A simple classroom exercise offers a powerful lesson for enterprises struggling to turn generative AI investment into meaningful results.
GUEST COLUMN | by Darren Person
IVAN RYABOKON
While artificial intelligence (AI) has been transformational across industries, many organizations are still struggling to see real business impact. In fact, MIT’s recent State of AI in Business 2025 found that 95% of organizations are getting zero return on their GenAI investments. That number is staggering, considering the significant AI investment organizations are making.
‘…95% of organizations are getting zero return on their GenAI investments. That number is staggering, considering the significant AI investment organizations are making.’
The reason most AI initiatives stall is surprisingly simple. Organizations are deploying powerful technology without a shared understanding of how to instruct it or what outcomes it should deliver. The solution is not more tools or bigger models, but clearer thinking, something most of us first learned in a classroom.
The Need for Clear Instructions
Many of us remember the classroom exercise where a teacher asks students to explain how to properly make a peanut butter and jelly sandwich. The students, eager to answer the seemingly simple question, typically say something like, “take out the bread and put peanut butter on it.” The teacher then takes out a loaf of bread and places the unopened peanut butter jar on top of it, and the students erupt in laughter. This goes on with varying degrees of instructions and actions, none of which result in a successful sandwich. Following several rounds of trial and error, the laughter fades, and the lesson becomes clear. Precision matters. Outcomes depend entirely on the quality and clarity of the instructions.
Now replace the classroom with an enterprise and the students with its workforce. Today’s organizations are handing out a powerful new programming language to employees who’ve never had to “program” before. While the syntax may be English rather than Java, ultimately, it’s still code and will execute directly what it’s told. While organizations expect individual employees to suddenly become prompt engineers, automation designers, and AI strategists, the truth is that access to AI does not equal understanding of how to properly instruct the technology. Organizations are asking users across departments to “take out the bread and put peanut butter on it,” and wondering why the “sandwich” doesn’t turn out quite right.
Three Principles for AI Success
Most enterprise AI projects start with enthusiasm but unfortunately stall in the execution phase. This is not because AI fails, but because the instructions, expectations, and operating context are unclear.
It’s also important to understand that AI itself isn’t a strategy; it’s a tool, and a powerful one at that. AI deployments must serve a product strategy, a customer need, or a desired business outcome. To move from experimentation to real business impact, enterprises need to follow three pragmatic principles:
A clear strategy. Every AI initiative should be anchored to a customer problem or business outcome. AI should accelerate a strategy, not become the strategy.
Investment in AI literacy. Expecting every individual to know how to use AI is like asking every student, regardless of discipline, to know how to program a robot they’ve never seen before with no instructions. Success lies in building capability through workshops, use-case champions, and hands-on experimentation. AI literacy is foundational to success.
Focus on practical workflows. The most successful AI use cases aren’t flashy; they’re practical. Start small – automate repetitive tasks, improve search and retrieval, enhance customer service, and build credibility through true business impact, not hype.
By following these principles, enterprises can close the gap between ambition and execution, ensuring all users are aligned on purpose and have the tools for successful deployment.
Achieving Meaningful AI Impact
Today’s enterprises are at an inflection point. Those that treat AI as a magic trick will see their deployments quickly burn out. Those that treat AI as a craft – something to be learned, practiced, and applied thoughtfully – will build durable advantage and business impact. A successful AI strategy begins by listening to users and customers to understand the tangible ways that the technology can truly make a difference and solve real pain points.
The organizations that will succeed in AI will start with clarity of purpose and then provide the AI literacy needed to build, apply and responsibly complete deployments. Just like the classroom lesson on making a peanut butter and jelly sandwich, clarity of instruction determines the outcome. With a clear strategy and proper training on how to deliver direct and intentional instructions, the results can be far more satisfying.
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Darren Person is EVP & Chief Digital Officer at Cengage Group, bringing more than 25 years of experience leading large-scale product, platform, data, and AI transformations across global media, information services, and education organizations. Connect with Darren on LinkedIn.
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