Artificial intelligence I in media has moved well beyond a collection of tools. Capabilities such as metadata tagging, QC automation, transcript generation, and recommendation engines now shape decisions across the content chain. As these systems grow more connected, AI increasingly acts as the operating layer that routes content, applies policy, and manages routine tasks.

The industry is shifting from narrow automation toward agentic systems that can understand context, pursue goals, and execute multi-step processes within clear editorial and policy boundaries. Routine content can flow automatically while sensitive material is held for human review. The result is faster, more consistent operations — paired with new expectations for transparency and trust.

How End-to-End AI Workflows Work Today — and Why They’re Now Essential
Broadcasters tend to begin one of two ways: solving individual pain points or linking teams and systems into continuous workflows. Both paths have reshaped operations.

Individual High‑ROI Tasks
For many organizations, the first gains come from targeted use cases. Smarter metadata tagging improves archive access, personalized recommendations and artwork help keep viewers engaged, churn prediction sharpens retention efforts, and load forecasting prepares systems for major events without guesswork. Automated compliance checks flag inappropriate content, while QC tools catch frame-level issues.

Crucially, AI now reaches upstream into pre-production, where agentic systems orchestrate automated script breakdowns, generate storyboards, and optimize complex production schedules before a single frame is shot.

Shift to Workflow Orchestration
As organizations connect individual AI tasks, the operating layer starts to take shape. Instead of siloed workflows, agentic systems act as the connective tissue between the newsroom, production, advertising, and operations. For example, AI now orchestrates contextual advertising by analyzing video frame-by-frame for hyper-targeted dynamic ad insertions (DAI). Content moves according to policy, not manual handoffs, and the system improves as teams refine rules and review outputs.

These orchestration models can even show “self‑healing” behavior, with agents monitoring traffic patterns, detecting early signs of congestion, and adjusting routes automatically. Human teams retain oversight for judgment calls and editorial nuance, guided by clear governance on when to intervene.

Some broadcasters have already taken orchestration further. Sky Italia uses an AI-driven delivery platform that routes video data dynamically across its network, ensuring buffer-free 4K streams for millions of viewers. By anticipating demand spikes, the system reduces egress and storage costs while improving viewer experience.

As distribution expands across regions, platforms, and accessibility requirements, manual versioning and monitoring cannot scale. Three domains show how AI has become foundational:

1. Real-time Monitoring and Operational Intelligence
   Operations teams oversee thousands of feeds at once, and AI helps surface issues that would otherwise go unnoticed — mis-triggered graphics, muted audio, compliance violations, subtle sync drift. In one recent global sports broadcast, AI detected graphic rendering errors on mobile devices early, prompting an automatic switch to a backup encoder before viewers notice anything. AI‑driven forecasting also helps teams scale resources for major events, reducing the need to over‑provision and improving resilience during peak demand.
   
2. Localization remains one of the most labor‑intensive parts of media operations. AI accelerates translation, subtitling, compliance edits, metadata generation, and platform specific packaging. It also preserves sync and ensures consistent output across formats and languages. With accessibility expectations rising, AI systems can automatically identify non-speech audio cues like "[rain patters]" or "[door creaks]" and support high‑volume production of Subtitles for the Deaf and Hard-of-Hearing (SDH).
   
   Dubbing has also improved significantly. Newer models preserve tone, pacing, and emotional nuance rather than merely converting dialogue. Netflix has seen completion rates for global titles increase after adopting emotionally aligned dubbing, demonstrating how performance‑aware tools can improve viewer engagement. Humans still guide cultural context and oversee less‑common languages, but AI now handles much of the repetitive work that slows production.
   
3. Sports Logic, Highlight Generation, and Resource Optimization
   Sports broadcasting shows how quickly AI is evolving. Instead of generic highlight packages, AI now identifies sport‑specific moments — a goal, three-pointer, or slapshot — and assembles clips for social distribution instantly. This logic also powers generative personalization, as seen when NBC Universal used AI orchestration to create millions of highly personalized daily Olympic recaps. These same systems forecast audience surges for major matches and adjust cloud and network resources accordingly – helping maintain stream quality while cutting infrastructure costs.

