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How AI will transform the Testing Process

By John White Last Updated on Jun 14, 2021

Currently, there is so much discussion about how artificial intelligence (AI) will change our lives. One of the technology’s key benefits lies in its power to transform traditional approaches to app development and software testing. Gartner identified AI-driven development as one of its top three strategic technology trends for 2019.

Digital transformation is dependent on better-quality software, and software testing matters more than ever. However, the growing complexity of our software-driven world means that new, smarter and quicker forms of testing are critical in the race to build better software faster. But in a hyper-connected and complex environment, this is no simple task, and this is where AI-driven testing can help.

AI Transforming Testing

Like any new technology, there are exaggerated claims. However, when it comes to testing, AI is now delivering actual improvements and making intelligent automation a certainty. AI has moved far beyond an academic concept and is driving business benefits as opposed to hints to those organizations that have adopted it. Below are four of the key techniques that it’s already transforming testing.

Suggested Read: Key benefits of AI in testing

Auto-Generation of Test Scripts

There are undoubtedly complex test cases for which AI can’t auto-generate all the code. However, AI can easily auto-generate the code that clicks the buttons on the screen, fills out a form, logs into the app and other similar functions. Organizations that have deployed AI-driven testing are able to auto-generate 80% of code reliably, delivering substantial efficiency improvements. Along with auto-generation, AI achieves auto-maintenance: Tests are rebuilt when something in the digital product changes, ensuring continuous quality is maintained and further reducing the resource burden on human testers.

Test Optimization

If you’ve ever used Amazon, then you know that reference engine technologies are not that innovative. AI can be applied to testing, in the same way, to help companies determine which test is most likely to find a defect based on the risk information gathered. Rather than taking a haphazard approach to testing, AI enables you to home in on the areas at risk—not only delivering efficiency gains but also ensuring a quality experience that delights.

Read: Artificial Intelligence trends for 2019

Release Impact Neural networks, joined with test history and data from current test runs, can forecast how a future release will impact users.  For example, will customer happiness go up or down? Armed with this information, companies can make any adjustments necessary to ensure their users continue to be delighted by their digital experience.

Customer Impact

This is a key advantage of deploying AI-driven testing as you can regulate the impact on the business from issue updates. Neural networks, machine learning, and other AI techniques can be used to understand how technical factors impact business performance. For example, are freight times negatively impacting change rates? By understanding how releases will affect the business, you can make changes that will quickly have a positive impact.

What Does the Future Hold for AI-Powered Testing?

In addition to the core benefits that AI-driven testing is already delivering, organizations can expect to see additional benefits within the next 12 months that will further accelerate their ability to fully automate the entire testing life cycle.

Failure Determination

Current testing compares the result of a test with a pre-defined known good result. That methodology simply will not work with dynamic systems, such as an internet of things (IoT) device that interacts with multiple other devices which are constantly changing. AI is a key part of the solution: A well-trained AI system can determine whether a real user would consider the actual result correct or not.

Read also: 3 ways of AI is improving cybersecurity

Persona Testing

One size doesn’t fit all, and the ability to understand how your app reacts under different personas will allow organizations to understand what parts of the app are particularly good or bad for different personas. Armed with this information, you can optimize your app for your target audiences, ensuring an experience that delights.

personas based testing

As every organization races toward digital transformation, delivering a high-quality digital experience is essential for survival. To create compelling digital experiences, companies need tools that can navigate applications intelligently, learn where quality issues are most likely to occur and identify the critical data correlations that will help developers resolve issues quickly. This is where AI is already delivering significant advantages to organizations that have adopted it.

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It’s clear that AI-driven testing is not a temporary trend. Rather than taking a wait-and-see approach, it’s time to jump in and experience how AI can help transform app development and software. With AI-driven testing making a real and measurable impact on the business, you can’t afford to be late to this revolution.