WHITEPAPER

AI in Software Testing

What’s Real, what’s Next, and what’s Speculative

The rise of AI-powered testing tools has left QA teams bombarded with bold promises. Vendors claim their solutions can replace testers, automate everything, or discover bugs with little oversight. But for anyone working in quality engineering, the reality is far more nuanced. Some AI features are already delivering real efficiency gains, while others remain immature or unrealistic.

This whitepaper provides a practical framework for evaluating AI in testing today. We break down what’s proven in production — such as automated test generation and log anomaly detection — what’s still evolving in labs, and what’s largely speculative. By understanding these distinctions, technical QA leaders can invest in the right capabilities without falling into the hype cycle.

Written for testers, QA managers, and engineering leaders who value substance over marketing, this paper helps you separate fact from fiction in the AI testing landscape.

Cut through the hype. Deliver real quality.

With Qase, QA professionals get  solutions that strengthen test coverage, reduce flakiness, and speed up release cycles.

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