Enhancing cybersecurity through adaptive networks and AI-coaching: Organizational learning and risk management

This article presents an adaptive network-oriented modeling approach incorporating an AI-coach to support cybersecurity teams in organizational learning and risk management scenarios. Four distinct scenarios within a hypothetical smart energy company were simulated, progressively introducing complexity through factors such as stress, incomplete knowledge, and team dynamics. By integrating second-order adaptive mechanisms and AI-driven coaching, the models reveal critical insights into how cognitive and social factors influence cybersecurity outcomes. A systematic What-If and risk assessment analysis further demonstrates the robustness and sensitivity of team performance under varying conditions. The findings underscore the importance of shared mental models, AI-enhanced knowledge retention, and collaborative dynamics in successfully addressing complex cybersecurity threats.