Securing AI-Native Operations: Risks and the Trust Stack
As AI becomes central to production, the risks grow too. Synthetic anchors, fabricated promos, tampered clips, and impersonations of public figures can erode credibility. Another challenge comes from contaminated or synthetic content entering production pipelines, where it becomes harder to detect and more costly to fix.

A stronger approach builds trust into each asset. A practical trust stack includes:

• Digital watermarking — durable, invisible identifiers that survive editing, compression, and screen capture.
• Provenance frameworks — cryptographically signed manifests capturing an asset’s origin and transformations. Broadcasters such as France Télévisions and ARD have begun daily use of C2PA protocols to safeguard VOD authenticity.
• Authentication — hardware-backed proof at capture that confirms material comes from a trusted source, as seen in Sony’s latest C2PA-enabled camera systems.

For this to work, trust signals must be added at ingest and persist through localization, editing, transcodes, and multi‑partner distribution. Challenges remain, including metadata stripping, uneven adoption, social-media black holes, and key-management burdens. However, without these layers, AI-native operations carry significant brand and legal risk.

A Pragmatic 12-Month Plan
Adopting AI effectively starts with a focus on viewer impact and measurable outcomes. Choose one or two high-value problems — manual bottlenecks, missed QC anomalies, dubbing throughput, churn — and link them to clear KPIs such as time-to-air reductions, versioning-throughput targets, or improvements in detection-to-resolution times.

A brief workflow audit will surface quick wins, especially where AI already functions as an informal orchestrator. From there, lightweight governance helps clarify risk ownership, documents human-override paths for agentic systems, and anticipates rising expectations for explainability. Procurement should include questions about provenance and authentication support so integrity signals travel with each asset. Finally, investing in skills helps editorial and technical teams shape and evaluate outputs rather than carry out repetitive work.

What Success Looks Like in 3–5 Years
Recent moves, like Netflix’s acquisition of Interpositive AI, prove tier-1 media companies are now embedding AI directly into their core infrastructure as an operating layer. Broadcasters that thrive won’t bolt AI onto legacy workflows; they’ll operate inside agentic, policy-driven systems that learn from outcomes, route work fluidly between humans and machines, and embed trust by default.

As these systems mature, each output improves the next, KPIs guide decisions, and consistency scales globally. The earliest deployments already show these benefits, and they will increasingly define industry expectations in the years ahead.

The media and entertainment industry stands at the brink of its most transformative evolution since the advent of digital. As generative AI, intelligent agents, and hyper-personalized content converge, every aspect of the content lifecycle, from creation to delivery, is being reshaped. Over the next five years, workflows will look markedly different, shaped by the growing influence of agentic AI systems.

Content Creation: From Human-Led to Hybrid-Generated
AI is already playing a significant role in creative pipelines, automating repetitive tasks and introducing new creative capabilities.

Automated highlight reels for sports and news are now commonplace, driven by AI models trained on visual cues and metadata. These systems generate content within seconds of live action, playing a critical role in generating social engagement and monetization opportunities. For example, Amazon Prime Video uses real-time AI tagging to compile highlights from English Premier League matches, publishing clips on social platforms within moments of key plays.

We are also seeing synthetic anchors and deepfake-like avatars being piloted in multilingual newsrooms to localize delivery at scale. Korean broadcaster MBN has deployed AI-generated news anchors to present daily bulletins, improving efficiency and reach.

AI is also expanding creative freedom by fabricating ultra-realistic B-roll footage, reducing reliance on traditional stock libraries. In advertising, tools like Runway are powering the generation of hyper-realistic videos, while platforms like Kalshi have demonstrated the viral potential of AI-driven creatives with several campaigns, including an NBA Finals ad. These technologies enable the rapid generation of full ads or trailers using brand guidelines and consumer data, allowing for targeted, creative iterations at scale.

These advances foreshadow a future where AI agents take on a more active creative role, proposing ideas, testing new formats, and adapting multiple content versions in real time to suit audience response.

Content Intelligence: Programming with Purpose
Once seen as a back-office task, programming and enhancement now serve as the nexus between content and monetization.

AI tools that generate rich metadata, including emotion tagging, facial recognition, and scene classification, dramatically improve searchability and discoverability. Translation and voice cloning tech make it possible to produce multi-language versions of content almost instantly, unlocking global distribution opportunities. Disney has been testing multilingual AI narration for regional Disney+ content, making dubbed versions available faster than traditional workflows allow.

