client after client, I see testers, test automation engineers, and developers creating test cases that are long, that are difficult to work with, and that don’t have a clear purpose. If their test cases were more streamlined and focused, the teams that use them would save a lot of time.

Here are five pointers for improving test cases, garnered from my years of working with clients who are implementing test automation.

AI in testing is becoming mainstream. Some 21% of IT leaders surveyed said they are putting AI trials or proofs of concept in place, according to the 2020-21 World Quality Report. Speaking to longer-term trends, only 2% of respondents said AI has no part in their future plans.

If you've been waiting out the AI hype, it's time to dive in. Here's what you need to know about AI in testing.

What if you could make software testing simple? What if it could be done without all the conversations, questions, defect reports, and metrics?

We've been promised artificial intelligence (AI) as the solution to all problems related to testing, especially by those who have never tested—those who believe that what we do as testers is little more than tapping screens to make comparisons.

Although I've stated that AI is coming and will change software testing forever (eventually), we're not there yet—not even close. But that doesn't mean we can't use AI to support our testing efforts.

I often work with clients who are either just beginning, or trying to grow, their test automation capabilities, and more often than not they all make the same, fatal mistakes.