Citation :

Beng Ee Lim, Mert Zamir, 2025. "AI for Regulated Domains: Bridging Compliance, Explainability, and Trust" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 3, Issue 4: 13-16.

Abstract :

Artificial intelligence is increasingly used to support complex decision workflows, yet its adoption in regulated industries remains limited. Medical device regulation, pharmaceutical oversight, aviation safety, and financial governance all rely on strict documentation, traceable reasoning, and verifiable evidence. Current large language models struggle to meet these requirements because they do not natively provide citations, cannot guarantee consistency, and lack the mechanisms needed for repeatable reasoning. This paper outlines the core challenges of applying AI in tightly regulated domains, identifies the gaps in current AI-assisted workflows, and proposes a practical agentic framework that emphasizes explainability, traceability, and trust. The goal is to show how AI can enhance compliance work without undermining regulatory integrity.

Keywords :

Artificial Intelligence, Regulated Domains, Explainable AI (XAI),Trustworthy AI, Agentic AI, Regulatory Compliance, Auditability and Traceability.