Adoption of AI, data platforms and digital technology is inevitable. The key question is whether organizations can trust what ...

Most widely cited AI coding benchmarks, including the original SWE-bench, were built primarily around Python repositories, meaning headline performance results may not accurately predict how coding ag ...

Enterprise data masking tools help organizations protect sensitive data while still making it usable for testing, analytics, ...

A comparison of eight AI-powered requirements management platforms for 2026, from NLP-based quality analysis and automated test generation to live traceability scoring, covering Jama Connect, IBM ...

The AI revolution is significantly outpacing the IC industry’s ability to sufficiently test multi-chip systems for all necessary failure mechanisms at probe, final test, and system-level test. The ...

Abstract: With the rise of autonomous systems (AS) and agentic artificial intelligence (AI), a heightened automation of testing processes is required to build, deploy, or repair reliable intelligent ...

Abstract: The growing complexity of software systems and the need for more rapid, high-quality software releases have created the need for intelligent and automated testing mechanisms. Drawing on ...

This commentary was originally published in Fortune. The views expressed are the author’s own. Two inconsistent phenomena seemingly can be true at the same time: AI is seen as disrupting jobs, and, ...