 million for Copilot and 30 million for Gemini.
• Claude reached 22 million desktop conversations in March, up 1,858% compared from October 2025, signaling growing consumer interest in alternative AI assistant experiences.
• In Q1 2026, AI assistant tools reached 36% of desktop users and 23% of mobile users.
• AI search is becoming a new discovery layer. U.S. desktop searches reached 76 billion in Q1 2026, up 10% versus Q1 2024, as AI search experiences became more integrated into traditional search behavior.
• AI is influencing high-consideration purchase journeys. In consumer credit cards, AI Overviews appeared alongside 46% of paid search ads in Q4 2025, up from 21% in Q2 2025. Over the past three quarters, approximately 25% of credit card applicants were exposed to AI Overviews, and roughly 5% applied directly from pages where AI Overviews appeared.
• Prompt behavior reveals how consumers refine decisions. In March 2026, users averaged 4.9 prompts per conversation on ChatGPT, 4.6 on Gemini and 7.1 on Copilot, showing that AI interactions are often multi-turn journeys rather than one-off queries.

The full AI Intelligence report for Q1 2026 is available for download here.

MOUNTAIN VIEW, Calif.—Utopai Studios has announced the PAI 2.0, a major upgrade of its cinematic storytelling AI system, as the company pushes forward on its plans to build an infrastructure layer for AI-native filmmaking.

PAI 2.0 arrives less than two months after PAI’s April debut and amid strong early commercial demand for Utopai Studios’ technology. The company reported that PAI has already reached $11 million in annual recurring revenue, reflecting growing demand from creators, studios, production companies, and professional teams seeking AI tools that can support higher-quality, longer-form storytelling with greater creative control, consistency, and production flexibility.

“With PAI 2.0, our goal is to help catalyze a ‘Claude Code moment’ for media generation,” said Zijian He, chief scientific officer of Utopai Studios. “Simply generating faster, isolated clips is not enough for true filmmaking. PAI 2.0 is designed to address the foundational challenges of long-form cinematic storytelling by preserving narrative context, maintaining consistency across extended sequences, and giving creators more granular control over the creative process.”

Designed as an agent-first cinematic creation platform, PAI 2.0 helps users plan, generate, and refine videos through a more personalized and flexible creative workflow.

The company said that the system is designed to understand a user’s goal and to guide them into the right creative experience based on how they want to work. PAI 2.0 combines a more powerful creative agent, a freeform Canvas-based workspace, voice input, and advanced image and video generation models to make cinematic creation more visible, controllable, and editable across story, assets, storyboard, and video generation.

PAI 2.0 introduces two creation modes built for different levels of creative control. Easy Mode guides users step by step through the full creation workflow, from story and references to storyboard, clips, and final timeline, giving creators a clearer path from idea to finished video. Pro Mode gives users access to Canvas, a connected creative workspace where they can organize, branch, edit, and refine story, assets, storyboard, and video generation in one place.

The new release also introduces advanced creation capabilities, including rapid variant generation, 2x2 keyframe generation for each 15-second video segment, and support for cinematic 4K video generation with virtually limitless extension - offering an industry-leading capability for continuous, long-form content. Within the Canvas workspace, users can directly edit story details, prompt PAI for variations, define references pre-generation, exercise precise control using both references and prompts, and seamlessly regenerate results throughout the process.

PAI 2.0 is built for prosumers and professional creative teams creating video content with clear intent and higher expectations for quality, consistency, and control. The platform is designed to support creators building short films, episodic stories, fantasy and historical videos, music videos, kids' animation, cinematic visual pieces, brand storytelling, and production-level content that requires greater continuity across characters, locations, scenes, and final outputs.

As part of the launch, Utopai Studios is introducing updated subscription-based pricing for PAI 2.0, including monthly and annual plans, direct credit top-ups, and customized enterprise plans. Existing PAI users will have access to a phased migration plan, with PAI 1.0 remaining available until July 2 to allow users to complete ongoing projects. Remaining PAI 1.0 credits as of June 2 will be matched 1:1 and added to each user’s PAI 2.0 account.

As new advances in efficiency and vendor interoperability fuel momentum behind broadcasters’ reliance on production in the hybrid private/public cloud domain, cost challenges posed by AI resource scarcities are moving to the top of industry suppliers’ to-do lists.

