AI-Driven Quality Engineering for Regulated Enterprise Systems

A Framework for Reliability, Validation, and Operational Trust in High-Stakes Digital Environments Abstract Artificial Intelligence is reshaping enterprise software engineering, particularly in regulated sectors such as healthcare, insurance, financial services, public workforce systems, and digital commerce. As organizations increasingly integrate Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), and Large Language Models (LLMs) into mission-critical business applications, conventional quality assurance and software testing approaches are no longer sufficient to address the reliability, fairness, explainability, and governance challenges of these systems. AI-enabled applications introduce probabilistic behavior, dynamic model drift, data dependency risks, hallucinated outputs, bias propagation, and new forms of operational uncertainty that require a modernized quality engineering discipline. This paper proposes a framework for AI-driven quality engineering ta