Generative AI Is Coming For Business Schools—But How Exactly?

Generative AI is already reshaping industries—and business schools are no exception. As tools like ChatGPT, DALL-E, and Bard become ubiquitous, their impact on how business education is delivered, experienced, and assessed is changing. But what will generative AI mean for business schools a year from now—or five? It depends on who you ask.

Five Unanswered Questions On AI’s Impact On Business Schools

As a lecturer of academic writing, I noticed the impact of ChatGPT almost immediately—overnight, there was a strong bunching around the generic middle. Gone were the linguistic train wrecks, but so too were many of the unique, highly sophisticated (and quirky) papers. Generative AI polished off the rough edges, for better or worse.

My observations, however, are limited to my own immediate experience. To explore the systemic transformations unleashed by generative AI on business schools—and more importantly, the transformation it may hold in the months and years to come—I spoke to four experts within my network of academic colleagues: Jonathan Boymal, Associate Professor of Economics at RMIT University; Donald Clark, AI entrepreneur and author of Artificial Intelligence for Learning; Patricia Feubli, Professor and co-head of the MSc in Information and Data Science at the Lucerne School of Business (where I also teach); and Douglas MacKevett, Head of Digital Learning Services at the Lucerne School of Business.

All four agreed that generative AI is already changing how students and educators interact with business education. They also agreed that for business schools this has meant a careful balancing between, as MacKevett described it, “embracing opportunities while mitigating risks.”

But rather than looking at what business schools are doing—and not doing—today (there is good reporting on this elsewhere), I was curious about what possible impact these experts see down the line for students, for business schools, and for society at large.

On this, the four had a lot to say. I summarized some (though far from all) of their speculations about how things will change into five key questions. The answers to these questions will be become apparent only in the months and years ahead, but will have a profound impact on the world of learning and work.

1. Will The Use Of Generative AI Be Good For Student Learning?

“Most students are using this technology,” Clark said plainly. And why wouldn’t they? As MacKevett put it, “For students, it’s like having a personal tutor available 24/7—offering help with everything from clarifying concepts to refining assignments.”

Yet this convenience might come with a price. Boymal highlighted a key drawback: by using AI to reduce their “cognitive load,” students risk bypassing the “friction and desirable difficulties” that are vital for meaningful learning. “Outsourcing these tasks to generative AI tools can potentially undermine the development of important skills,” he explained.

Boymal also raised a lesser-discussed but critical concern: the “Equity Paradox.” While AI is a boost to those who are already experts in a domain, “it poses unique risks for novices. Its limitations—such as inaccuracies or biases in outputs—can hinder skill development for those still in the early stages of learning.”

Could generative AI, despite its promise to boost learning, hinder it among some groups of students? We will have to wait and see.

2. How Will The Social And Emotional Dimensions Of Learning Be Maintained?

Part of the answer to the question above will hinge on how exactly generative AI is integrated into curricula and the learning process. “While we often focus on the technology itself, we need to remember that AI can only be effective in environments that support growth, collaboration, and critical thinking,” Boymal emphasized. In thriving learning cultures—those rich in motivation, curiosity, and collaboration—AI has the potential to enhance learning. But in less growth-oriented settings, students might be tempted to treat AI as a shortcut, bypassing the deeper engagement required for meaningful learning.

AI cannot replicate the social and emotional dimensions of education, which are essential for solving complex problems. As Boymal pointed out, “Solving complex problems isn’t just about applying knowledge—it’s about drawing on emotional resilience and collaborating with peers and educators.”

Business schools have an opportunity to build learning cultures that seamlessly blend AI with human-centered education, promoting emotional resilience, social collaboration, and creativity. But will they do so, and how?

3. Will Professors Remain The Gatekeepers Of Knowledge?

Traditionally, professors have held the authority to determine what constitutes correct information in the classrooms. But as generative AI gains traction, this dynamic is beginning to change. “It is clear that power is moving towards the learner and away from the teacher,” Clark observed, signaling a fundamental shift in knowledge transmission.

Feubli referred to this as a problem of “knowledge authority.” She explained, “What information is correct, and who determines this? Currently, the responsibility for deciding what constitutes correct information lies with the lecturers, which is also not always optimal. In the future, however, this question will take on much greater importance as the transmission of knowledge becomes increasingly delegated to generative artificial intelligence.”

As students rely more heavily on AI tools, the role of professors as knowledge gatekeepers could diminish, raising profound questions about the future of authority and expertise.

4. Will Lecturers And Disciplines Be Relevant In The Future?

“One of the most profound shifts I foresee is a move away from traditional lectures, faculty-designed materials, and static exams toward a model that emphasizes coaching and real-time formative feedback,” MacKevett observed. Generative AI’s capacity for personalization could upend conventional teaching methods, enabling tailored learning experiences at every stage of the educational process. This shift is a clear challenge to the dominance of traditional lectures and standardized assessments.

Feubli raised an equally provocative question: “I wonder to what extent today’s sub-disciplines, such as marketing or accounting, will still play a role in the future.” Business schools currently produce specialists—graduates defined by their expertise in HR, marketing, or other areas. But as AI blurs the boundaries between fields and fosters interdisciplinary work, the relevance of narrowly defined disciplines may diminish, forcing schools to reconsider how they structure curricula to meet the demands of an integrated future.

5. Will Business Schools Even Be Relevant in the Future?

Perhaps the most profound question of all is, “How can young people be convinced to pursue structured education in the future instead of simply relying on generative artificial intelligence?” Feubli’s question strikes at the core of business education’s uncertain future. As generative AI becomes a ubiquitous and often powerful substitute for traditional learning, the value proposition of structured education is increasingly under scrutiny.

Boymal added another dimension to this challenge: the disruption of traditional career pathways. With generative AI poised to take over entry-level tasks, young professionals may lose critical opportunities to “gain hands-on experience and mentorship,” that is, “essential for career progression.” This could create a “bottleneck” in professional development that risks slowing the cultivation of future industry leaders.

Unanswered Questions

Generative AI is undeniably disruptive, and while its presence in business schools is already being felt, even the experts I spoke to aren’t entirely sure where exactly it will lead (nor are experts in other areas, for that matter). The shifts explored above highlight just how much is up in the air.

Will business schools double down on their human-centered value, or will they pivot toward AI-driven personalized education—or find a way to combine both? Will they lead the charge in shaping future-proof leaders, or struggle to adapt to a landscape they no longer control? Will they even be around? These questions remain unanswered.

What is clear is that generative AI is not just another tool; it’s a force reshaping the foundations of education. And, as with all disruption, both opportunities and pitfalls are abundant on the road ahead.