For both instructors and learners, these tools open up new possibilities. But they also raise an essential question: how can we train students to use AI without delegating their judgment?
The AI competency frameworks published by UNESCO highlight the importance of a human-centered, ethical, and responsible approach. In its article on the AI Competency Framework for Teachers, UNESCO emphasizes that AI transforms the traditional teacher-learner relationship into a teacher-AI-learner dynamic, which requires rethinking the role of teachers and the skills that need to be developed.
This approach places particular emphasis on the central role of humans, inclusivity, critical thinking, and the responsible use of AI in teaching, learning, and assessment.
This is where business simulations become especially meaningful.
Using generative AI to write a report, summarize a document, or propose an analysis is not enough. Students must also learn to question the results produced, identify possible biases, compare multiple scenarios, and justify their choices.
The goal is no longer just to produce a good answer. It is to understand how that answer was built, with which tools, according to which criteria, and with what level of responsibility.
In this context, AI becomes a tool that supports reflection. It can support analysis, but it does not replace human decision-making.
Cesim business games are based on experiential learning: learning by doing, analyzing, and adjusting.
Students are placed in a realistic competitive environment. Working in teams, they manage a virtual company, make strategic decisions, and observe the consequences of their choices throughout the simulation.
In particular, they must:
In this type of serious game, AI can help formulate hypotheses, structure thinking, or compare multiple scenarios. But it cannot take responsibility for the final decision.
With generative AI, written reports and analyses remain useful, but they are no longer always enough to measure real learning.
A text can be well written without fully reflecting the student’s understanding. A recommendation may seem relevant without truly being adapted to the context. An analysis may be well structured while still relying on weak assumptions.
Business simulations make it possible to complement assessment with more concrete elements:
In a business game, decisions do not remain theoretical. They produce visible effects that students must analyze and explain.
One of the risks of AI in education is excessive dependence. If students use AI as a source of authority, they may lose intellectual autonomy.
Business games, by contrast, make it possible to turn AI into an object of critical discussion. An instructor can, for example, ask teams to compare their own analysis with one produced by AI, then identify points of agreement, contradictions, blind spots, or questionable assumptions.
Debriefings then become a central moment. Students explain why they followed, modified, or rejected a recommendation. They connect their decisions to the results obtained and to the theoretical concepts studied.
The question is no longer only: "Did you use AI?". It becomes: "How did you evaluate what AI suggested to you?"
In Cesim business games, artificial intelligence is integrated in a way that supports learning without replacing students’ reasoning.
Cesim AI Coach acts as a support tool that guides teams in their reflection. It can help interpret results, suggest avenues for analysis, or draw attention to certain performance gaps.
Its role is not to provide ready-made decisions or strategies, but to encourage students to structure their reasoning, formulate hypotheses, and deepen their analysis. For this reason, it fully aligns with the approach recommended by UNESCO: a human-centered use of AI that strengthens the capacity for judgment rather than replacing it.
The arrival of AI does not reduce the value of business games and serious games. It reinforces it.
The more powerful AI tools become, the more important it is to train students in what AI cannot do for them: make decisions under uncertainty, take ownership of a strategy, collaborate with a team, learn from mistakes, and exercise judgment.
Cesim business simulations offer a particularly relevant framework for developing these skills, especially when they are deployed with Cesim AI Coach. They make it possible to connect concepts, decisions, results, and critical reflection in a realistic, risk-free environment.
In the age of AI, the central question is no longer only: "What can they produce?". It becomes: "How do they make decisions, with which tools, according to which criteria, and with what level of responsibility?"
This is precisely the skill that Cesim business games and Cesim AI Coach make possible to develop in depth.