The latest, frequently AI-enhanced solutions that came to light at April’s NAB Show have made the hybrid cloud model more attractive than ever amid waning enthusiasm for exclusive reliance on either public cloud or proprietary hardware resources.

In the case of Grass Valley’s customers, for example, “whether broadcasters choose to host aspects to their production workflows on premises or in the cloud can be decided on the basis of architectural complexity and what makes sense for the tasks at hand,” Chief Product Officer Adam Marshall said. “That’s what they’re looking for.”

Like just about everywhere else, AI is playing an ever-greater role at Grass Valley. Marshall said the company uses AI “to accelerate our ability to deliver what our clients need” and to provide a “third-party front door” that allows customers to add their own AI application layers.

The need to secure cloud operations, including vulnerability analysis of the type delivered by Anthropic’s new Mythos AI model, has added to AI processing requirements. Grass Valley will make the technology available if and when Anthropic lifts current restrictions on its release, Marshall said.

Inference Costs
A late 2025 report from Deloitte Insights underscored the immensity of the AI usage challenges facing all industries. That report found enterprises everywhere “are discovering their existing infrastructure strategies aren’t designed for AI’s demands,” Deloitte said.

The mismatch results from “inference,” or the incessant processing required as AI models generate new information based on changing conditions. “While inference costs have plummeted, dropping 280-fold over the last two years, explosive growth in overall AI spending… has dramatically outpaced cost reduction,” Deloitte said.

“Dependence on high-performance compute in the public cloud can get expensive,” Jonathan Gryckiewicz, business development director for cloud solutions at Ross Video, said.

Businesses are adjusting to the new realities “incredibly fast,” he said, but for now, “it seems largely the case that to get benefits from AI, we need to connect the media environment to the [public] cloud” where processing is “gobbling up GPU capacity and prices are getting higher and higher.”

Ross Video’s latest cloud- and AI-related contributions include support for its XPression real-time browser-based graphics creation and monitoring tools via a scalable on-demand service called XPression.cloud, which can be used instead of local XPression hardware. XPression.cloud uses AI to identify appropriate XPression templates and expedite graphics-related asset retrieval, creativity and generation.

XPression.cloud offers customers “a more sophisticated way to manage graphics on their own” without “shipping boxes around,” Gryckiewicz said.

Matrox Video is also riding the market surge toward hybrid cloud-optimized converged production solutions. For the past two years, Matrox has promoted its ORIGIN media-aware content transfer fabric as a way to control high-performance multiprotocol transport and scalability without dedicated hardware. ORIGIN was again a big focus for Matrox at this year’s NAB Show, but with a different emphasis this time, Product Manager Daniel Robinson said.

“We hadn’t seen very many use cases emerging until now,” Robinson said, noting uptake this year involves the likes of industry suppliers Amagi, EVS and TSL, as well as the Canadian multiservice giant Rogers Communications. The difference lies with Matrox’s success in using AI to make it easier for customers to put ORIGIN to work in their products and services, Robinson said.

“We’re not running AI on the software but using AI tools to build things quickly,” he explained, which means executing on projects that might have taken days or longer in a matter of hours. “It’s about shortcutting discovery of information. If you didn’t do that, you’d have AI searching through thousands and thousands of lines of documentation with outcomes that may or may not be the right ones.”

AI Supply Chain
Such uses of AI on the build side of supplier innovation are fueling acceleration in product development for cloud- and hardware-based solutions alike. While these applications don’t incur the ongoing inference processing costs associated with AI applications used in live production workflows, they are vulnerable to hardware capacity and cost trends, noted Stephan Stadler, chief product officer at Appear.

“Being a hardware manufacturer, the AI supply chain is top of mind,” Stadler said, citing Appear’s use of AI not only in “how we plan and build things” but in discovering new opportunities and creating sales messaging. “The big challenge is memory chips for everyone who builds hardware products in this industry,” he added.

Appear has moved into the hybrid cloud production space with the recent introduction of the VX Media (VXM) Gateway, which uses open-source interfaces to enable interoperability with other vendor solutions in commodity cloud support for the dispersed REMI production versatility enabled by its hardware-based X Production portfolio.

“VXM doesn’t replace XP,” Stadler noted. “It’s just an extension of that.”

