How Generative AI, Lifecycle Intelligence, and Risk-Based Testing Are Redefining Quality Engineering?
Quality assurance is changing faster than most teams realize. The old playbook, counting test cases and chasing coverage metrics, no longer tells us anything useful about quality. You can have thousands of automated tests and still miss the one bug that brings production to a halt.
Here’s the thing: you don’t need more testing. You need smarter testing.
Generative AI and Large Language Models (LLMs) are giving QA something it’s never had before: context. They can understand requirements, analyze code changes, and connect testing back to business impact. Instead of asking, “Did we test everything?” the real question becomes, “Are we testing what matters most?”
This whitepaper unpacks what it means to become an AI-native QA organization, one that uses intelligence, not volume, to ensure quality. You’ll learn how:
