How does AI/ML turn software testing from reactive to predictive?

I’m looking to understand how AI/ML tools are being practically applied in enterprise software testing to predict issues before they occur. What models or techniques are commonly used? And how do they integrate with existing QA workflows or DevOps pipelines?