Today, I’m excited to share that mabl has once again been named a Best AI-based Solution for Engineering by the annual AI Breakthrough Awards program conducted by AI Breakthrough, a leading market intelligence organization that recognizes the top companies, technologies and products in the global Artificial Intelligence (AI) market today. 

This award is the fourth time mabl has been recognized as an AI innovator by AI Breakthrough, having been honored in the same category in 2019, 2020, and 2022. Mabl’s repeat wins demonstrates our team’s commitment to delivering innovation to our customers and the broader quality engineering community. This type of sustained platform growth never happens in a vacuum, so we thank our customers, especially those who participate in our early access programs, for helping mabl build the future of test automation. Your feedback, support, and expertise are essential to our team.

The Changing World of Artificial Intelligence 

The landscape of AI in both the enterprise and in our daily lives has been transformed in the past six months. People are excited and apprehensive about the opportunities presented by generative AI and its potential. At mabl, we share your curiosity and excitement for how AI can make software development faster and more efficient. But our fundamental mission hasn’t changed: we’re still focused on making software testing possible for everyone, including manual testers, QA engineers, developers, and business roles. Everyone has a role in quality, mabl just helps them have a higher impact.


AI and machine learning already play an important role in mabl’s test automation platform; reducing the effort needed to maintain tests, improving test reliability, providing recommendations to improve test coverage, and much more. A few examples: 

Autohealing: mabl features native autohealing test capabilities that capture over 35 unique element attributes during test creation and execution, which helps automatically evolve tests as a website’s UI changes. Mabl’s smart element locators offer an in-depth and adaptable approach to identifying app changes, allowing development teams to easily test dynamic customer journeys across shadow DOM elements, APIs, and non-functional quality attributes. By automatically updating tests, without the need for human intervention, autohealing test automation improves reliability and team efficiency for faster development that doesn’t sacrifice quality. 

Intelligent Wait: Intelligent Wait reduces test failures by incorporating historical application performance into the timing of actions within tests. During each test run, mabl collects timing data for each step and automatically tailors test execution to match the pace of the application. By mitigating the need to insert manual wait steps or other cumbersome configurations, quality engineering teams can improve test reliability and reduce false positives without any extra work, saving them valuable time and effort. 

Page coverage: mabl’s page coverage feature uses machine learning to cluster similar application URLs to give mabl users useful insights about real application usage. For example, when multiple webpages are actually customized versions of the same page, such as individual user workspaces, it’s more efficient to focus testing on the general functionality the pages provide. Page coverage allows quality engineering teams to understand how to more effectively prioritize tests for better test coverage and fewer low-impact tests. 

Like the intelligent capabilities that came before it, generative AI and the next wave of intelligent innovations will work best if they complement and elevate human capabilities. Quality teams play an invaluable role in connecting how software is built and how it is used. AI can help us do that faster and effectively, but it cannot replace the critical perspective of people.

Harnessing Generative AI to Support Quality Contributors

Mabl is honored to be a 4-time recipient of the AI Breakthrough Awards Best Solution for Engineering. There has never been a more exciting time to be a software tester as AI and machine learning unleash new ways to build better software at faster speeds. Thank you to our team, our customer community, and everyone joining our journey as we build the future of intelligent test automation. 

Join myself, the mabl team, and the rest of the community as we explore the exciting world of AI and machine learning in software development. Follow us on LinkedIn, Twitter, or Facebook as we share new ways to harness generative AI for software testing. I have already shared a few ways you can experiment with ChatGPT to support low-code test automation, with more insights on the way.