Beyond AI-Generated Answers: How Business Simulations Bring Crisis Management Learning to Life

Insights from a RealGame interview with Professor Daniel Chicksand, Professor of Operations and Supply Chain Management at Birmingham Business School, UK.

If AI can write the answer, what should students do instead?

As generative AI becomes part of everyday higher education, business educators face a growing challenge. If students can ask AI to analyse a case study, identify key issues, and recommend solutions in seconds, where does meaningful learning happen?

For Professor Daniel Chicksand, the answer isn't to avoid AI, but to create learning experiences that require what AI cannot replace: judgment, communication, collaboration, and decision-making under pressure.

In a recent RealGame webinar, Daniel shared how he adapted a business simulation to teach crisis management and resilience, moving students beyond analysing past events to experiencing a crisis as it unfolds.

Moving Beyond the Case Study

When Daniel joined a Master's module in Crisis Resilience and Change Management, he wanted students to do more than discuss what organisations should have done after a crisis had already happened.

Traditional case studies remain valuable, but they often allow students to reflect with the benefit of hindsight. Real crises rarely offer that luxury. Leaders must act with incomplete information, conflicting priorities and considerable uncertainty. Daniel's goal was simple: instead of analysing somebody else's crisis, students should experience one themselves. Having already used RealGame in operations and supply chain management teaching, he recognised that the simulation could provide a realistic organisational environment in which a crisis could emerge and develop.

The challenge was not the technology itself. The challenge was designing an experience that would help students practise leadership, communication and collective problem-solving.

Turning a Business Simulation into a Crisis

The learning experience unfolded across three seminars. The first session familiarised students with the business environment and assigned organisational roles such as procurement, operations, and leadership. Students learned how their functions interacted and how decisions in one area affected performance elsewhere. The second session introduced the crisis.

A supply disruption interrupted production and quickly created problems across the organisation. Production struggled to meet demand, procurement faced mounting pressure, and customer-facing teams encountered growing dissatisfaction. At this point, Daniel deliberately moved beyond the simulation itself. 

Different participants received different pieces of information on paper to complement the digital learning with pen-and-paper activities. Some were given customer complaints. Others received warnings of potential legal consequences. Information was incomplete and, in some cases, contradictory. No individual had a complete picture of what was happening. To understand the situation, students had to talk to one another, challenge assumptions and piece together a shared understanding before agreeing on a response.

They also had to consider how to communicate with customers, suppliers, and internal stakeholders as the situation evolved. The final session focused on recovery and reflection. Students reviewed their decisions, evaluated the effectiveness of their leadership and communication, and linked their experiences to academic frameworks such as Mitroff's five-stage crisis model.

Learning Through Consequences

One strength of the approach was that students could see the consequences of decisions unfold in real time.

Rather than reading about the impact of a supply disruption, they observed how operational problems affected performance across an interconnected organisation. They had to manage the crisis rather than merely discuss it. However, Daniel's objectives extended beyond operational outcomes.

He was equally interested in how students behaved as managers. How did they respond to uncertainty? Which information did they trust? How effectively did they communicate? How did they make decisions when no one had all the answers? Throughout the exercise, Daniel deliberately stepped back, letting students lead discussions and determine their own responses. According to Daniel, students found the experience engaging, realistic, and relevant to the kinds of challenges organisations face in practice.

Designing Learning for the AI Era

Perhaps the most interesting part of the discussion concerned AI.

Daniel noted that students can now use AI tools to generate convincing responses to many traditional academic tasks. A well-crafted prompt can often produce a plausible case analysis without requiring deep engagement with the underlying problem. The simulation created a very different learning situation.

Students operated in a live, evolving environment where circumstances changed, information was incomplete, and no single answer was correct. Success depended on how effectively they interpreted events, communicated with others and adapted as the situation developed. Daniel also encouraged activities off-screen. During crisis discussions, students used paper, whiteboards and face-to-face conversations to organise information and develop responses.

The emphasis shifted from producing an answer to engaging in the problem-solving process. Importantly, Daniel did not argue that business education should exclude AI. AI can support reflection, analysis and communication tasks. His point was different: educators need learning experiences where active participation, human judgment and collaboration remain essential.

Lessons for Educators

Daniel's experience offers several practical lessons for educators exploring simulation-based learning.

First, start with the learning outcomes rather than the technology. The simulation should support what students need to understand, practise or experience. Second, complexity does not require an elaborate scenario. Much of the realism emerged naturally from different organisational responsibilities, competing priorities and incomplete information. Third, some of the most valuable learning happened when the simulation paused, and students talked. Structured discussions, leadership meetings and debriefing sessions helped turn events into learning.

More Than a Simulation

Daniel's experience highlights an important principle for business education in the age of AI. Technology alone does not create meaningful learning. What matters is how educators design experiences that require students to think, communicate, collaborate and make decisions for themselves.

For Daniel, RealGame provided an environment where students could experience the uncertainty and ambiguity of a developing crisis. For students, it created an opportunity to practise leadership and decision-making rather than discuss them. As universities continue to explore the opportunities and challenges AI creates, experiences like these suggest that some of the most valuable learning may come not from generating better answers, but from putting students in situations where they must work together to discover them.

Explore the Full Conversation

This article is based on RealGame's webinar, Beyond AI-Generated Answers: Designing Active Learning with Business Simulations, featuring Professor Daniel Chicksand of Birmingham Business School.

Watch the full webinar recording to explore Daniel's teaching experience and the discussion on active learning, crisis management, and business simulations.