AI testing

The rise of artificial intelligence has redefined the boundaries of software testing. Whether you are testing AI models for bias and accuracy or using generative AI to automate your test suites, staying updated is crucial. Here, we explore the intersection of AI and QA, covering everything from MLOps validation to advanced AI-powered testing tools that help teams achieve unprecedented scale and efficiency in 2026.

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Test Automation Reporting
AI testingInsightsreviewtesting tool
Test Automation Reporting: Best Tools, Features, and Practices in 2026
Software testing is a mission-critical element of the SDLC where the newly created product undergoes an out-and-out check of its security, performance, usability, and other functional and non-functional aspects. Given the multitude of software quality parameters that need to be validated and the overwhelming number of test cases to be executed, manual testing of the […]
Mykhailo Poliarush
Mykhailo Poliarush
AI-cover
AI testingInsights
AI Prompt Testing Methods: How to Build Reliable QA Workflows
In our previous article on the topic “ChatGPT vs. AI Test Management Platforms”, we explored the fundamental differences between using general-purpose AI assistants like ChatGPT versus AI-native QA management systems like Testomat.io. While LLMs offer remarkable flexibility, they often fall short when applied to structured, domain-heavy use cases like software testing. A key challenge we […]
Vitaliy Mikhailyuk
Vitaliy Mikhailyuk
ChatGPT vs. AI Test Management Platforms
AI testingInsights
ChatGPT vs. AI Test Management Platforms: What’s Better for QA Documentation Analysis?
Modern software quality assurance (QA) processes demand speed, accuracy, and consistency. With the introduction of generative AI technologies such as ChatGPT, the potential for automating and enhancing QA tasks has grown exponentially. However, while ChatGPT and similar AI assistants offer general-purpose intelligence, specialized test management systems provide domain-specific solutions with deeply integrated AI workflows.
Vitaliy Mikhailyuk
Vitaliy Mikhailyuk
AI testingautomation testingtesting guides
Marcus Merrell – How to Keep Your Productivity Up Despite AI
Artificial intelligence tools offer promising support, but they also introduce new complexities. Balancing realistic expectations with effective AI integration requires careful management to protect workflow and enhance output without falling prey to overhyped solutions. Key Takeaways Frequent interruptions significantly reduce focused coding time. Managing evolving priorities contributes strongly to cognitive overload. Effective use of AI […]
Solomia Krutenko
Solomia Krutenko
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Switch to Testomat.io now and transform your testing process into a faster

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