In any business’ financial world, the company officers, sales leaders, engineers and such are often asked to justify not just the “reasons” for making decisions, but are also to validate the return (usually monetarily) on what assumptions, decision or investments (i.e., the “costs”) are involved in making that decision. Besides just the project “budget,” this summary is often known as the “return on investment” (aka “ROI”)—and this generally becomes a determining factor in making a “go for it” (or not) on the project or its expenditures.
Those metrics are needed to assess the “investment” in terms of expenditures, i.e., the dollars for capital or operating, the number or size or resources (people, space hardware or even outside services) and finally “how long will it take to recover or begin seeing meaningful returns” (profits). Figures or merit may further involve what will be the volume (size) of those returns in terms of new (or reduced) people, expected costs, efficiencies and performance.
Given the astounding references to AI given in everything today…a great many will emphasize these “ROI factors” while at the same time attempting to understand what is gained by going “down the AI path” and the change requirements needed to realize this ROI when employing AI in the solution. These factors can be very different elements which are applied depending on where, how and by what means the adaptation of AI concepts will be utilized…especially given the acceleration in tech, media, engineering, manufacturing, etc.
To examine the impacts of AI, many find that using “the marketing segments” is a worthy workplace factor when deciding what elements of AI are best applied and where as the business evolves. We’ll use the “marketing segment” as the strategy for example in this article on AI in the marketing era.
AI in the Market
A recent marketing-focused white paper from iterable.com stated that 47% of marketers are drawn to AI for its ability to make their work more efficient. Higher efficiency means more time to strategize on how to reach customers in a meaningful way. However, the way marketers view AI goes way beyond that.
A white paper in “Ad Age” highlighted some of the findings from a Wakefield Research survey of 1,200 marketers worldwide. The survey took a deep dive into how companies are taking a second look at AI and includes many of the benefits it can bring when used in the marketing space and beyond.
As marketers become more comfortable with technology and the use of AI applications expands, a brand definition still requires human intervention for maximum creativity. AI is well-suited for testing and simulations, but it has not yet become a replacement for a human’s smarts and emotions.
Defining ROI
ROI is a simple way to measure an investment’s profitability, showing how much money was made compared to how much was spent, usually as a percentage (i.e. 10% or 200%). It tells you the “bang for your buck,” indicating how efficiently an investment generates earnings relative to its cost. This helps you compare different options. In short, ROI is a financial ratio comparing the gain or loss from an investment to its cost (Fig. 1). But how does one define the “costs” of AI?
AI in banking and finance is certainly earmarked for the future, but how will that be measured and affirmed? AI can’t succeed on its own, and it isn’t just a passing trend (like 3DTV). AI is intended to aid in the support of risk management, customer service and operational efficiency by continually cross-analyzing data sets across all elements of the enterprise and providing insightful information about changes, all the while running evaluation models that curate data on projects, sales, costs and other elements needed to make assertive decisions critical to success across the organization.
In 2023, McKinsey & Co. said banking was expected to be one of the top two industries spending the most on AI: “The economic potential of generative AI…is the next productivity frontier.” That report affirmed that one must “first look at where business value could accrue and the potential impacts on the workforce.”
AI has permeated our lives “incrementally,” and not just in terms of tech (i.e., from smartphones to self-driving automobiles). Generative AI apps such as ChatGPT, GitHub Copilot and Stable Diffusion have not only captured imaginations, they’re now “routine” in nearly every task from paying bills online, to ordering prescriptions, to classifying data at all segments of the population, to daily workforce tasks. Fig. 2 shows some of the AutoGPT principles and tasks that will be explored as this column continues.
GenAI “has the potential to change the anatomy of work, by fundamentally augmenting individual workers’ activities. Current generative AI, coupled with other technologies, has the potential to automate work activities that absorb as much as 70% of an employee’s time “today.” That ROI can immediately be equated to dollars saved or performance increases per unit time.
Earliest Adopters
According to a Google ad from February, 86% of marketers are using AI. A Harris Poll from October 024 states, “marketing is the most communication-driven and content-heavy function in any organization.”
As AI reshapes how work gets done, marketing teams have been among the earliest adopters, leveraging ROI through more complex communications, refined brand messaging and greater workloads. AI offers critical opportunities to reduce inefficiencies, scale content production and improve cross-team communications, often without direct human intervention.
Generative AI isn’t just another technology shift — it’s a fundamental transformation in how enterprises operate. The best CIOs are using it to drive innovation, competitive advantage and efficiency. Without AI, they risk falling behind or worse, becoming obsolete.
Researchers agree that AI’s positive benefits for marketers with 92% saying that they saw a reduced workload, 91% saw an increase in productivity and 91% reported increased creativity, with 87% reporting improved communications.
To sum it up, according to the SOBC Marketing Report, an average of 27% of marketers use AI for drafting, 25% for responding and 40% for enhancing communications—with a mix of 23% using AI to respond to emails and 28% using it to respond to chats or simple “pings.”
These are monumental changes to how the workforce is evolving, considering that you, as the recipient of these responses from AI bots, now have no idea who really responded, or if that person had some tech agent doing their work for them. Does this trend worry you or annoy you? One must now fully flesh out the integrity of the workforce and where it is heading, in whole or in general.
What is the “path to efficiency and effectiveness” now? Will it lead to more errors or reduce the risks of having little to no—or less—human intervention or thought processes involved in decision-making?
One might be reminded of “War Games,” the 1983 Matthew Broderick movie, in which computers were the players in a global epic event where AI almost left the “human decision-making process” paralyzed. Only time will tell!
Agents or Bots?
Most are familiar with chatbots, but aren’t as familiar with AI agents. But AI agents (i.e., Large Language Models, or LLMs, that perceive their environment) go well beyond chatbots. Such AI agents will plan and make decisions, run tasks and team up with other tools to aggressively attack tasks such as cross-coding, other AI services, content, operations and more.
Bots are more or less an input device that sends queries to preprogrammed sets of sequences, doing little “interpretative thinking.” Chatbots are reactive, conversational tools designed to answer questions based on scripts or AI models.
Are the emerging chatbots becoming tomorrow’s assistants, or will today’s assistants seem to be stuck in the waiting room of productivity? It’s hard to tell, but certainly worrying to some.
