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– Written by Edosa Odaro

Your marketing team requests an AI recommendation system. IT refuses to prioritize it without proven business value. But marketing can’t demonstrate value without the working system. Compliance won’t approve the pilot because of liability concerns. And finance just denied everyone’s budget request because nobody can agree on priorities.
Welcome to the prisoner’s dilemma of AI implementation.
Here’s what game theorists discovered decades ago: when groups optimize for their own success without coordination, everyone ends up worse off. Your AI initiative faces this exact problem. Compliance minimizes risk rather than enabling innovation. Technology teams chase technical excellence over business adoption. Business units focus on quarterly results instead of building long-term capabilities. Finance controls costs rather than creating value.
Each department makes perfectly rational decisions. The collective outcome? Failed AI initiatives. Missed organizational value. And mutual finger-pointing.
A healthcare organization watched this play out with their AI diagnostic system. IT measured implementation speed. Clinicians tracked diagnostic accuracy. Finance monitored costs. Each department succeeded by their own metrics while the overall initiative delivered disappointing results. Nobody won because everyone played their own game.
Traditional project management sets up what game theorists call a “one-shot game.” Departments make decisions, hand off their work, and move on. There’s no incentive to care about the collective outcome because they won’t face consequences from other players again.
Dr. Thuc Vu, entrepreneur and co-founder of OhmniLabs, explains it clearly: “If you think of collaboration in business as a game, then people are just playing a game. It’s like a one-shot game — a bit of a dilemma — and at Nash equilibrium, everyone is going to cheat in a way, non-collaborate.”
Your governance structure creates this trap — one-time approvals, separate budgets, individual metrics, functional handoffs. Every structural choice pushes departments toward self-optimization instead of collaboration.
First, transform one-shot games into repeated games. The same healthcare organization restructured its diagnostic AI around ongoing cross-functional governance. Rather than IT judged solely on timeliness, clinicians on accuracy, and finance on costs, it established a bonus structure where 30 percent of each department’s performance evaluation came from the overall system’s success.
The result? The Nash equilibrium (in which each department chooses its best possible strategy) shifted from departmental optimization to system-level success. Cooperation became the rational choice.
When departments know they’ll continue working together — and when their success depends on collective outcomes — behavior changes fundamentally.
Second, redesign your payoff structure. A telecommunications company moved from departmental budgets to a three-tier portfolio model: enterprise platforms funded centrally, cross-functional use cases funded through shared budgets, and departmental applications funded locally. This created natural incentives for collaboration on high-impact initiatives while maintaining autonomy for specialized needs.
Third, increase interaction frequency. Game theory proves that repeated interactions foster cooperation. Create regular cross-functional working sessions, shared project spaces, and rotation programs.
One manufacturing company established weekly “value stream” meetings where engineering, operations, and supply chain reviewed progress together. The frequent touchpoints shifted behavior from territorial protection to collaborative problem-solving.
Beyond structure, you need five specific mechanisms.
A retail company applying these principles to demand forecasting AI modified its entire incentive structure. Inventory managers, merchandizing teams, and store operations all shared metrics around forecast accuracy, inventory levels, and customer availability. This replaced previous incentives that had inventory minimizing stock while merchandising maximized variety and stores demanded perfect availability — all rational individually, collectively impossible.
The prisoner’s dilemma persists because your organizational design creates it. Separate budgets encourage hoarding. Individual metrics reward local optimization. One-time approvals eliminate future consequences. Functional silos reduce visibility into collective outcomes.
Dr. Vu offers the solution: “But if we remodel it and repeat the game so that people will play the game over again, there are some very interesting game theoretical approaches which can enforce the behavior out of this game, so that we can not only incentivize but force collaboration between the players.”
Your AI initiative doesn’t need better algorithms or more sophisticated models. It needs game theory. Restructure governance from one-time to continuous. Replace individual with shared metrics. Transform handoffs into co-creation. Make cooperation the rational choice instead of the noble sacrifice.
The departments aren’t the problem. The game you’ve asked them to play is.

Edosa Odaro stands at the forefront of artificial intelligence and data transformation. As Executive Advisor for Data & AI, and Chief Data Analytics & Privacy Officer, he has guided international organizations through complex transformations that delivered substantial, sustainable results. Recognized as a Financial Times Top 100 Most Influential Leader and a Global 100 Data Activator, he’s a sought-after speaker and advisor, known for his ability to distill complex technical concepts into actionable strategies that create lasting organizational value. His new book is Values of Artificial Intelligence: How Smart Leaders Capture and Connect AI Value to Human Values (Auerbach Publications, Jan. 29, 2026). Learn more at edosaodaro.com.
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