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GMAC research entitled AI in Business Education referenced an AACSB survey in which deans displayed more optimism over the adoption and acceptance of Generative AI (GenAI) by their community than faculty members. Why do you think this might be? competitiveness. They’re thinking about how GenAI can support programme evolution, operational efficiency and market positioning. Faculty, meanwhile, are more immersed in the day-to-day reality of teaching and assessment, where the disruption feels more immediate and personal. Concerns around academic integrity, workload and pedagogical fit are understandably more pronounced among faculty. They’re grappling with how to integrate GenAI without compromising educational quality or creating new inequalities in the classroom. Bridging this gap requires dialogue, professional development and inclusive decision-making because faculty buy-in is essential to making GenAI adoption both ethical and effective.” How can business schools get around some of the barriers and resistance to GenAI identified by GMAC’s study? “The key lies in building trust and capability. “Deans have a wider strategic view of institutional innovation and external Resistance often stems from a lack of familiarity or support, so schools need to invest in training that’s accessible, relevant and ongoing. Creating safe spaces for experimentation, where faculty and staff can test GenAI tools in low-stakes environments, can also help shift the culture. “Institutional championing and clarity around policies and ethical frameworks are vital. When educators feel supported by clear guidelines and leadership, they’re more likely to engage proactively. Importantly, successful adoption isn’t just about technology, it’s also about change management. Schools that listen to their faculty and students, acknowledge their concerns and co-create solutions will lead the way.” Your AI study encompassed case studies from six different institutions. What stood out most to you among these examples of the technology’s current uses? “What stood out most was the variety of entry points and the creativity schools are showing.
From experimenting with AI-powered feedback in written assignments to using GenAI for student wellbeing interventions, institutions are not merely thinking about AI in terms of cost-saving, but rather as a tool for pedagogy, inclusion and engagement. “One compelling example was a school using GenAI to simulate real-world business scenarios that students could interact with, bridging the gap between theory and practice. Another was using GenAI to support neurodiverse learners through personalised scaffolding. These case studies reminded us that AI isn’t one-size-fits- all. The institutions leading the charge are those that align AI use with their unique mission, culture and student needs.” How might changing approaches to learning assessment within business schools impact on the GMAT test? Would you ever consider integrating an element of GenAI prompt engineering, or a critical assessment of AI‑generated outputs and biases, into the test? “As assessment models evolve to emphasise applied learning, collaboration and real-world problem-solving, admissions tests like the GMAT are adapting in parallel. The modifications we made recently to the test were already a further move away from rote memorisation, instead emphasising analytical reasoning, decision-making and data literacy. These are all core competencies for today’s workplace, as well as being essential where AI is concerned. There are many amazing opportunities coming from the technology but it is crucial that humans can still think critically and analyse their own data sources, not just what has been presented by a large language model. “Looking ahead, there is an expansive set of possibilities to evolve the test further to reflect the increasing integration of AI into professional life, including those you mentioned. That said, any future development must be grounded in rigorous psychometric research and fairness across global populations, which takes time, alongside more data on how businesses integrate AI. “We’re committed to ensuring the GMAT remains not only a valid predictor of academic success, but also a signal of readiness for a world in which human and artificial intelligence increasingly intersect.”
“AI adoption isn’t just about integrating the latest tools, it’s also about fostering digital fluency, ethical awareness and systems thinking”
Nalisha Patel is regional director for the Americas and Europe at GMAC, where she is responsible for the organisation’s overall strategy in promoting the regions as business education destinations and building diverse pipelines of talent there. Patel has more than a decade of experience in graduate management education, including serving as executive director of degree programmes and student experience, as well as a governing body member, at London Business School
www.gmac.com
Ambition • ISSUE 4 • 2025 17
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