AI enhanced leap learning

AI is a priority everywhere. How is Vlerick positioning itself in the AI arena?

Steve Muylle: “AI is not a separate project for us. Instead, we regard it as an extension of two strategic priorities that help us to stand out: digital learning innovation and taking your next leap. When you bring the two together, you get a very powerful combination. AI is the technology that enables us to further deepen and accelerate these strategic priorities. This is what we call ‘AI enhanced leap learning’. ‘AI enhanced’ is exactly what the name suggests. We use AI to enhance our educational approach. And ‘leap learning’ refers to this approach, which helps to achieve the leap that every student or participant wants to take in his or her life.”

Did you also include the students and participants in this exercise?

Steve Muylle: “We analysed almost 25,000 qualitative feedback points using 3 AI tools, of course not forgetting the crucial critical judgement of humans. What makes the learning experience at Vlerick special? Where is there room for improvement? No fewer than 93% of our students and participants gave meaningful answers to these questions, and the resulting insights were sent to our professors right away.

It turns out that four elements make our learning experience special: 1) we start from the leap itself, namely the concrete step that someone wants to take in his or her career or personal life, and support this through 2) applied learning or converting the theory into action in various ways, such as through case studies, business games, simulations and practical projects, 3) the quality, energy, passion and inspiration of our professors who combine their academic approach with practical experience and, last but not least, 4) the power of peers, or the quality of the fellow students and participants. The personal ambition of the student or participant therefore serves as our starting point, supported by applied learning, alongside dedicated professors and fellow students and participants.”

How do you translate this vision into practice?

Steve Muylle: “We work on three axes. The first is AI literacy for students and professors. Our surveys of MBA and Masters students always reveal the same thing: although most of them use AI, they don’t harness its full potential. It is also crucial for them to adopt a critical, responsible and ethical approach to AI, and that they are able to appropriately assess the value of its output. Furthermore, today’s employers also expect the AI literacy of our graduates to be above average.

We are creating a development track for our professors that includes everything from prompting to more advanced applications such as AI agents, with a focus on the critical, responsible and ethical use of AI for learning. We also help them to make their assignments AI-proof. If ChatGPT can do an assignment in two minutes, the assignment is worthless. We have therefore built a tool that checks the extent to which an assignment is AI-proof and makes recommendations if improvement is required.”

“The second axis is the redesign of the leap learning journey itself: how do we integrate AI as a natural part of the learning process? We look at each stage of this journey and ask ourselves: what role can AI play here? Or, just as importantly, when should we not use AI? Take supply chain planning, for example. First, we want students to really understand the models – without relying on AI. Not simply to apply them, but to understand them through and through. Only once they have demonstrated this understanding do we bring in a company with a concrete problem, at which point they are allowed to work with AI. This teaches them how to use AI based on understanding, and not as a shortcut.

To support this axis, we have built an AI Augmented Bloom agent^[1] based on the Bloom taxonomy. Our professors can use this agent to test their course at six learning levels – from remembering and understanding to applying, analysing, evaluating and creating – and determine where AI can be put to meaningful use. Because if you just get AI to carry out every step of the learning process, in the end you won’t really know what you have created.”

1. _{Muylle Steve and José Gerardo Herrera. 2025. Designing AI-augmented Learning: Innovative Teaching Practices Aligned with Bloom’s Taxonomy. Book Chapter (pp. 66-75) in Caporarello Leonardo (Ed.), AI in Education: The Urgency of the Now. Real-world Applications, Challenges, and Lessons for Educators. Amazon Publishing. (ISBN 979-8-2644-8710-1).}

Can you give concrete examples of what this looks like in the programmes?

“Our full-time MBA students participated in a hackathon with NLMK Europe. Our Masters in General Management students were able to use AI and two chatbots for the Goldstein simulation, which we have been organising in collaboration with PwC for several years. Both are examples of how we confront students with a real business problem, in which AI is a tool but not the actual answer. You are expected to apply what you have learned, collaborate with fellow students and manage incomplete or even overwhelming amounts of information in order to further develop your personal insights and skills.”

“In 2025, we also launched the online programme Take the Lead in AI. More than 500 participants registered for this programme, 74% of whom successfully completed it. A strong result for such an intensive programme. Over the course of six modules, participants learn how to apply AI with an impact on aspects such as their productivity, data skills, creativity and decision-making within their specific job context. Making the programme applicable to their daily activities also makes it relevant to the step they want to take. Afterwards, it turned out that participants went much deeper than asked and put in more hours than expected. We felt that was a positive development, as it meant they were genuinely engaged. There was also a LinkedIn learning community where they could share insights. That’s the power of peers in action.”

“The third and final axis is AI learning innovation, or experimenting with new tools and technologies. This doesn’t mean AI innovation purely for the sake of innovation, but experimenting with AI to increase the impact of our pedagogical approach.”

Many executives regard the ethical and legal aspects of AI with a degree of scepticism. How does Vlerick help them with that?

“For us, this question is fundamental but complex. We always say: ‘ethical means doing the right thing’. It might sound simple, but what actually is ‘the right thing’? In Europe, we focus on privacy and autonomy. Other regions have completely differently ideas. I can assure you that when you teach executives from America, Europe and Asia in the same group, it immediately becomes a rich – and at times uncomfortable – discussion.

But Vlerick is a business school, and it is our job to show students and participants the different perspectives, each with their advantages and disadvantages. We get them to think critically, with well-founded insights, about the impact of AI within their ethical, business and legal context and with regard to the step they want to take.”