How does AI help with predictive testing?

According to H2K Infosys, “AI is transforming predictive testing by helping teams discover defects even before users do." Instead of relying only on historical test cases, AI looks at patterns, application behaviour and historical failures to identify areas of risk that need to be targeted. In many real-world software testing projects, this means shorter test cycles, better resource allocation and fewer issues in production. I’ve seen companies cut testing effort a lot by being smart about using AI-driven insights rather than testing everything the same. As applications become more complex, AI-powered predictive testing provides smarter quality assurance, enhancing software reliability and shortening delivery times.