Adaptive AI Systems with Continuous Human Oversight (AI Governance and Society Journal p-ISSN 3117-6097 and e-ISSN 3117-6100, 2025)
Adaptive AI systems -- systems that modify their behaviour, parameters, or objectives in response to new data, user feedback, or environmental changes -- present distinctive challenges for continuous human oversight: the dynamic nature of adaptation means that the system overseen at deployment may differ substantially from the system in operation weeks or months later. Existing human oversight frameworks are designed primarily for static AI models and do not adequately address the oversight requirements of adaptive systems undergoing continuous learning, model updates, or preference adaptation. This paper proposes the Continuous Oversight Architecture for Adaptive AI (COAAI), a system architecture and governance framework designed to maintain effective human oversight across the full adaptation lifecycle of AI systems. COAAI comprises five architectural components: an Adaptation Monitor that detects and characterises model behaviour changes; a Drift Alert System that classifies adaptation events by oversight significance; a Human Review Gateway that routes significant adaptations through human approval before deployment; an Adaptation Audit Trail that maintains a complete and immutable record of all adaptations; and an Oversight Effectiveness Tracker that continuously assesses whether human oversight is maintaining its intended governance function. COAAI is evaluated through deployment on three production adaptive AI systems in healthcare, financial services, and smart infrastructure over a 12-month period. COAAI deployment achieves a 61.3% reduction in unreviewed significant adaptations (SD = 7.4%), a 43.8% reduction in oversight effectiveness degradation events (SD = 6.1%), and full compliance with EU AI Act Article 9 lifecycle risk management and Article 14 human oversight requirements across all three systems. The study contributes the COAAI architecture specification, an Adaptation Oversight Maturity Model (AOMM), and empirical evidence for continuous oversight as a practical and measurable governance mechanism for adaptive AI.