This role is supported by 2024 research led by Felipe Csaszar at the University of Michigan’s Ross School of Business exploring how AI affects strategic decision-making. Using evidence from an accelerator programme and a startup competition, the paper demonstrates that current large language models can generate and evaluate strategies at a level comparable to entrepreneurs and investors. The researchers also argue that AI may augment core cognitive processes involved in strategy, including search, representation and aggregation. Moreover, the study suggests that AI has the potential to increase the speed, quality and scale of strategic analysis. AI as a coach: stimulating self-awareness MBA programmes are both academic and developmental, with students often trying to improve how they lead, communicate and influence. AI can play a useful coaching role here, as it can help students rehearse presentations, simulate difficult conversations, test the clarity and tone of communication or prompt reflection after a class session. A student preparing to give feedback to a colleague, for example, might use AI to role-play possible responses. A student preparing for a presentation might use AI to identify where an argument is unclear or overly complex. Research published in 2024 by the University of Cincinnati’s Scott Dust and Laurens Steed supports this kind of use. Their study found that engagement in an automated coaching platform increased participants’ metacognitive activities daily, with benefits spilling over into a next-day need for self-knowledge and learning goal orientation. In other words, automated coaching appeared to stimulate reflection, self-awareness and a stronger developmental orientation – key ingredients for leadership development and effective teamwork. These findings suggest that AI-based coaching tools could be particularly useful for EMBA students. At the same time, AI cannot replace real human relationships, moral accountability or the emotional intelligence required in actual
BIOGRAPHY Amanda Shantz is chair of responsible leadership at Trinity College Dublin, Ireland. She has been at the forefront of the design and delivery of MBA, executive MBA and executive education programmes for more than 15 years. Her research focuses on how organisations leverage human talent to achieve high levels of performance while also making a positive impact in the communities in which they operate
leadership situations. Therefore, while it may help students prepare, it does not remove the need to engage thoughtfully with real people in real contexts. AI as an analyst: synthesising complex material One of the central challenges in MBA study is information overload. Students must often work with readings, notes, case materials, organisational data and feedback from multiple sources. AI can be extremely useful in helping make sense of this complexity. It can compare documents, identify recurring themes, distil long notes into patterns, organise qualitative material and help students move from information to insight. This analytical role overlaps with the strategic decision-making evidence noted above. Indeed, Csaszar and his co-authors suggested that AI can improve search, representation and aggregation in strategic contexts, making it useful not only for generating options but also for synthesising and structuring complex material. In practice, a student might use AI to synthesise themes from (anonymous) stakeholder interview notes, compare competing leadership models across readings, or extract key tensions from
30 Ambition • ISSUE 5 • 2026
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