Abstract for: Cultivating Collective Intelligence in Cyber Risk Governance: An Enterprise Architectural Approach

Cyber risk governance has become increasingly complex due to fragmented data, rapid technological change, and growing cognitive demands on decision-makers. Evidence shows that executives often make suboptimal cyber-risk investment decisions, resulting in either excessive spending or insufficient protection. System dynamics (SD) provides a framework for analyzing such environments by modeling feedback structures, delays, and nonlinear interactions that shape cyber risk exposure and resilience. This study aims to strengthen cyber risk governance by augmenting human cognition through a collective intelligence architecture integrating artificial intelligence with SD-based simulation. Using a design science approach, architecture is validated through three proof-of-concept (PoC) implementations focusing on multi-agent decision-making, multi agent approach to data consolidation, and knowledge-based reasoning. Each proof-of-concept provide insights in both implementation and lessons learned. Findings suggest that integrating AI with system dynamics enhances cyber risk governance by improving information integration, supporting consistent strategic decision-making, and augmenting human cognition, while introducing new challenges related to governance, validation, and model transparency. Reviewing and strengthening self written text. Search for literature.