artificial intelligence: real solutions for automated testing

AI-powered testing tools are becoming a vital resource for achieving these goals. There are a dizzying array of options and it’s important to analyse where your organisation can best profit. A Gartner[1] paper highlights the values of these tools for assisting in generating test scenarios, automating tests, optimising and prioritising test suites, predicting defects, analysing results, and estimating testing efforts. They reduce the need for manual intervention, enhancing test coverage, accuracy, and robustness.

In a survey conducted by Censuswide[2] last year, most organisations reported already using some form of AI-enhanced testing tools and they could also foresee increased investment (74%) in their organisation in 2025. It’s important to note the emphasis on “augmented” with AI-augmented testing: despite all the hype about autonomous testing, no-one believes that human input to the testing and validation process is going to go away any time soon. Understanding the use cases is important as you research AI testing tools and investigate capabilities. As with any technology, it’s important to think about where you will get the most benefit. Not all organisations will need all capabilities, and not all tools will offer them.

Gartner highlights five use cases where AI is improving the test process today:

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