Next-Gen Quality Assurance: Leveraging AI, Automation, and DevOps for Scalable Software Excellence

Abstract

As software delivery accelerates in scope and scale, traditional Quality Assurance (QA) methods are proving insufficient. This review explores the evolution and future of QA through the integration of Artificial Intelligence (AI), automation, and DevOps practices—collectively termed Next-Gen QA. We synthesize findings from key research and industry implementations to highlight how AI-driven test generation, machine learning-based anomaly detection, and continuous testing pipelines have transformed the QA landscape. We also present a conceptual model for scalable QA and validate it through empirical results. The review concludes by outlining future directions, including explainable QA systems, continual learning agents, and QA-AIOps integration. This paper serves as a guide for researchers and practitioners striving to deliver high-quality software at scale.