Even programming itself is becoming AI-assisted. Peacock uses AI recommendation engines not only to suggest content but to shape scheduling and on-platform promotions. Linear and FAST channels increasingly rely on these data-driven models to optimize engagement and retention.

The result is an emerging decision-support layer where AI augments licensing, curation, and audience development decisions.

Content Production: Dynamic and Automated
Content production, particularly for live and near-live workflows, is undergoing a quiet revolution. AI can now synthesize localized promo environments, render hyper-targeted explainers, and dynamically generate contextual graphics. Voice cloning tools enable multilingual delivery from a single master script, modulating tone and emotion to suit each market.

These innovations culminate in AI-generated news or sports bulletins that can be auto-assembled from metadata, pre-tagged highlights, and templated narratives, making “live-to-tape” practically instantaneous. Looking ahead, we can expect intelligent agents to function like virtual producers, co-ordinating assets, triggering cues, and adapting layouts on the fly.

Content Storage & Delivery: Where AI Drives Measurable ROI
If AI’s creative applications generate headlines, its impact on storage and delivery is where the most immediate and measurable returns are being realized. AI models now inform caching strategies, using historical and predictive data to prefetch high-demand content to edge servers, dramatically reducing latency during peak demand. Netflix, for instance, uses machine learning to pre-position popular content on its Open Connect Appliance (OCA) CDN nodes, reducing load times and buffering.

Encoding optimization is another major frontier. Cutting-edge AI-based encoding technology is able to achieve unparalleled visual video quality while delivering a remarkable 30% or better reduction in bandwidth usage for streamed HEVC-encoded video content - or provide a significant improvement in picture quality at the same bitrate. Efficiencies are maximized by performing real-time analysis of incoming video streams, dynamically adjusting encoding settings, and optimizing codec performance to ensure optimal results.

AI-based pre-processing provides the opportunity to deliver an additional 20-40% improvement in bandwidth efficiency, depending on the source content. These same savings can be realized for file-based as well as live content, creating similar savings opportunities in storage spend. For mobile-heavy markets and latency-sensitive applications, such as sports betting or live polls, this edge-aware distribution is mission-critical.

Perhaps most revolutionary is AI-driven edge personalization. YouTube’s ad engine dynamically tailors preroll content based on viewer location, behavior, and preferences, a practice that is now expanding to overlays and stream packaging.

In an industry where delivery costs are measured down to the cent, these AI capabilities offer a clear business case for investment. By reducing operational friction and scaling personalization, AI is transforming the economics behind modern experiences.

The Overarching Layer: AI Orchestration
Applying AI in silos undoubtedly limits its full potential. True transformation comes from orchestration: intelligent systems that operate across the full pipeline, constantly assessing and acting on data to optimize end-to-end operations.

These agents evaluate tradeoffs like:

• Asset value vs. processing cost
• Audience segmentation vs. delivery overhead
• Time-to-air vs. compute resources
• Distribution priority by platform, geography, or audience segment

By monitoring asset performance across the content lifecycle, these orchestration agents can suggest where to automate, where to accelerate, and where to save, shifting AI’s role from task execution to strategic decision-making.

Such systems are being deployed not just by the largest streamers but also by agile broadcasters and telcos seeking to optimize performance without ballooning operational complexity.

Preparing for the Agentic Era
While many media organizations are still experimenting, the path from assistive AI to truly agentic systems is beginning to take shape, with intelligent agents poised to take on goal-setting, adaptation, and execution across complex workflows. To support this change, organizations must build for architectural agility, not just technical capability.

Companies must reimagine infrastructure as modular, interoperable, and AI-native. Data must be liberated from silos. Governance models must be established to ensure AI operates transparently and ethically. And above all, experimentation must be embraced through sandboxed pilots that allow teams to test, fail, and iterate without disrupting live operations.

Success in an audience-first world depends on building around AI. It’s not a feature to bolt on. Although measurable impact has often emerged first in content delivery, the more complex challenges lie in content production. Media organizations that invest thoughtfully across both domains will be better prepared to adapt and lead. The key is to act with focus and to ignore the hype.

