As AI continues to evolve, the QA testing environment is changing at mach speed, and testing teams must learn to utilize the technology to increase testing productivity, especially with regards to test automation. Now’s the time to get on board and integrate one or more tasks into the testing strategy. AI will continue to change, but early integration of AI into testing will help ease the learning curve and limit potential disruption.
Testing teams must cover increasingly complex applications. AI can help provide task or process automation that supports testing. The last thing a testing team needs is a new process that generates additional work. By creating a solid plan and involving the test team, companies can leverage AI with little business disruption. This guide describes the benefits of AI technology, top areas for AI in test automation, and tips for integrating AI into testing processes.
Decide where to start
Before we jump into the benefits of AI in your quality efforts, consider the fact that an efficient testing team will always integrate new technology by identifying exactly where to start. Process changes depend on the technology introduced. Allow testers time to adjust to these changes and improve it with continuous feedback.
Testing teams may select one or two testing activities and determine if integrating AI changes the entire process only slightly, or results in major adjustments for testers. Productive testing teams then prioritize changing processes and update them in turn. To support continuous process improvement when integrating AI, use reporting to set up testing metrics so the team knows if the intended improvements are working.
Benefits of integrating AI into test development
Testers must understand the benefits of integrating AI into test development to manage a transition without impacting deadlines or testing quality.
The benefits of integrating AI into test team processes include:
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Automated test script development assistance
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Detailed management reporting
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Expanded test coverage beyond basic functional scenarios
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Enable rapid automated test development with less need for re-work
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Automated testing for visual UI testing using computer vision
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Reduced need to maintain automated scripts
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The ability to create test data for automation without involving development or IT
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Time and testing cost savings
AI-enhanced test development tools can assist testers in script development by analyzing requirements or user stories, code, and specification documents to identify test scenarios. Most tools generate manual tests that can be automated either directly or by using a modern record and playback tool. The improvement can be seen in fewer missing test scenarios that were not recognized by human testers. At the same time, testers add their expertise, automatically making any corrections necessary in the AI tests.
Testers also use AI for predictive analysis to find patterns in functionality that are more prone, historically, to defects. AI does a decent job of discovering possible user behaviors that keep testing from missing potential user workflows. The more defects identified during testing, the fewer that appear in production.
Another benefit of using AI is that it expands test coverage. Most AI-infused test automation tools include automatic test creation for visual regression on a UI. Visual testing involves auditing visual elements on a web or mobile page and comparing them to past releases to find undocumented changes. AI tools only take minutes to compare dozens of pages in both mobile and web apps to identify changes.
AI also benefits testing teams by finding visual defects. Preventing visual defects builds customer trust and generates credibility. AI-infused tools will flag an assigned tester to review defects entered for validity. Testers don’t waste time pouring over reports, but instead get notified when an AI-reported defect requires review. With AI performing the bulk of the visual testing, testers can focus on critical customer workflows and other more complex scenarios not covered by AI.
Testing teams spend significant time re-creating or editing automated test scripts when they break due to coding changes. Automated test script maintenance significantly slows test completion, which hinders effective testing across an iteration or sprint. AI test automation tools benefit testers by including self-healing technology that maintains automated scripts.
Finally, AI is exceptional at creating test data. Experienced test teams spend a great deal of time and effort on refreshing test data per test execution. When teams repeatedly run automated tests throughout a sprint or iteration, AI is the only way to keep up. AI technology can create test data, and testers can refresh it using a script or by pushing a button before the next scheduled test execution.
Tips for making testing process changes
Good testing teams are both productive and adaptable. Exceptional testers cope well with change and are open to creative solutions to solve challenges. What challenges? Testing teams are typically challenged by time and resources. When making testing process changes, like integrating AI into automated test development, talk to the team first.
Ask the team for ideas on how to get AI integrated where it fits. Have the testing team identify gaps and potential conflicts. Remember, flexibility is vital. Flexibility is the best approach for successful testing. Software technology and testing continue to evolve, and AI is the latest change. There will be improvements to AI for years to come, so now’s the time to evolve. For added success, Involve test team members in solutions.
Testing teams that integrate AI into testing processes are then ready for the next AI improvement. Testers can optimize testing quality and reduce complexity by using AI to help create tests, support automated script maintenance, and provide test data on demand. AI is not an enemy. It is the tireless teammate who handles the tedious work that is necessary but takes too long. AI can improve automated test development, script maintenance, and create test data that saves testers a great deal of time.
Is there no time in the schedule to integrate AI into testing processes? Why not use OnPath’s experienced testing teams to help make the transition? Our testers leverage AI to improve productivity and software quality. Contact OnPath today.
