Well firstly, are you comfortable with AI writing your test cases and if so, how would you spend the saved time? What tasks would you do instead?
We are starting to implement an AI first approach to Planning so really intrigued to see what comes from this convo. AI’s driven massive growth in output in efficiency from our Dev team which means we need to do something to keep pace. We’ve only just started using it, but anticipate that we may be able to begin to address gaps in our ACs and hopefully much more exploratory testing.
This is an interesting question, to be fair I’ve not written test cases in decades due to waste and low value related thing so this is not something I’d look to AI for. Similarly with automation its not so much a saving but allows me to add automation I would not have covered before.
With AI bringing others challenges to light though I am recognising that a lot more people than I was aware of have been writing and executing test cases or spending a lot of time on maintenance activities. There are some indicators they will just do more of this with faster code churn coming through but I am interested to see what the views of those in this situation are.
Taking on more QE activities from developers does seem one path that is being flagged at the moment but that is a move away from testing,
Based on my past experience of shifting away from test case approaches to other testing models I’d say easily 5x in value and efficiency so an opportunity there but that could me less headcount along the way unless workflow increases to balance that out.
So much tools to experiment with at the moment so that could be a quick option and their would be knowledge not being gained by not writing them anymore, best though to get views from those going through this now, whilst I have experience in that sort of transition from decades ago I’m speculating quite a bit here.
I think I’d spend a lot of time reviewing the test cases AI wrote. I’d also be spending time prompting AI to produce better test cases. The human in the loop will be important for some time to come.
i’d spend the time testing the assumptions behind the generated cases, not just executing more of them.
if the same acceptance criteria shape both the feature and the ai-written tests, you can get a lot of clean coverage around the wrong behavior.
exploratory work, real user journeys, and reviewing why each case exists feel like the higher-value move.
I’d spend more time validating requirements, not writing more test cases.
AI can generate test cases quickly, but it can’t tell whether the requirements are complete or correct. My Validation-First approach is to validate business rules, assumptions, and edge cases before using AI for test generation.
Better inputs lead to better AI-generated tests. Human judgment is still essential where it matters most.
I’m still one for human in the loop. Hence I think I wouldn’t have too much free time at hand to do anything else. However, given the new stuff with agents and sub agents, I think I’d spend time thinking about improving the quality improvement.