Guides
Guides to AI testing
Practical guides for testers, developers, and teams who want better software quality. Understand your options and decide where to start.
- Guide
- Describe intent
- AI executes
- Review results
What is AI testing?
AI testing is the use of AI to create, run and maintain software tests, often from a plain-English description. What it covers and where it still fails.
- Guide
- Team constraints
- Shortlist tools
- Try a real flow
The best AI testing tools in 2026
26 AI testing tools, sorted by what each one needs from you — including Tricentis Tosca, ACCELQ, Leapwork, Checksum, Eggplant, Perfecto and Sauce Labs.
- Guide
- Starting state
- Specific actions
- Expected result
Natural language test automation
Writing automated tests in plain English instead of code: how its two generations differ, how to write a description that works, and where it breaks.
- Guide
- Interface changes
- Find the element
- Verify the outcome
Self-healing test automation
Self-healing repairs test locators when the UI changes. How it works, why it solves only half the problem, and the failure mode nobody selling it mentions.
- Guide
- Critical flows
- Run before release
- Assign an owner
Regression testing without a QA team
How to get a working regression suite when nobody’s job is testing: which flows first, how many tests you need, when to run them, and who owns the result.
- Guide
- Agree on criteria
- Test the delivery
- Accept or report
Acceptance testing software built by a supplier
You had software built by an agency or contractor. How to verify it does what you paid for without source code, engineers or the supplier’s word for it.