Toward a Governance Maturity Model (GMM): A Capability-Based Framework for Adaptive, AI-Enabled Governance Systems

Abstract

Governance systems across sectors vary widely in their ability to integrate artificial intelligence, real-time monitoring, and adaptive oversight. While advanced organizations increasingly rely on continuous sensing, data-driven decision-support, and event-validated learning, many institutions remain anchored in reactive, compliance-centric governance models. This manuscript introduces the Governance Maturity Model (GMM), a five-level capability framework that evaluates an organization's readiness to implement adaptive, AI-enabled governance systems. The GMM extends the Adaptive Governance Systems Framework (AGSF) and the AI-Enabled Governance Oversight Model (AIGOM) by defining progressive stages of governance capability—from reactive oversight to fully adaptive, intelligence-augmented governance ecosystems. The GMM further establishes governance maturity as a dynamic institutional capability involving governance observability, operational intelligence integration, adaptive recalibration, and crossdomain governance coordination within complex socio-technical environments. The model provides a structured pathway for organizations seeking to modernize governance practices, strengthen accountability, and align oversight mechanisms with the demands of complex, dynamic risk environments.