Title:
AI-Driven Oversight in Multi-Sector Governance Systems: A Cross-Domain Analysis of Adaptive AI-Enabled Governance

Authors:
Dr. Robb Shawe, USA

Abstract:

Artificial intelligence (AI) is rapidly transforming governance systems across sectors, yet most institutions continue to rely on oversight models designed for pre‑digital environments. As AI becomes embedded in cyber‑physical systems, organizational decision processes, and regulatory infrastructures, governance must evolve from static compliance to adaptive, intelligence‑augmented oversight. This manuscript introduces the AI‑Enabled Governance Oversight Model (AIGOM). This layered decision-support intelligence architecture integrates AI-driven sensing, operational observability, analytics, and adaptive decision-support into governance systems while preserving human accountability, governance interpretation, and ethical control. The model demonstrates how AI can serve as a governance augmentation layer, generating decision-support intelligence, accelerating operational awareness, enhancing adaptive oversight, and supporting real-time governance recalibration. AIGOM extends the Adaptive Governance Systems Framework (AGSF) by specifying how AI capabilities interface with governance processes across diverse sectors, including critical infrastructure, healthcare, finance, and public administration. This manuscript establishes a theoretical and operational foundation for AI-enabled governance across complex socio-technical environments.

DOI: http://dx.doi.org/10.51505/ijaemr.2026.11324