How Agentic Automation Can Expand Your QA Coverage Without Expanding Maintenance

Give Yourself More Time to Investigate

You open the test results for a release and see several failures. Before you can tell anyone whether the product is ready, you need to work out what those failures mean.

Perhaps a button moved and the test can no longer find it. Perhaps the test account has expired. Or perhaps a customer really can no longer complete the task. Each possibility sends you down a different path, and you may spend much of the morning sorting them out.

Meanwhile, there is a new feature you would like to explore more thoroughly. You already have questions about how it behaves when someone changes their mind halfway through. Finding time to investigate them is another matter.

This is where agentic automation can be useful. You can give an agent a defined testing task and let it help with the steps involved, from exploring a workflow to preparing tests and examining failures. That gives you a way to cover additional ground while reducing some of the repetitive effort.

The opportunity is worth pursuing. You also need a clear view of what the agent has checked, what it changed, and what still needs your attention. That visibility is what lets you use the extra capacity with confidence.

Understand What You Are Asking the Agent to Do

If you already use automated tests, you are familiar with defining a sequence of actions and checking the result. An agent can take on some of the work involved in developing or maintaining that sequence.

You might ask it to explore an application form and propose a test plan. Once you have reviewed the plan, it could generate executable tests and run them. If a test fails, it could inspect the application and suggest a change for you to review.

You can see this approach in Playwright’s test-agent documentation, which describes separate agents for planning, generating tests, and investigating repairs. That is a useful example of how an agentic workflow can work alongside an established test framework.

The capabilities vary by tool and configuration. When you evaluate a system, ask to see the work it produces between the assignment and the final result. You should be able to understand its plan, examine the checks, and follow its explanation of a failure.

That also helps you set realistic expectations. You may gain a useful assistant for a particular workflow before you are ready to let it handle broader responsibilities. Start with the work you can evaluate well.

Tell It What Should Happen

An agent can explore what your application does today. You still need to give it a reliable basis for deciding whether that behavior is correct.

Suppose you are testing an application form that lets someone save their progress and return later. You want to know whether the information is preserved, whether the person can recover access, and whether the final submission reaches the right destination.

Watching the current application may reveal how those steps work. It will not necessarily reveal a missing requirement. If the system already loses an attachment when someone resumes a draft, an agent could observe that behavior without recognizing that it is wrong.

Give it the relevant acceptance criteria and explain the outcome you expect. Include the conditions that matter, such as whether a returning applicant must sign in again. A clear example of a successful result can be more useful than a long collection of loosely related documents.

You can also supply selected evidence about where someone struggles. A recurring support issue may point to a useful scenario. Usage information may show a common route through the form. Choose information that helps the assignment, and use suitable test data rather than handing over unnecessary customer details.

If you cannot explain the expected behavior clearly, pause long enough to resolve that with the person responsible for the product. The answer will improve both the agent’s work and your own test plan.

Start Where Additional Coverage Would Matter

You probably have more possible scenarios than time to investigate them. An agent can generate more ideas, but you still need to decide which ones deserve attention.

Start with a workflow where failure would create a meaningful problem for the person using it. For the application form, saving progress may be especially important if completing the form takes time. Losing that work could force someone to start again or give up.

Then consider variations around that task. What happens when the session expires? What happens when the person returns on another device? What happens if they correct an earlier answer that affects a later section?

Those questions give exploration a purpose. You can ask the agent to investigate them, record what happened, and identify further paths worth reviewing. You have a better basis for judging its work than you would after asking it to test everything.

Keep the first assignment contained. Give the agent an appropriate test environment, defined access, and a limit on how long it should explore. You want enough freedom to discover useful variations while keeping the activity understandable and manageable.

Review What the Test Actually Proves

A generated test can run successfully and still prove less than you think. Reading the test’s name or its summary may not reveal the difference.

Imagine a test called “Submit a completed application.” It fills in the form, clicks the submit button, and checks that a confirmation message appears. That might be a useful check, but it does not establish whether the application was stored correctly or delivered to the system your staff uses.

Decide how far the test needs to follow the result. You may need a separate check of the saved record or a controlled way to confirm that a downstream system received it. The right approach depends on the responsibility you are testing.

Pay particular attention to the assertions, which are the conditions a test uses to decide whether it passed. Ask whether those conditions would fail if the problem you care about occurred. A test that merely confirms a page opened may offer little protection against an incorrect calculation displayed on that page.

You should also review whether new tests add distinct coverage. Several variations can be worthwhile when they exercise different rules. Several tests that repeat the same path with different wording may simply create more work to maintain.

Once you are satisfied with a test, you can add it to your established suite and run it consistently. You do not have to repeat the entire exploratory process every time you need that check.

Make Test Repairs Explainable

Test maintenance is one of the most appealing uses of agentic automation. When a product changes, an agent may help you locate an updated control or adjust a test to reflect an approved workflow change.

You need to know why the repair was appropriate. Ask for an explanation of the original failure, the proposed change, and the requirement the revised test still checks.

Consider a hypothetical checkout test that verifies a delivery charge. If the application starts showing the wrong amount, changing the expected value would make the test pass while allowing the defect to remain. A repair that produces a successful run can still be the wrong repair.

A moved button is a different situation. If the action and expected outcome are unchanged, updating how the test finds that button may be reasonable. You should be able to see that distinction in the evidence provided with the change.

Make skipped tests and removed checks visible as well. If an agent cannot complete a test, you need that unresolved result to remain part of your release discussion. It should not disappear into a cleaner-looking report.

You can also use the investigation to address recurring flakiness. A test that sometimes passes and sometimes fails may have a timing problem, unreliable data, or an unstable dependency. Finding and correcting the cause can save more effort than repeatedly accepting small repairs.

Fit the Agent Into the Testing You Already Trust

You do not need to rebuild your entire QA process to introduce an agent. Look for a place where it can add useful information alongside the checks you already rely on.

You might use it to explore a changed workflow before writing the final regression tests. Or you could ask it to investigate a recurring failure and prepare a proposed repair. Keep the assignment close enough to your existing process that you can compare the results.

For your build-and-release pipeline, begin with visibility. You could run new agent-assisted checks alongside your established tests and review what they report before making them release requirements. Once a check has proved useful and dependable, you can decide whether it belongs among the conditions that must pass.

Keep exploratory work manageable by giving it a time limit and a clear reporting destination. You need to know who will review a finding and what evidence they need to act on it. Screenshots, reproduction steps, and relevant test data can make the report easier to investigate.

You can continue using conventional automated tests for repeatable checks while reserving time for hands-on exploration. That combination lets you benefit from generated work without giving up the predictable feedback and direct observation you already value.