When people talk about âAI in testing,â they usually imagine some fancy automation tools or AI-generated test cases.
But hereâs the truth: I use AI completely differently.
For me, AI has become my QA pair buddy â someone I brainstorm with, test ideas with, and even argue with.
Not to replace my thinking, but to challenge it.
đ How It Started
I used to spend hours reviewing release notes, thinking:
- What did we really change here?
- Whereâs the highest risk?
- What could possibly break that weâre not seeing yet?
Now, instead of overthinking alone, I open ChatGPT and say:
âYouâre my QA teammate. Help me find hidden risks in these release notes.â
And you know what? It often points out things I mightâve missed â not because itâs smarter, but because it forces me to look again from a different angle.
âď¸ What My âAI Pair Buddyâ Does
Here are a few ways I use AI daily in my QA routine:
1ď¸âŁ Brainstorming edge cases
âAct as QA reviewing a checkout feature. What scenarios might fail under heavy load or poor internet?â
2ď¸âŁ Clarifying unclear requirements
âRephrase this user story from a QA perspective â whatâs missing or ambiguous?â
3ď¸âŁ Pre-reviewing regression risks
âAnalyze this changelog and tell me which areas of the product are most likely to be impacted.â
4ď¸âŁ Helping with test documentation
âSummarize this long testing session into 3 bullet points I can paste into Jira.â
These are not âautomations.â Theyâre collaborations.
đ§ Why It Works
- AI doesnât get tired.
- It doesnât assume things.
- And it doesnât take offense when you ask âstupidâ questions.
So, instead of working for me, it works with me.
It helps me test my logic before I test the code.
Thatâs what I call AI-assisted critical thinking â not letting AI decide, but letting it provoke new questions.
⥠The Shift That Changed Everything
At some point, I stopped thinking of AI as a chatbot and started treating it as a junior teammate.
Someone who can:
brainstorm freely,
make mistakes safely,
and push me to think differently.
The best part?
It made my testing faster, more creative, and way more fun.
đŻ Final Thought
The future of QA isnât about replacing testers with AI.
Itâs about giving every tester a thinking partner â one thatâs available 24/7, asks the hard questions, and keeps your curiosity alive.
If you treat AI like your pair tester instead of a magic box,
youâll realize itâs not automation thatâs powerful â itâs collaboration.
How do you use AI in your QA work today? Iâd love to hear your thoughts below đ
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Top comments (3)
This is a great framing of how AI and human QA can collaborate! đ
A few thoughts:
Thanks for writing this â itâs a refreshing and balanced take on AI in QA.
Wow, thank you for such a thoughtful comment â I really appreciate how deeply you engaged with the post! đ
Totally agree about the âtrust thresholdâ â thatâs such an important mindset. I also try to treat AI outputs as hypotheses, not answers, and validate them against product context or logs before taking anything further.
And yes, the more context you feed, the more valuable the collaboration becomes. Iâve actually started building a small âQA memoryâ library of past bugs and product patterns â it helps the AI recognize familiar risk areas faster.
When AI suggestions conflict with team knowledge, I usually go the âjustify + iterateâ route â Iâll ask it to explain its reasoning, and that often helps me uncover whether the disagreement comes from missing context or just a misinterpretation. Sometimes, the back-and-forth surfaces something genuinely new.
Thanks again for sharing these insights â your âtrust thresholdâ framing might just make its way into my next post!
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