How does AI help in requirement analysis for testing?

H2K Infosys explains how AI is changing requirement analysis for testing in ways that honestly felt impossible a few years ago. Instead of testers spending endless hours reviewing documents line by line, AI tools now identify gaps, unclear requirements, and possible risk areas much faster. In many modern QA projects, teams use AI in software testing to trace dependencies, predict defect-prone modules, and improve test coverage before development even starts. I’ve seen companies reduce rework simply because AI-driven requirement analysis catches inconsistencies early. With the growing demand for intelligent automation testing and smarter QA strategies, AI is becoming less of a “future trend” and more of a daily testing companion.