Cloud technology is making itself at home in the broadcast sector, and not just in post-production or distribution, but increasingly for live production and playout. Flexibility, scalability and cost efficiency await the organizations that adopt these solutions, particularly when extra processing capacity is needed above the normal levels compared to building extra capacity in-house.

However, it remains unlikely that all production resources will find their way into cloud infrastructure. For example, running all broadcast processes is likely to work out more costly than owning some of the resources.

So where does this leave broadcasters? In practice, a mixture of on-premises (ground) and cloud production setups allows adopters to benefit from the best of both worlds. For example, everyday production and crisis-situations broadcasting might be handled by on-prem equipment, while cloud would handle peaks above normal usage, such as special events.

But the adoption of hybrid production raises questions as to how workflows spanning resources from on-premises to the cloud are effectively managed—otherwise production staff may be drawn away from focusing on delivering engaging content. Management of these workflows, or orchestration, is therefore essential.

Framing Orchestration for a Hybrid Future
Whether it’s live production in the cloud, outsourcing part of an on-prem production into the cloud as a hybrid workflow, or delivery of live content to a pop-up playout channel, they all require control over on-premises and cloud resources. They need to be connected with each other to ensure the safe and reliable flow of media.

Controlling and orchestrating connectivity and signal routing in the cloud itself can often be handled by established static-events automation tools. For example, predefined automation templates can be quickly deployed to create cloud infrastructure. But this approach does not extend to on-premises resource control, which is often essential for larger live productions or permanent workflows.

Orchestration systems for hybrid live production must therefore integrate both on-premises and cloud resources seamlessly. The goal should be for these workflows to be managed in the same way as a traditional master control room or production gallery, with end-to-end visibility, monitoring, and efficient management of both on-premises resources such as bandwidth, ports and equipment, and cloud instances.

Must-Have Features for Orchestration Systems
In hybrid live production setups, operators should simply be able to select a source and a receiver, whether they are based on-premises or in the cloud. The orchestration system should then be able to automatically allocate the required encoders, ARQ protection and cloud gateways from a managed pool of resources.

For example, choosing the right compression technology is often a balance between quality, bandwidth and latency, and configuration might cover codec parameters, encryption and network addressing.

All of these decisions should be made by the system in the background, ensuring that users aren’t presented with unnecessary complexity. To make the management process even more seamless for staff, an intuitive control surface, such as a familiar hardware panel or an easy-to-use software interface, would allow them to keep track of on-premises, ground-to-cloud-cloud-to-ground (GCCG) and cloud workflows.

A hybrid connection may cover a number of networks, including the on-premises production network, dedicated WAN links and unmanaged networks such as the internet. An orchestration system must monitor these network types and provide redundancy in the event of failure. It also needs to handle multi-vendor equipment, including IP switches, cameras, switchers, servers and multiviewers, to ensure end-to-end control. Transcoding between on-premises feeds and cloud receivers is also essential, alongside orchestration of the connectivity to the cloud and between cloud-native applications.

In order to make the best use of the pay-per-use model offered by a cloud solution, the orchestration system should be able to interface with public cloud providers and automate the scaling of cloud instances by spinning them up or down. If a connection is no longer needed, automatic termination of cloud processing instances can save on hosting costs. Where spinning instances up and down isn’t practical, such as for larger instances in a cloud-based video switcher, starting and stopping instances can also reduce costs, although typically not as much as the spinning option.

And just as importantly, no orchestration system should be lacking in effective security measures. While public clouds usually offer enterprise-grade security, the system must cover secure communication between on-premises devices and cloud instances. It can do this via encrypted communication protocols, role-based access control (RBAC), integration with identity and access management systems via Single Sign-On, ARQ stream encryption management and audit logging for full traceability of operations.

The Importance of an Integrated Orchestration Approach
As live production evolves, the broadcast industry is embracing hybrid models that blend the strengths of on-premises infrastructure with the flexibility of cloud. But to unlock the full value of this approach, orchestration must take center stage to provide the operational efficiency, cost control, and resilience. Systems that can intelligently and seamlessly manage resources across both environments will define the future of live production.

Looking ahead, AI could enhance the automation and efficiency of orchestration systems, automating complex workflows, reducing manual intervention, and minimizing human error. With dynamic scaling of resources also an AI-led possibility, organizations will be further empowered to make a success of hybrid live production and continue to create high-quality content for audiences.

