4 Ways Software Test Teams Can Gain Value From Gen AI

In a recent blog post, I outlined ways that software developers can improve efficiency by using generative AI. Now it’s time to explore some use cases for test and QA teams. As more organizations embed Gen AI into their integrated development environments (IDEs), many test teams are gaining access to these tools. But simply providing access to the tools is no guarantee that testers will use them – they need to understand the value. 

Here are some ways that QA pros and test teams can use Gen AI to save time and work more effectively. 

Create tests cases based on requirements and acceptance criteria

If your organization practices test-driven development (TDD), when you get requirements for a feature from product or customer teams, you can use Gen AI to turn the conversation into a set of test cases. Ensure that the Gen AI considers the full range of testing scenarios: positive and negative tests, testing error cases, security and compatibility issues, etc.

To take things a step further, you can use AI to take a first pass at writing the automation to test those cases – this offers an efficient way to maintain often neglected automation suites.

Generate automation scripts

Continuing on the automation theme, SDETs can specify a test framework and the features they want to test, then use AI to help create those tests. You can use AI to generate tests that satisfy requirements for a variety of different scenarios and audiences. You can even ask AI to create a list of edge cases – and the automated tests to cover them.

Add AI (and QA) into the pull request review process

When a developer initiates a pull request to indicate that their code is ready for review, give QA teams visibility into that process so they can get ready for testing. Gen AI could take a first look at the PR and the ticket requirements, checking for any errors within that specific branch of code, and recommending test cases. AI could also summarize the changes – or provide a detailed list – allowing team members to quickly narrow their focus to the areas that require attention. QA could have AI look at the requirements and then have it look at the changes to determine whether the changes meet the requirements. There GenAI could direct testing or further discussions.

Optimize test suites

Every test team has gaps. Gen AI can analyze historical test data to identify flaky tests, unused tests, redundancies, and tests that don’t correspond to requirements. It can also identify untested requirements and provide recommendations on how to optimize the test suite to ensure you’ve got the right coverage in place without bloat.

Treating AI as an extra set of eyes or additional reviewer can keep the process moving, providing immediate feedback. AI doesn’t struggle with context switching in the same way that human teammates can and is always available.

Use Gen AI where it works best for you

While Gen AI has limitations when it comes to certain types of testing that rely on human judgment, using it to perform repetitive, time-consuming tasks frees up QA teams for the types of testing people do best.