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, ...

Leapwork recently released new research showing that while confidence in AI-driven software testing is growing rapidly, accuracy, stability, and ongoing manual effort remain decisive factors in how ...

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

Times are changing fast. Take the automotive industry for example. Software has evolved far beyond infotainment, now controlling everything in the car, including braking and steering for the driver.

Identify sources of unnecessary cognitive load and apply strategies to focus on meaningful analysis and exploration.

When evaluating AI for testing, prioritize approaches that keep teams in control and maintain end-to-end testing connectivity ...

While thorough testing and quality assurance checks have always been important steps in the software release and updating processes, they’re taking on a new and higher significance in an ...