Everyone Has AI. Who Has a Strategy?

More than 60 percent of American adults now use AI in some form, and corporations have spent billions on models and platforms. The question most still cannot answer is the one that matters: Where are the returns?

That gap is where my team and I are doing some of our most consequential work. Together with H.C. Gao and Huanhuan Shi, associate professors of marketing at Mays, plus Adi Pattabhiramaiah at Georgia Tech, Martin Mende at Arizona State, Vamsi Kanuri at Notre Dame, and Muzeeb Shaik at Indiana University, I am working to build frameworks for a discipline that is still emerging: the strategic management of AI as a business resource.

One line of research tackles return on AI directly. A retailer deploys a personalization engine, sees a 12 percent conversion lift, and celebrates. Six months later, the lift is gone. The model drifted as customer behavior shifted, and no one noticed. This is not an implementation failure. Unlike a CRM system, which stores data faithfully until you change it, an AI model changes itself. It learns, drifts, erodes. We argue that return on AI (RoAI) is not a number you calculate at launch. It is a management discipline, continuous and largely uninvented.

Other research examines what happens when AI agents replace humans in the buying process. For example, AI trip planners now finalize hotel reservations autonomously, evaluating cancellation policies and structured data. The hotel with the evocative brand story gets filtered out before any person sees it. The basis of competition has shifted from persuasion to structured transparency. Trust is no longer earned through a relationship. It is the entry requirement for being considered at all. Related work maps how different consumer segments experience AI in fundamentally different ways. Field experiments with Agastya International Foundation, from Texas to Bodoland, Assam, in India are studying what deliberate human-AI collaboration can achieve where resources are scarce.

Across all of it, the same strategic conclusion keeps emerging: the firms that win will not be those that adopted AI earliest, but those that learned to design it with intention and apply scientific human guardrails around it. My goal is to help firms and policymakers with a framework for competing on AI before the strategy window closes.