The company’s release of VXM—even as it registered another big hardware win, with Fox Sports using its X platform to deploy its REMI production workflow for the 2026 FIFA World Cup—reflects the growing pull of the virtualized hybrid cloud opportunity across the traditional broadcast-production hardware supply chain.

Another case in point is the expanded support for cloud production introduced by Sony Electronics’ Nevion unit. Nevion has integrated MOXELA, a new cloud-native software platform, with its cloud-based VideoIPath media orchestration layer to transport, process and monitor production workflows encompassing output from cameras and other equipment supplied by Sony and by other vendors.

“The big problem we’re solving with MOXELA is producers’ need for flexibility to adapt to different workflows by running various processing functions for different streams in parallel across on-prem and public cloud clusters,” Nevion Head of Product and Solutions Jan Helgesen said.

The Impact of MXL
MOXELA aligns with common frameworks like SMPTE ST 2110 and NDI, as well as the emerging industry guidelines shaped by the European Broadcast Union’s open-source Digital Media Facility (DMF) initiative, including the Media eXchange Layer (MXL) specifying containerized microservice support for real-time, in-memory exchanges of uncompressed audio, video and metadata across multiple vendor software applications. This is a big step toward enabling cloud-based live sports and other productions, but there’s much more to come, Helgesen said.

“We’re currently on a cloud production journey from Tiers 3 and 2 to Tier 1,” he explained, noting that getting to Tier 1 still “requires some technical development that’s not completely there yet.” It’s a staged road map that will also bring AI into play to automate the complex troubleshooting, planning and setups that big cloud productions will require, he added.

Implementations of MXL in vendor product lines—facilitated by the Linux Foundation’s release of the first MXL Software Development Kit (SDK)—are fast becoming the norm. This is because the shift toward hybrid cloud production has made just-in-time activations of COTS resources with cross-vendor interoperability essential to cost containment.

Sony, along with a new commitment to the protocol by Ross Video, adds to a list of MLX supporters that includes Appear, AWS, Grass Valley, Imagine Communications, Intel, Lawo, Matrox, NVIDIA, Riedel Communications and Telos Alliance.

Pay As You Go
For Lawo, the growing consensus around the hybrid cloud approach to broadcast production is right in stride with its longstanding promotion of the Lawo HOME management and orchestration platform. HOME runs on commodity servers in private or public clouds to enable discovery, authentication, security management and monitoring of all production-connected devices from a single user interface.

To address cost uncertainties as the hybrid cloud production model takes hold, Lawo has introduced Flex, a payment system built on credits that makes it easier for customers to adjust to changing dynamics in private vs. public cloud resource usage.

“You can buy and use Flex credits like chips in a casino to spend on any HOME app,” Chris Scheck, head of marketing content for Lawo, said. The hybrid cloud model “is where we’re heading,” he added, but uncertainties mandate offering customers as much flexibility as possible in choosing how to spend on cloud resources.

For example, while customers would rather maximize use of private resources, “right now, servers have almost tripled in price because of chip shortages, and it can take six months to get them,” Scheck said. At the same time, as Grass Valley’s Marshall observed, in the public cloud space “we’ve seen processing costs rising at record rates, up 40% during the first part of the year and now up 80%.”

Factor in the complications added by the AI squeeze and it’s clear the hybrid cloud model might not be the cost-saving slam dunk it once appeared to be. But in a live-production environment that needs to accommodate fragmented workflows delivered through ST 2100, NDI, SDI and other pipelines while enabling browser support for executing editing tasks across dispersed locations, the advantages of cloud-based accessibility, agility and efficiency are too compelling to be ignored.

This puts a premium on cloud cost-containment know-how. As Marshall noted, at a moment of growing confusion among producers, figuring out what will work for each customer has much to do with knowing which questions to ask.

The only constant is change. For the past several years, much of the conversation around artificial intelligence has centered on generative systems—tools that can produce text, images, audio and video. These have captured the public imagination and, understandably, generated both excitement and concern across the industry. But a potentially more consequential shift is now beginning to take shape: the rise of agentic AI.

Before going further, let’s be clear about what this article is and is not. This is a thought experiment, not a forecast. The future described here may be a decade away, may look entirely different in practice or may not arrive at all. The value of the exercise is not prediction, but rather the perspective it can give about what is possible. As the saying goes: All models are wrong, but some are helpful.

