AI can speed up testing, but if you trust it too much, you might ship bugs faster than ever — with no one clearly accountable.

Testing places unique demands on AI. Errors carry real business risk, and fragile tests or slow updates can quickly erode trust in results. As a result, while momentum around AI in testing is strong, ...

When LambdaTest was founded, the problem it set out to solve was far more contained but with the rise of AI-generated code ...

From generating test cases and transforming test data to accelerating planning and improving developer communication, AI is having a profound impact on software testing. The integration of artificial ...

Agentic artificial intelligence is the new belle of the software ball. C-level executives want their companies to use AI agents to move faster, therefore driving vendors to deliver AI agent-driven ...

Generative AI (GenAI) isn’t just changing how code is written; it’s reshaping how we define software quality. As AI tools become more embedded in software development workflows, the role of quality ...

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Strong quality cultures analyze this historical execution data to identify flaky tests, unstable code sections and deployment patterns that correlate with incidents. Machine learning algorithms can ...

BrowserStack today released its State of AI in Software Testing 2026 report, showing how AI has become central to modern testing, while highlighting the practical gaps that slow adoption. Based on ...