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, ...

Generative AI automation targets coding, debugging, documentation, and testing workflows in SDLC processes SAN JOSE, ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

AI is becoming a strategic differentiator in industrial automation; those who learn to apply it effectively will shape the next generation of industrial projects.

In an age where software drives nearly every aspect of daily life, ensuring its quality at scale has never been more essential. In 2024 alone, global IT spent over $5.1 trillion in expenditures, and ...

New platform helps non-technical founders and teams implement AI inside real business workflows without hiring ...

Quality engineering must evolve faster than code; otherwise, agentic AI will move quickly, learn rapidly and fail expensively.

The approach toward software testing has drastically changed over the years. It has changed from manual testing to automation frameworks and now to AI-based testing. It isn’t just about increasing ...

Most testing strategies collapse under the weight of modern software development demands. But speed requirements continue to increase while application complexity grows, which creates an impossible ...

China’s push toward large-scale automation is entering a new phase as a major robotics player rolls out a high-profile test ...