Michelle Sisto: "While we need to understand AI and incorporate it into business strategies, usage must be human centric and value-driven"

• This interview was originally published in EDHEC Vox Magazine No. 16, dedicated to artificial intelligence.

What inspired the creation of the AI Centre, and what was your vision behind it?

In the fall of 2022, when ChatGPT really came onto the public scene, I was immediately interested. It was my last year as associate dean of graduate programs, and I had already informed leadership that I was ready to start something new at the end of my mandate. A meeting in early December 2022 with EDHEC alumnus Michel Guillemot further cemented my desire to create new AI-centric and AI-infused programmes at EDHEC. Michel, a founder of Ubisoft, is forward thinking, and his vision of the future has contributed to shaping mine. My background is in math and computer science. Back in 1988, I was studying expert systems, an early approach to AI, so I was simultaneously amazed by and concerned about the progress in AI since then.

With the support of Emmanuel Métais, we decided that at the end of my term as Programme Grande Ecole and Masters director, I would devote myself to an AI project at EDHEC. During the 2023-2024 academic year, I was able to step back and delve into the new technology of generative AI, deepen my knowledge, create and test AI assistants in my courses, and build convictions and concrete ideas for integrating AI into EDHEC’s programmes. All this analysis led us to the decision to build an AI Centre, focusing on its impact on teaching, research and the business world.

Could you describe the core purpose and organisational structure of the AI Centre?

I’m beginning to put together a team whose missions will focus on three pillars: integrating AI into all EDHEC programmes, from the bachelor’s to the PhD; conducting research on AI’s impact on the transformation of professions; and focusing on outreach, community building and thought leadership within and beyond the school.

How would you characterise EDHEC’s approach to AI integration?

As an institution, EDHEC is also concerned about ensuring higher education maintains its value. Hence it is a founding member of the Responsible AI Consortium, together with Luiss Business School in Rome, Imperial College Business School in London, and QS. This consortium is structured around four categories of action: teaching, learning and assessment; sharing and conducting joint research projects; governance; and human-centric AI ethics. Underlying these activities is the development of a roadmap for institutional integration of AI and metrics to gauge progress, driven by the idea that business schools will be better and learn faster if we work together.

We emphasise that while we need to understand AI and incorporate it into business strategies, usage must be human centric and value-driven, positioning ourselves not solely on tools, but rather on why and when we should use them and when we shouldn’t and on how usage may impact learning and human interaction.

How have students embraced AI technologies in their academic work, and what patterns have you observed in their usage?

The students are all using AI. In the lectures I’ve given, almost 100% use AI, and at least 60-70% use it every day. However, they don’t necessarily use it in a way that effectively promotes their learning. This is where we have an essential role to play.

How do you guide students in their AI journey?

We take a proactive approach in our courses and programmes. For example, in our Global MBA programmes, we begin the year with an AI boot camp. We start with the history of AI, the definition of generative AI and how it will impact students’ future jobs and ethical and legal considerations. We then cover the basics of prompting, using a variety of models. We encourage them to engage their cognitive abilities by prompting systems to get multiple approaches to a problem, so as not to limit their thinking.

What unique challenges do students in business schools face when developing meaningful AI competencies?

The biggest challenge is that they are geared toward productivity and the mindset that “time is money.” Students have so many competing demands on their time — association activities, interviews, academic work… Our natural human tendency is to think, “If I get this done quickly, I can use that time for something else.” But “quickly” and “effectively” aren’t the same thing. Getting them to invest time, not just in creating a final product but in using AI to enhance their learning and significantly improve their output, is challenging.

The MBA curriculum includes significant technical AI components, including coding. How do you balance developing technical literacy with broader leadership competencies?

The AI Innovation track of EDHEC’s Global MBA programmes complements the core programme. In the core, students develop a strategic view of AI business strategy, but to understand implementation, they need to delve deeper into the details. That’s why they’re learning Python coding.

Another reason is that algorithmic thinking is becoming an essential element in a leader’s portfolio of competencies, in addition to more classical core MBA elements of ethical thinking, critical thinking and strategic thinking.

Nevertheless, we’re not aiming to produce engineers. A recent BCG study on leadership showed that about 10% of resources should be allocated to algorithms, 20% to data structuring, and 70% to people and processes. Our curriculum allocation is similar; only 10-20% is technical, while the rest focuses on people and processes, including classical leadership requirements.

How do you integrate ethical considerations into your AI curriculum?

Ethics is an essential element. Currently, to gauge their own usage, we encourage students to follow the LEAD framework, developed by the Digital Education Council:

• L for Learning: “Did I actually engage with this material? Have I learned something, or did I just summarise it with AI without improving my knowledge?”
• E for Ethics: “Would I feel comfortable sharing with my professor, boss or client how I used AI for this task?”
• A for Accuracy: “Have I checked every source I’m citing? Have I gone beyond sources provided by Gen AI?”
• D for Development: “Have I grown from this work? Have I developed myself in some way?”

How are you preparing students for an AI-transformed job market?

We are convinced that the business industry still needs experts to converse effectively with AIs. We encourage students to develop expertise in their fields because experts can identify where AI results fall short.

Beyond automation, what transformative business opportunities does AI enable that weren’t previously possible?

For example, in education, when teaching a heterogeneous MBA class with students from marketing, finance and human resources backgrounds, AI allows you to create exercises tailored to each student’s field of interest, facilitating quicker engagement. Similarly, when dealing with customers or internal stakeholders, AI enables a level of personalisation that’s impossible with standardised approaches. These are just initial first-use cases.

How will leadership roles evolve as AI becomes further integrated into organisations over the next decade?

I believe we’ll end up managing people, machines and human machine ecosystems. More robots and inanimate machines will be integrated into our everyday lives, as is already the case in places like Japan, where robots commonly work in hotels and restaurants. Leaders will need to understand how AI functions and which types of problems can be addressed by AI, as well as be able to prioritise valueadding solutions.

More importantly, they need to understand what drives people and how to keep people engaged, fulfilled and learning, all while leveraging the integration of AI into the workplace or workflows. There are enormous challenges and opportunities ahead, and AI will continue to improve and accelerate, so curiosity, adaptability and resilience will remain key leadership qualities.