NEP Europe is utilizing technology and teams from across Europe for this year’s Eurovision Song Contest.

The company is the official media services provider for the event for the sixth year in a row.

To meet the demands of the two semifinals and Saturday’s Grand Final, NEP is employing equipment and crew from across its European network, including Switzerland, Sweden, the Netherlands, Germany, Finland, Belgium, and the U.K.

The delivery operation includes:

• Main outside broadcast (OB) unit: UHD2;
• Backup OB unit: UHD24;
• Music mix truck: Music One with dual audio;
• Technical Operations Center: Built on NEP’s TFC broadcast orchestration platform for EBU services and signal distribution;
• 6 wireless RF cameras;
• Augmented reality services;
• 4 EVS servers;
• 27 cameras, including six wireless RF cameras;
• 40 NEP crew, with 780 working days onsite;
• Delivering over 320 monitors around the venue;
• Using over 60 kilometers of cable.

The implementation of the TFC broadcast orchestration platform means NEP can constantly monitor the entire contribution and distribution of all signals involved in Eurovision 2025 on a dashboard, the company said. That gives Eurovision 2025 a faster setup, increased flexibility and more sustainable and efficient resource deployment, NEP added.

“We’re incredibly proud to continue supporting the Eurovision Song Contest 2025 with our technical expertise and innovation,” said Lise Heidal, president of NEP Europe. “This event is not only a celebration of music and culture, but also a testament to what can be achieved when the best of European broadcast talent comes together. Every year, we push the boundaries of what’s technically possible in live production and this year is no exception.

“The deployment of our TFC platform has been a game-changer, allowing us to streamline signal management and reduce rigging and setup time dramatically. It’s this kind of software-defined flexibility that allows us to deliver complex live events with greater efficiency and reliability than ever before,” she said.

This article originally appeared on TV Tech sister brand TVBEurope.

The media industry is navigating a storm of disruption. Broadcasters are grappling with challenges stemming from relentless market shifts, mergers, acquisitions, and tighter budgets. To remain competitive amidst these pressures, efficient playout consolidation and management have transitioned from a nice-to-have to an absolute necessity.

In this context, automation emerges as the key to navigating a rapidly evolving market, driving operational excellence in an industry where efficiency, consistency, and adaptability are paramount.

The Need for Consolidation and Automation
Historically, playout and media orchestration relied heavily on manual workflows that were time-intensive and prone to error. Today, such methods are no longer sustainable. Increased channel variety, fragmented audiences, and the demand for lightning-fast delivery across platforms like OTT and FAST channels require streamlined operations. At the same time, broadcasters face immense cost pressures, forcing them to reassess their traditional, resource-heavy approaches.

Automation is fundamentally redefining this landscape. By consolidating processes and automating key functions, broadcasters can manage their operations far more efficiently. Tasks that once demanded human oversight—content ingestion, quality control, compliance checks, and distribution—can now be executed within seamless, repeatable workflows. This consolidation not only simplifies operations but also reduces redundancy, eliminates silos between departments, and provides a central, unified system to manage complex playout functions.

Simplifying Complexity
Modern media orchestration is incredibly intricate. From managing incoming content to preparing it for multiple platforms and ensuring flawless delivery, each step adds layers of complexity. Automation cuts through this chaos by standardizing and optimizing every stage of the process.

For example, automated systems can format content to suit diverse platform specifications without manual intervention. This ensures a faster turnaround and higher accuracy while reducing the operational burden. Broadcasters no longer need to spend valuable time troubleshooting inconsistencies or duplicating efforts. With automation, their teams are free to focus on innovation, storytelling, and long-term strategy rather than tedious logistics.

Driving Efficiency and Cost Savings
Efficiency lies at the heart of automation. Whether it’s dynamic scaling in a cloud-native playout system or automated quality control checks, automation ensures broadcasters only expend resources when and where they’re needed. Dynamic scaling, in particular, allows operations to flexibly adapt to fluctuating workloads. For live broadcasts, compute resources can ramp up instantly, while non-peak operations can scale back to conserve power and cut costs.

