Title: SCENARIO PLANNING WITH AGENTIC AI FOR REINFORCEMENT LEARNING AND RISK MITIGATION IN DEVELOPING ECONOMIES BUSINESS EDUCATION
Authors:
Kevin Fleary and Keyon Thomas
Abstract:
Problem: Business leaders in developing economies face significant challenges due to volatile environments, supply chain shocks, and institutional voids, leading to suboptimal decision-making and a critical need for adaptive pedagogical tools.
Approach: This study employs a Design-Based Research approach, utilizing the “Captains of Industry” simulation, an AI-augmented experiential learning framework that integrates Product Service System theory and Design Thinking. The simulation generates bespoke scenarios and provides AI-driven feedback for reinforcement learning.
Objectives: To analyze the impact of AI-driven simulations on cognitive problem-solving skills, risk appetite, and standardized decision-making; evaluate the AI agent’s effectiveness in enhancing student performance; detail the simulation’s design and implementation; and elaborate on the role of bespoke scenario design and localized data.
Findings: The simulation effectively enhances decision-making capabilities and risk mitigation strategies. Analysis of 125 students revealed a mean performance of 59.3% and significant heterogeneity in learning trajectories (4.7-4.8% mean growth rate, but varied individual improvements/declines). Diffusion Maps identified non-linear geometric patterns and “micro-clusters” in student performance, while Kernel Two-Sample Tests statistically confirmed “separable achievement profiles” between top and bottom performers.
Implications: The framework provides a dynamic laboratory for developing adaptive decision-making and risk mitigation skills in complex environments. It offers a scalable solution for in-company training, addresses data scarcity in developing regions, and frees human instructors for higher-level mentorship.
Keywords: Agentic AI Simulation, Scenario Planning, Reinforcement Learning, Risk Mitigation, Developing Economies.
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