ESCP Treats AI as Structural Change, Not a Curriculum Update
Business schools are no longer debating whether to teach AI. They're rethinking how they operate around it. At ESCP Business School, the shift extends beyond adding courses-it touches teaching methods, assessment practices, research, and institutional operations.
Louis-David Benyayer, who leads this work at ESCP, frames the shift as "strategic." The school has invested in tools, training, and internal transformation across the entire institution rather than isolating AI initiatives in a single department.
The Job Market Demands It
AI is reorganizing functions across industries. HR, marketing, and finance roles are being reshaped by the technology. Business schools must prepare students not just to understand AI itself, but to grasp its implications for non-technical roles where they'll actually work.
Yet the pressure goes deeper. Generative AI is forcing schools to rethink how they teach and assess students. "We can no longer teach the same way, nor assess the same way," Benyayer said.
The 1,000 Champions Experiment
Rather than imposing a top-down strategy, ESCP launched the AI 1000 Champions programme in September 2024. One thousand participants-roughly 10% of the school community-received full access to AI tools and a year to experiment.
The result: 150 to 200 documented experiments across the school's multi-campus, multi-programme environment. Faculty built bots representing historical figures to conduct realistic negotiations and interviews. Students took teaching roles, sharing their own approaches to generative AI and LLM with peers.
The focus wasn't on polished outputs. "We don't care about the result," Benyayer said. "We care about the process." The programme revealed a key insight: in rapidly evolving technical contexts, knowledge is often distributed, not hierarchical.
Assessment in an AI Era
ESCP developed frameworks to rethink evaluation when AI is ubiquitous. This includes revising student guidelines and addressing complex questions about AI's role in thesis work. The process remains unfinished.
"It's not super easy," Benyayer admitted. "We combine several approaches-and we are still learning."
Governance and Trade-Offs
Early debates framed AI as simply beneficial or harmful. That's shifting. "The questions are no longer yes or no," Benyayer said. "They are about trade-offs."
Two issues dominate: governance and sustainability. Who decides how AI tools are used? At what institutional, national, or global level? As AI systems become more influential, questions of control and accountability sharpen.
Sustainability adds another pressure. AI requires significant computational resources. As adoption scales, energy consumption and environmental impact become harder to ignore.
Global Collaboration Is Necessary
Business schools operate within a global ecosystem shaped by international students, faculty, accreditation bodies, and rankings. No single institution can solve these questions alone.
"We don't have any other choice than collaborating at a global scale," Benyayer said. Different organizations will take different paths. Some will make AI central; others will limit its role. What matters is that the decision is deliberate.
ESCP's approach combines ambition with realism. It's not a finished model, but an evolving process built on experimentation and collaboration. For educators willing to engage with this change, the work ahead involves more than adaptation. It requires rethinking what learning itself should be.
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