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

Authors:
Dr. Robb Shawe, USA

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 cross-domain 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.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11325