AI Belongs In The Business School Clinic — Not Just The Lab

Business schools love to talk about innovation. But when it comes to artificial intelligence, many are still stuck in lecture mode—debating case studies, theorizing disruptions, or worse, banning generative AI tools altogether.

That’s not just shortsighted. It’s malpractice.

I’ve long argued that business schools should follow the medical school model. Both are professional programs. Both prepare students for high-stakes environments. And both should rely on faculty who are not just researchers, but practicing professionals.

Imagine a med school that only teaches anatomy and case reviews but never takes students into the clinic. That’s exactly how many business schools are still approaching AI.

Moving From Seminar Room to Simulation Lab

We need to move AI from the seminar room into the simulation lab—from theoretical to clinical. This is the only way to prepare students for a business world where AI is no longer an emerging trend—it’s the operating system.

AI is already transforming marketing, finance, operations, and human capital management. Business students don’t need to know how to build these tools. They need to know how to use them—fluently, ethically, and strategically. That requires more than a guest lecture or an elective course. It requires immersion.

In medicine, clinical rotations put students shoulder-to-shoulder with experienced practitioners. That same model should apply in business education. Students should be running sentiment analyses in real-time, optimizing pricing models with machine learning, or using generative AI to redesign service workflows. And they should be doing this under the guidance of faculty who know how these tools work—not from theory, but from practice.

Real-World Implementation

At the institutions I’ve led, we’ve embedded applied technology into the business curriculum. We’ve launched student-run venture capital labs, real-time analytics centers, and MBA modules where AI tools are not the topic—they’re the medium. Students don’t write papers about AI. They use it to solve real problems, in real time.

This is the shift business education must make:

1. Faculty must be active practitioners, not just scholars of disruption.
2. AI must be integrated across disciplines, not confined to electives.
3. Students must learn by doing, just as future doctors do.

Beyond the Basics

Let’s be clear: this isn’t about eliminating core business knowledge. It’s about deepening it. Just as calculators didn’t eliminate the need to understand math, AI won’t replace foundational business thinking. In fact, it demands it. You can’t prompt well without insight. You can’t analyze without context. And you can’t lead without knowing how the tools your teams use actually work.

What’s at stake isn’t just relevance. It’s credibility. Employers are already expecting AI literacy. Students are using these tools—whether we teach them or not. And industry is moving ahead, often developing its own credentialing systems in the absence of agile academic programs.

The Path Forward

Business schools have a choice. We can remain observers of AI’s impact—or we can become its interpreters, its implementers, and its ethical compass.

That will take bold leadership. It will take a new approach to faculty hiring, curriculum design, and institutional partnerships. And it will take a willingness to operate more like clinics than classrooms.

AI is already reshaping every corner of the business world. The question is whether business schools will catch up—or stay behind in their own lecture halls.

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Dr. Elad Granot is a three-time business school dean, tech founder, and venture capital investor. He is Professor of Marketing at John Carroll University and a national thought leader in higher education innovation, AI fluency, and applied business education.