Emily Clarke

Why AI Innovation is Beneficial to Software Testing

Artificial intelligence is a technology that's still relatively new, but it's already having a colossal impact on the entire world. In software development, AI is starting to change how companies manage testing protocols. Testing is usually a time-intensive and resource-heavy task. Despite its burden, it's a necessary step in the development process that readies products for release.

AI-based test automation aims to revolutionize development cycles in many ways. Not convinced? Here are a few game-changing benefits AI brings to the testing table.

Better Reliability

Think about your current testing processes. You may still rely on manual testing. While the human element can be advantageous when looking at UI and other user-facing details, it's not the most reliable approach to software testing.

You must contend with human error, subjectivity, and wavering accuracy with manual testing. None of that is an issue with AI. It's machine-accurate, and AI can read and understand code changes. Imagine how effective and reliable regression testing is with AI!

More Efficient Testing

Another issue with human-powered manual testing is its generally low efficiency. Traditional testing is a slow and monotonous process. When one test cycle is over, you must do it all again with every code change. It's mind-numbing work that no one wants to do.

You can divert more of your human resources to impactful testing initiatives with AI-based test automation. Leave the busy work to the machines!

Faster Development Cycles

The beauty of AI testing is that it helps significantly speed up QA. Furthermore, you can implement testing at multiple stages of the development cycle. Start early, capture errors as they occur, and make changes before they become costly or time-consuming.

After setting up AI-powered tests, you can execute them repeatedly without additional costs.

Innovative Testing Processes

We can't ignore the unique innovations AI brings. This technology is about constant improvement. The more you use it, the better it gets.

AI in software testing is often used for image-based issues. With AI, a system can often detect minor visual anomalies that humans often miss. It's a great way to make fine-tuned adjustments, perform visual validations, and spot potential errors.

Author Resource:-

Emily Clarke writes about automated software testing & UI testing automation tools. You can find her thoughts at software testing ethics blog.