QA Automation After the AI Transformation: How the Engineer’s Role Is Changing

AI can already generate code, migrate automated tests between languages, build prototypes,identify root causes of problems,and convert test cases into automated test templates.In practice,it changes the QA automation process itself and the engineer's role.

In this talk,I'll share my experience using AI in test automation: migrating end-to-end tests from Java to .NET, rapidly prototyping libraries, generating scenario-based tests, identifying root causes, and developing an internal repository of AI practices for testing and requirements.

I'll show you where AI is useful: in routine conversion, sandbox experiments, documentation,and hypothesis generation.And where it's dangerous: in core architecture, complex logic, final reviews, and decisions made by humans. 

The main focus is how to integrate AI into the engineering process to speed up routine tasks without losing control over quality:through diff metrics, benchmarks, areas of responsibility,and a platform-based approach within the team.