Automation Meets Accuracy: A Deep Dive into AI for Quality Assurance

Abstract

This review discusses the transformative quality assurance (QA) of the Artificial Intelligence (AI) through the lens of the way intelligent technologies can make industries more precise, efficient, and decision-making. With a combination of machine learning, computer vision, as well as predictive analytics, AI-powered QA systems transition to proactive quality control as opposed to reactive inspection. The paper explains the history of QA, fundamental AI technologies, industry applications, advantages and the challenges related to it. It also describes the future trends that focus on explainable AI, human-machine cooperation, and real-time monitoring. All in all, the research highlights how AI has the potential to transform the quality systems to make them accurate, consistent, and continuously improved in contemporary industries.