This optimization runs parallel to significant savings in capital and operational expenditures. Gone are the days of huge upfront investments in costly infrastructure. By automating processes and adopting cloud-native models, broadcasters can reduce their reliance on physical equipment and ongoing maintenance. Pay-as-you-go systems further enhance flexibility, allowing broadcasters to allocate budgets strategically rather than locking them into fixed, oversized installations.

Reducing On-Air Risks with Automation
The stakes in broadcasting are high. A single on-air incident—from a technical glitch to a scheduling error—can damage audience trust and undermine relationships with advertisers. Alarmingly, human error has long been the leading cause of such disruptions. Here, automation plays a pivotal role in boosting reliability and minimizing risks.

With automated fail-safes in place, systems can instantly detect and resolve potential issues. Should a primary stream face a problem, automated workflows can shift to a backup stream without delay, ensuring seamless broadcasting. Similarly, scheduling conflicts and compliance oversights are virtually eliminated by rule-based automation. This consistency instills confidence, not only within operations teams but also among viewers and clients relying on uninterrupted, high-quality delivery.

Navigating a Disrupted Market
Broadcasters today face constant disruption, from mergers creating operational sprawl to tighter budgets demanding more output with fewer resources. Automation offers a critical solution, enabling organizations to streamline workflows, scale efficiently, and adapt to shifting market conditions. Whether integrating new assets, launching pop-up channels, or scaling down during off-peak periods, automation provides the flexibility and reliability needed to thrive.

Beyond cutting costs, it positions broadcasters for long-term success by maximizing efficiency and allowing them to focus on delivering high-quality content in an ever-changing media landscape.

NEW YORK—Fixed-purpose hardware-defined processing and delivery solutions have been standard in the world of video production for decades. However, these legacy systems, which require a large number of components and can be costly to deploy and maintain, have given way to more cost-effective software-based solutions that provide numerous benefits in video production that weren’t available with those dedicated hardware solutions.

“Virtual playout is becoming one of the enablers for broadcasters and content producers to do something that they were not really able to do before, which is to start launching hyper-specialized channels, so that they can have dedicated or targeted audiences they can address more easily, and can then start to monetize these new, more granular types or segments of the audience,” said Kevin Savina, director of product strategy at Dalet.

This move towards virtualization in the industry has spawned a new buzzword, “orchestration;” and it could be said that there are a symphony of opportunities that it now presents. However, to take advantage of what virtualization offers, there are actually two types of this orchestration that need to put in place.

“The first is a technical one, which is to orchestrate the appearance and provisioning of these virtual playout solutions,” added Savina. “And the other, which is the one that we are playing more of a role in, is to orchestrate the production process and the content preparation process to feed in these new types of channels that are suddenly appearing.”

On a more basic level orchestration also explains the lifecycle management of the workload that one would want to operate.

“Workloads need to be designed in terms of the functions needed and the topology of content flows between them and captured to a representation that’s readable by humans and computers,” said John R. Naylor, director of product security for Ross Video. “From a vendor’s perspective, at minimum we provide an API for virtualized products that enable them to be plugged into the workload’s topology.”

THE IMPORTANCE OF ORCHESTRATION

Today, even the term “virtualization” itself remains very much another industry buzzword—one that to some is now part of the industry’s migration to the cloud.

“At Harmonic we’re typically thinking of the cloud when we’re talking about virtualization,” said Andy Warman, director of playout solutions at the company. “However, the private and public cloud deployment has been changing over time and this is why this discussion of orchestration is important as it is necessary for multichannel deployment. Orchestration is far more significant than ever as it can take the function of the cloud with an effectively limitless pool of resources.”

It is allowing for greater customization in terms of how content can be delivered.

“With the advent of virtualization we have the ability to deploy systems quickly, and start up new channels as customers need these such as for live events,” said Karl Mehring, director of product management for playout at Grass Valley.

The issue in the short term is how virtualization will fit with legacy systems, even with the benefits it offers broadcasters and production houses.

“Not every customer has the ability to rebuild their production environment,” said Steve Reynolds, president of Imagine Communications, whose Virtualized Master Control solution that provides the ability to consolidate, streamline and create consistent workflows across teams. “We’re seeing that some will rely on a hybrid solution that includes an SDI-based infrastructure in the studio, while some customers have moved to virtualization in control and playout.”

