An overview of how organizations are using artificial intelligence to move from reactive testing to proactive quality engineering—reducing costs, accelerating releases, and improving reliability. Topics include automating and optimizing test design for higher coverage, predicting defects and focusing testing where it matters, enabling intelligent test automation with self-healing scripts, continuously monitoring quality across CI/CD pipelines, and generating realistic, privacy‑compliant test data. Expected outcomes discussed include reducing total cost of quality by up to 25% and accelerating release cycles by 20%.