5. Katalon AI Assistant – AI Support Across Testing Activities
Katalon provides AI-assisted capabilities for test design, automation, and test analysis. Available features depend on the Katalon product, configuration, and subscription.
It can help teams reduce repetitive work and organize different testing activities.
How QA engineers can use Katalon AI Assistant:
- Refine requirements.
- Generate initial test cases and test steps.
- Assist with automation scripts.
- Investigate execution failures.
- Support test reporting and analysis.
Practical example:
Suppose a requirement states:
“As a registered user, I want to reset my password so that I can access my account if I forget my password.”
An AI-assisted workflow can help generate scenarios for valid email addresses, unregistered email addresses, missing input, invalid formats, and password-reset link behavior.
The QA engineer should verify the scenarios against the actual acceptance criteria and security requirements.
Best for: QA teams looking for AI assistance within a broader testing workflow.
6. mabl – AI-Assisted Test Automation
mabl is a testing platform that uses AI to assist with automated testing across supported application types, including browser, mobile, and API testing.
Its capabilities include generating test steps from natural-language instructions and helping teams maintain and improve automated tests.
How QA engineers can use mabl:
- Create automated tests from test intentions.
- Validate user journeys.
- Build browser and API test workflows.
- Assist with visual assertions.
- Reduce some repetitive test-maintenance work.
Practical example:
For an online shopping application, describe a user journey involving product search, adding an item to the cart, and checking the cart total.
Use the generated test as a starting point, then confirm that it validates the correct product, quantity, price, and expected outcome.
Best for: Teams interested in AI-assisted end-to-end testing and automation.
7. Applitools – AI-Powered Visual Testing
Traditional functional testing checks whether an application behaves as expected. Visual testing checks whether its interface looks correct.
Applitools offers visual testing capabilities that help identify unexpected visual differences between application versions.
How QA engineers can use Applitools:
- Compare application screenshots.
- Detect unexpected UI changes.
- Validate layouts across supported browsers and devices.
- Identify visual regressions.
- Reduce the effort involved in reviewing large numbers of screenshots.
Practical example:
Imagine that a developer changes the CSS of a banking dashboard. The page still loads, and all buttons work, but the account balance overlaps another element.
A functional test may pass without detecting the visual issue. Visual testing can help identify the unexpected layout difference.
However, a visual difference is not automatically a defect. Some changes may be intentional and should be reviewed.
Best for: QA engineers testing dashboards, e-commerce websites, banking applications, and complex user interfaces.
8. AI Coding Assistants for Learning and Debugging
In addition to dedicated testing platforms, general AI coding assistants can help QA engineers learn programming and troubleshoot scripts.
Examples include ChatGPT and GitHub Copilot, as well as other coding assistants supported by your organization’s development environment.
How to use these tools effectively:
- Ask for a simple explanation of unfamiliar code.
- Request examples before attempting complex scripts.
- Share a sanitized error message and ask for possible causes.
- Ask the assistant to explain why a suggested fix works.
- Request alternative solutions and compare their trade-offs.
For example, if a Playwright test fails with a timeout error, ask the assistant to help you investigate whether the cause might be an incorrect locator, a slow response, an unexpected page state, or an environment issue.
Do not accept a suggested timeout increase without understanding the root cause.