To facilitate such a solution, Reynolds said some clients are creating so-called “islands of SDI functionality,” where content is then transferred to an IP environment in the same facility. “We see this as an integration layer where the old world and new world can talk together.”

MAKING THE TRANSITION

The biggest challenge in virtualization appears to be the ongoing transition the industry faces with the move from legacy systems. This requires more collaboration between vendor and customer, according to Daniel Robinson, Head of R&D at Pebble Beach Systems.

“Broadcasters can see where they want to go, but frequently have no idea how to get there when discussing virtualized and IP evolution,” he said. “The secret to our success, and the reason we have over 100 virtualized channels on the air today is that we partner with our customers and take a collaborative approach to ensure we meet their needs at a pace which suits them. It’s a unique strength that we’re very proud of.”

Going from SDI to IP will also require flexibility and openness to change. 

“The hard point of the transition will depend on how integrated a user is with the old-style broadcast infrastructure,” said Savina. “Moving forward, broadcasters also need to think in terms of multiple outputs that include linear streams, and if you don’t have the right tools upstream you could find yourself in deep trouble.”

However, this isn’t the first time the industry has faced a transition and while this one will end up being less about hardware, broadcasters and production facilities should be prepared for this brave new world.

“There are good examples with the move we’ve seen from tape to tapeless workflows,” said Warman. “We went through a very similar type of transition, and while we’re still not quite all the way with the transition to virtualization we’re making good progress.”

This move to virtualization is also providing new ways to do the same job.

“We are seeing less obvious solutions such as Software as a Service [SaaSs], and this provides the latest technology and also frees up the end user from inconvenient maintenance and upgrade cycles, and allows the user to focus on content delivery instead of software upgrades,” added Warman.

Another advantage is that the cloud offers the ability for users to experiment without a major investment in completely new hardware.

“It is easier to update software than a hardware board,” said Mehring. “That gives you the flexibility in how you modify your services.”

KEEPING IT SECURE

The move to virtualization introduces other challenges—including the fact that “content” and “data” will be increasingly interchangeable terms. And where there is data there is the risk of a breach.

“Cybersecurity is a huge concern for anyone in this industry, especially as the move to solutions that aren’t housed in four walls of a broadcaster,” said Bea Alonso, director of product marketing at Dalet. “It is difficult to keep up with the number of threats, but we should remember there was no security on the old VTRs.”

The industry will need to realize the nature of potential threats, but also take advantage of the available countermeasures. Security is about defending three principles: availability, integrity and confidentiality, according to Naylor.

“This priority order is the reverse of how government agencies and the military usually put them but is what’s appropriate for commercial operations,” he said. “The loss of confidential information is prevented using standard controls similar to those in place in a traditional broadcast infrastructure. The only twist that virtualization possibly adds is when your workload is but one of multiple tenants on a physical host which theoretically opens it up to attack from co-hosted bad actors.”

Broadcasters are not facing cyber threats alone—and in fact are actually late comers at least in terms of needing cybersecurity. Thus there are plenty of examples of how it has been done right in other industries.

“Because we are moving to standard IP technology and standard IP platforms we can draw from industries that are much wider than broadcast industry,” said Reynolds. “We can look at others, and by no means are a first mover so we have the advantage to draw upon experts and best practices.”

FUTURE PROOFING PRODUCTION

The final consideration to virtualization is the advantages that it could offer to content creators at all levels. This could be the final significant transition, in part because it is more future proof than legacy hardware. This is notable as the industry underwent only minor updates in the early days of video production from the early days of television until the late 1990s with the beginning of the transition from standard definition to HD.

Since then the industry has—in essence—experienced one transition after another, but virtualization could result in the end of such major transitions.

“Our upgrade path is much more streamlined than ever before,” said Reynolds. “We had the move from 1080 to 4K, and we can look at that as a blueprint for future moves. With HD to 4K you replaced a couple of components but you didn’t have to significantly replace everything in the workflow, just a few codecs. It resulted in a much more streamlined way to make a transition and that is what we can expect going forward. We will then move from a ‘revolution’ change and back to a more traditional ‘evolution.’”

Of course getting to that point will still require some effort however.

We’re at the point where users are getting over learning about the technology and finally putting it to use,” said Mehring. “We’re not at the end, but this is the end of the beginning.”