With that framing in place, here is the central argument: the journalist of the future won’t directly write the story — they’ll train the agent that does. If that idea sounds like science fiction, read on. The pieces are already in motion.

What Makes Agents Different
Generative AI systems respond to stimuli (prompts). Agentic systems “act” and seek to accomplish broader objectives. Unlike a generative model, which responds to prompts, an agentic system can pursue goals, make multistep decisions and interact with other systems or agents on behalf of a person, organization or system. It is not so much a tool as it is a delegate.

Understanding this matters because it tells us where the real disruption lies. Generative AI changed what machines could produce. The evolution of agentic AI will change what machines can be trusted to do. The newsroom could be one of the clearest places we will see agentic technologies playing out in our industry.

The argument that follows rests on a specific assumption: that news will increasingly be assembled dynamically for each user, rather than consumed as static content. To be clear—not fabricated—assembled intelligently from trusted sources in response to what a user needs, when they need it and in the context of that moment. Whether that assumption proves correct or even desired is genuinely uncertain, but if true, it will change many roles.

There is already directional evidence of the possibility. AI-powered tools are generating summarized, citation-linked news experiences today. Users of search interfaces receive synthesized answers that draw from multiple publishers without directing them to any one source.

This is not entirely new—search engines have surfaced news snippets for years. What is changing is the sophistication of the synthesis and the degree to which audiences are satisfied without clicking through. The path toward dynamically assembled news is already being walked.

How News Is Encountered Now
If news is increasingly assembled by agents rather than read as discrete articles, then the journalist’s job cannot remain centered on writing those articles. And the current trends in how audiences consume news means that this future is more plausible.

Not everyone goes looking for news. Younger audiences, in particular, tend to encounter it while doing something else—scrolling through short-form video, moving through algorithmic feeds. News finds them; they do not seek it out. Push notifications and platform algorithms have become the primary editorial voice for a significant and growing share of the audience.

This matters because it means editorial control is already shifting—not to AI agents, yet—but to technology platforms and their recommendation systems. An agentic future would be an extension of a trend already underway. The cultural conditions for this shift are already forming.

One further implication would be that as news becomes more individually assembled, shared cultural experience erodes further. Monoculture—the common reference points that once came from everyone watching the same broadcast—have already shrunk dramatically. Agentic personalization would accelerate that fragmentation. The thesis we discuss carries consequences that are arguably negative.

What Changes in the Newsroom
If the journalist of the future trains the agent rather than writes the story, what does that look like?

The fundamental activities of journalism—interviewing sources, attending events, obtaining documents, verifying facts—are not going away. These are what give journalism its credibility, and they cannot be automated. What changes is that rather than assembling every story manually, a reporter feeds their gathered knowledge into a system trained on their expertise, voice and editorial standards.

Over time, that system—a digital extension of the reporter—responds to queries, synthesizes developments and surfaces context using what it has learned. The human journalist remains the source of credibility. The agent becomes the mechanism that scales it.

The implications ripple outward. The editor’s role shifts from revising individual pieces to governing the parameters within which agent systems operate. The news organization becomes less a publisher of discrete articles and more an operator of a trusted information system—one whose quality is determined not by today’s headline but by the integrity of everything that trained it.

This is not a reduction in the need for human expertise. It is a redirection of how expertise is applied. And it places an enormous premium on the thing that has always mattered most in journalism: the quality and credibility of the reporter behind the byline.

If agents are assembling and delivering information to users without directing them to the original source, the traditional advertising and subscription models face obvious strain. How publishers get paid in this world does not yet have an obvious answer.

Emerging ideas around usage-based or token-based compensation for content access are being discussed, but none has yet gained traction. These are not technical problems. The economic and governance problem may take longer to solve than the underlying technology takes to mature.

Why This Model Matters Now
The reason to think through this scenario today is not to prepare for an imminent transformation. It is to avoid being surprised by a gradual one. Technology shifts in media never arrive all at once—the transition from tape to file-based workflows took the better part of two decades—but the organizations that engaged early tended to fare better than those that waited for certainty.

The journalist of the future may not directly write the story; they’ll train the agent that does. If that future arrives, what will matter most is not whether AI is telling the news. It is who shaped the agent doing the telling, what they fed it and what standards they held it to. These are human decisions. They always will be. And the time to start making them thoughtfully is now.