When budgets tighten, QA is often the first line to shrink. The logic seems sound: testing does not add features, so less testing means more output. In practice it works the other way round.
The real cost of skipping tests
A defect found by a developer costs minutes. The same defect found in production costs a hotfix, a rollback, support time and, sometimes, a customer. Teams without strong QA slow down over time because every release carries more risk, so they release less often and in bigger batches, which makes each release riskier still.
QA as part of delivery
- Test early. Testers join planning, so acceptance criteria are clear before code is written.
- Automate the repeatable. Regression suites run on every change, so people test what is new.
- Measure what matters. Escaped defects and time to recover, not just test counts.
Why it matters more with AI
AI features behave differently from ordinary code. The same input can produce different output, and quality can drift without a single line changing. That makes disciplined testing more important, not less: evaluation sets, regression checks on model output and human review where errors are costly.
Good QA does not slow a team down. It is what lets them release on a Friday.
The teams that ship fastest are rarely the ones that test least. They are the ones that made testing cheap, automatic and part of every change.