Understand why testing must evolve beyond deterministic checks to assess fairness, accountability, resilience and ...

Artificial intelligence (AI) models are being applied to almost everything, from helping people write emails to ...

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 ...

Conversational AI is gaining attention as enterprises look beyond CRMs to spot hesitation risk and momentum before forecasts ...

(Reuters) -Drug developers are increasing adoption of AI technologies for discovery and safety testing to get faster and cheaper results, in line with an FDA push to reduce animal testing in the near ...

Recently, one of our clients stated that their web content accessibility guidelines (WCAG) were met, but users with disabilities were still unable to use their AI-native chatbot. When my team examined ...

What if the very process meant to ensure your AI applications work flawlessly is actually holding you back? Manual testing, once the backbone of quality assurance, is now a bottleneck in the ...

The purpose of generative AI is to generate the most statistically likely output. In human terms, that means mediocrity at scale, not diversity, says Paul Armstrong Corporate diversity has turned into ...

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 ...

Testing APIs and applications was challenging in the early devops days. As teams sought to advance their CI/CD pipelines and support continuous deployment, test automation platforms gained popularity, ...