· ai-devtools
Why More AI-Generated Tests Don't Mean Better Testing
Every demo from an AI testing tool vendor ends with a promise to cut test design effort from hours to minutes.
Surprisingly, one important question is missing from these conversations: How many of those test cases can QA teams truly trust when testing a business-critical workflow such as payments? The AI Testing Efficiency Trap Many QA leaders use just test case counts and effort savings to show the success of AI implementation. The coverage gaps in AI-generated cases can be costly and won’t surface for months until they show up as a customer-reported bug. A small controlled study by Thoughtworks on AI-generated test cases found that roughly a quarter of AI-generated cases were not clear enough to trust without rework.
