Explainable AI as a Tool for Regulatory Compliance and AI Accountability

Abstract

As Artificial Intelligence increasingly drives critical decisions across sectors such as finance, healthcare, governance, and insurance, regulatory compliance and accountability have become central ethical and legal imperatives. Explainable Artificial Intelligence (XAI) offers a framework to make AI decision-making transparent, auditable, and accountable, thereby supporting compliance with emerging AI regulations and standards. This paper explores how explainable AI can serve as a tool for regulatory compliance and AI accountability. It examines regulatory frameworks, the role of explainability in demonstrating legal and ethical conformity, domain-specific use cases, and challenges in operationalizing XAI for oversight purposes. A structured framework is proposed to integrate explainability into compliance workflows, enabling organizations to meet regulatory obligations while maintaining ethical responsibility. The study concludes that explainable AI is not merely a technical enhancement but a foundational component of accountable AI governance.

Keywords: Explainable AI, Regulatory Compliance, AI Accountability, Auditable AI, Ethical AI