Business schools cannot afford to wait out the AI era

AACSB-accredited schools are confronting a question business educators can no longer put off: Are we preparing students for a world that is AI native, or simply layering new tools onto existing models without fundamentally rethinking how we educate?

It's a question that goes to the heart of what business education is for. And for schools facing unprecedented technological change, the answer will determine whether they remain relevant or miss the opportunity to lead.

Some business schools may be betting they can wait out the AI era, holding off until the landscape stabilises before making significant changes. But institutions building future-ready approaches today are likely to be better positioned for tomorrow.

From awareness to transformation

The defining divide in business education is no longer between institutions that have adopted AI and those that have not. It's between adoption and transformation.

AACSB's 2025 State of Accreditation Report revealed that 97% of accredited business schools now mention AI in their accreditation documents.

Forbes reports that 90% of college students use AI tools. Perhaps most strikingly, a KPMG study found that 70% of students surveyed turned to generative AI for help instead of asking their instructors.

These figures demonstrate widespread adoption. But adoption alone does not represent institutional transformation. Also important is whether adoption is translating into meaningful change. Are institutions redesigning how they teach, assess, and develop students, or simply layering AI onto existing models?

In many cases, AI is improving individual efficiency without fundamentally changing how learning is designed, assessed, or measured. Meanwhile, employers are redesigning work, embedding AI into core business processes, and redefining what workforce readiness looks like.

The power of faculty involvement

Faculty capability has emerged as one of the most important factors in determining whether AI integration succeeds or stalls.

The Inspire Higher Ed report, developed in partnership with AACSB and other leading organisations, highlights that sustained faculty development (not one-time training) underpins every successful example of AI integration in business education. Without it, institutions struggle to move beyond experimentation.

Many faculty members are being asked to integrate AI into their teaching without the sustained support needed to do so effectively. This is one of the genuine tensions institutions face: the pace of change in the external environment does not always align with what is realistic for faculty who are already stretched.

One-off training sessions are unlikely to be enough. Institutions that are making progress tend to invest in ongoing faculty development that is embedded in day-to-day academic practice, rather than treated as a separate initiative.

There is also a real risk of overcorrection. In responding to external pressure, some institutions may move too quickly, adding AI content to courses without rethinking the underlying programme logic or changing assessment structures before faculty have had the time to engage with what those changes are for.

That kind of acceleration can produce fragmented results and erode the coherence that makes a programme credible. But the alternative – standing still – is no solution either. Faculty who actively engage with AI will be better positioned to help students navigate a world where AI is already reshaping how business is done.

AI literacy goes beyond prompting a chatbot

Student expectations are accelerating the pressure on institutions.

The 2026 GMAC Prospective Students Survey shows that demand for AI-related skills is now widespread across degree types, with nearly half or more of candidates expecting exposure to artificial intelligence alongside business analytics and strategy.

Moreover, candidates are not simply interested in theoretical coverage. They are actively seeking hands-on applications of AI in decision-making and real business contexts. Students increasingly recognise that AI capability will be an important part of career readiness.

But AI literacy is not simply about learning to prompt a chatbot. The Inspire Higher Ed framework emphasises that AI literacy is becoming a foundational capability for all business graduates, alongside the ability to critically evaluate AI outputs and work effectively in human-AI collaboration.

As AI takes on more execution tasks, the distinctly human contribution concentrates around three things: defining the problem clearly, evaluating what AI produces, and taking responsibility for how systems are governed over time.

AI systems lack full contextual awareness. They do not understand organisational purposes or culture, cannot interpret nuanced human dynamics, and cannot take responsibility for decisions.

This distinction is critical. AI excels at scale and speed. Humans remain responsible for defining problems, interpreting results, and making decisions in complex, ambiguous environments. AI can suggest answers, but humans must determine which answers matter and be accountable for how they act on them.

Tomorrow’s leaders need to understand how AI systems work, where they fail, and how to deploy them responsibly. That requires a fundamentally different kind of curriculum – one that embeds AI across disciplines rather than confining it to isolated modules.

Why waiting won’t work

The instinct to wait for AI standards to settle and for technologies to mature is understandable. But it's also a mistake.

While some business schools are choosing to wait, others are beginning to formalise their approach. Governance structures, ethical guidelines, and institutional policies around AI are becoming more common, signalling a shift from experimentation to infrastructure.

This reflects a broader recognition that AI is not a temporary disruption but a permanent feature of the educational and business landscape.

Schools that can deliver AI literacy at the programme level – woven through disciplines rather than confined to isolated modules – will be better positioned to meet student and employer expectations in an increasingly competitive environment.

Graduates from schools that engage seriously with this shift will be better prepared for the workforce they are entering.

The business schools that will matter will be those that connect with business and society, redesign curricula around enduring capabilities rather than chasing the latest tools, and invest in faculty as the primary lever of transformation – recognising that this takes time and real support.

The purpose of education in an AI era

Ultimately, this is not a story about technology. It's a story about purpose. AI is prompting institutions to revisit fundamental questions: What skills truly matter? What capabilities endure? How do we design learning experiences that develop them in a world where information is always accessible?

As the pace of change shortens the shelf life of skills, focusing only on current tools risks preparing students for yesterday's problems. What matters more are capabilities that endure: the ability to think critically, learn continuously, and apply judgement in unfamiliar contexts.

Business schools that recognise this shift – by embedding AI across their curricula, investing in faculty, and prioritising human capabilities – will not simply adapt to change. They will become essential in shaping the future of work. Those that do not risk losing relevance, not just in technology, but in purpose.

AI is not reducing the need for education – it is increasing it.

Stephanie Bryant is executive vice-president and chief accreditation officer at AACSB International, the global accreditor of business schools and the world’s largest business school association, representing some 2,000 institutions across more than 100 countries.

This article is a commentary. Commentary articles are the opinions of the author and do not necessarily reflect the views of University World News.