From AI Alerts to Accountable Decisions: A Governance Framework for Regulatory Compliance

Abstract

Artificial intelligence (AI) is increasingly used to manage regulatory and ethical compliance obligations. This paper examines AI’s role in regulatory compliance with particular attention to human oversight, accountability, transparency, employee competency, and organizational governance. It builds on existing scholarship on AI governance, regulatory technology, compliance risk identification, human oversight, and organizational AI readiness. It argues that increased reliance on AI can create an accountability gap when organizations lack effective human oversight and clearly defined responsibility. The paper also incorporates findings from a recent practitioner survey the author conducted. The survey findings reveal that human oversight, AI accuracy, and reliability are the top challenges to AI’s use for compliance. Respondents also identified privacy and data security, employee knowledge and training, unclear processes, and integration with existing systems as significant concerns. Building on existing literature and the survey findings, the paper proposes the STAGE framework (Scan, Triage, Assess, Govern, and Evaluate) as a practical approach to maintaining human judgment and organizational accountability when integrating AI into regulatory compliance. STAGE does not treat AI as an independent decision-maker. Instead, it positions AI as a support tool that requires constant human verification and clear escalation paths. The framework focuses on whether organizations can use AI to identify risks while keeping qualified people responsible for interpreting alerts, making decisions, documenting actions, and correcting weaknesses.