Automated vs autonomous QA testing
People use "automated QA testing", "automatic QA testing" and "autonomous QA testing" as if they meant the same thing. They overlap, but the difference matters when you decide what to buy or build.
Automated QA testing means a machine executes tests that a person designed. Someone writes a script that says "open the cart, add two items, check the total". The computer runs it quickly and repeatably. The thinking was done in advance.
Automatic QA testing is usually a looser phrase for the same idea: tests that run without anyone pressing a button, for example on every pull request.
Autonomous QA testing moves the thinking itself to the machine. An autonomous system reads what the product should do, looks at what changed, decides what to test, runs it and judges the result. Nobody writes the individual test steps.
| Question | Automated QA testing | Autonomous QA testing |
|---|---|---|
| Who decides what to test? | A person, ahead of time | The system, for each change |
| What is written by hand? | Test scripts and assertions | Context: requirements, design, rules |
| When the UI changes | Scripts often need updating | Checks are planned again from context |
| New feature, no tests yet | Not covered until someone writes tests | Checked against its requirements |
| Strongest at | Fast, exact repeat checks of known flows | Broad coverage without script upkeep |
Neither is simply better. Our side-by-side comparison of agentic QA and test automation covers when each one earns its keep.
What "no test scripts" really means
No test scripts does not mean no input. It means your input moves up a level. Instead of describing every click, you describe what the product is for.
- Requirements and acceptance criteria. What the feature should do, in plain language.
- Your design system. Tokens, components and layouts the screens should match.
- Business rules. Prices, limits, permissions and edge cases, such as "viewers can never edit orders".
- A build to test. Usually a preview or staging environment.
Most teams already have these documents in some form. Autonomous QA testing turns them into checks, so the same documents that guide development also guide testing.
How autonomous QA testing works in ShipperAG
- Connect a preview or staging build.
- Add context: requirements, design system and business rules.
- Specialists test. A coordinator picks which AI QA agents this change needs and they run real checks.
- Evidence. An independent verifier re-runs every finding before it is trusted.
- Sign off. You approve the release, or share the report with your stakeholders.
Every result lands in one of four states: verified, issue found, needs input or not covered. That last state is what makes autonomy safe. A system that hides its gaps looks complete when it is not.
Want to see this run against your own requirements, design system and business rules, before your next release? Start with a free 45-day trial, no card.
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Guardrails that make autonomy safe
"Autonomous" should never mean "unaccountable". The system should act on its own for routine work and stop when a real decision is needed.
Limits you set
The coordinator chooses specialists within the time and scope limits you define, so a small copy change does not trigger a full security review unless you want it to.
It asks instead of guessing
When two sources disagree, for example a product spec and API docs describing different refund windows, the result is marked "needs input". Guessing would turn an unclear requirement into a hidden assumption.
Proof over opinion
A model saying "looks fine" is not evidence. A pass has to come from a check that ran and can be reproduced. We explain why in our guide to agentic QA testing and verification.
No self-approval
If code changes, a different part of the system checks it independently. Nothing approves its own work.
Running autonomous QA in your own pipeline
ShipperAG is designed to run checks inside your own CI, next to your code. Results are written to a hash-chained evidence ledger, giving you a record of what was checked on each build and who signed it off.
What stays human
Autonomous QA testing takes over repetitive checking. It does not take over responsibility. People still decide what the product should do, resolve "needs input" questions and make the final release call. Some checks, such as judging whether alt text is actually meaningful, need human review; our AI accessibility testing guide is honest about where that line sits.
This balance holds however your code gets written. Whether your team writes it by hand, with AI coding tools, or both, autonomous QA gives every change the same careful check against what the product is meant to do.