Mabl was built on the premise that AI and machine learning could empower software testers to transform how their organizations build and deliver world-class user experiences. Since our founding in 2017, we have invested in harnessing AI to amplify human insight, build reliable tests, and improve the user experience. That effort has earned the trust of customers like ADP, Barracuda, JetBlue, Roche, and Liberty Mutual, as well as industry recognition from respected experts like Gartner, who recently included mabl in their Market Guide for AI-Augmented Software Testing Tools.  

Building Test Automation That Empowers QA Professionals, Developers, and More 

Mabl’s approach to harnessing AI for software testing is guided by our fundamental belief in the importance and value of QA expertise. As the definition of software quality is modernized to match shifting consumer expectations for the user experience, the human element of QA has only become more essential. Automation, no matter how intelligent, must complement the people powering quality. To that end, mabl’s Core AI Principles are:

  • Augmentation, Not Replacement: We build AI to handle the grunt work, amplifying human insight and giving you superpowers. Reliable, resilient automated tests mean you can trust the results and focus on what matters.
  • Quality > Quantity: A thousand flaky tests are useless. We give you smarter test automation, helping you build a rock-solid core of tests you can trust. Achieve higher quality with less work.
  • AI for Better UX. Period: We use AI strategically, not just for the sake of it. From expert systems to generative AI, we leverage the right AI for the task, ensuring your user experience is always the priority.

These principles are the foundation for how we consider new capabilities and the needs of QA professionals everywhere as software testing evolves.

Leading the Pack in AI-Augmented Software Testing

The Gartner Market Guide for AI-Augmented Software Testing Tools, released in February this year, highlighted just 15 vendors in the test automation market. With over 100 vendors in this space, being included is a tremendous honor and accomplishment for the mabl team.

The Market Guide noted the bright future for AI in software testing, sharing that:

  • By 2027, 80% of enterprises will have integrated AI-augmented testing tools into their software engineering toolchain, a significant increase from approximately 15% in early 2023.
  • More than half of IT leaders expect their organization will use generative AI to build software, according to the respondents of the 2023 Gartner IT Leader Poll on Generative AI for Software Engineering. 

Driving this sharply rising demand is the increasing complexity of modern applications and ongoing high dependency of manual testing, which impacts overall developer productivity, product reliability, stability and compliance as well as operational efficiency of final products. When applied correctly, AI can help software testers, developers, and companies confidently deliver new innovations to market. 

Gartner noted that mabl includes a variety of AI-augmented capabilities, including visual testing, test orchestration and Intelligent Wait features. All of which are wrapped in our user-friendly low-code test automation platform, meaning that anyone - regardless of coding experience - can harness these cutting edge technologies to test web apps and APIs, as well as perform accessibility and performance testing.

Being recognized in the Gartner Market Guide for AI-Augmented Software Testing Tools follows mabl being named a 4x winner of the AI Breakthrough Award for Engineering Solutions and honored as the “Most Disruptive” at Vista Equity Partners’ 6th Annual Global Hackathon. The hackathon featured over 130 participants on 30 teams from dozens of Vista portfolio companies to explore how generative AI can transform the future of enterprise software and create solutions that drive customer value and are developed in an ethical, transparent and accountable manner.

Mabl’s contribution to the hackathon used generative AI to further augment test creation. In software test automation, the intent of a test is critical. This intention is often captured in the form of assertions. Assertions allow you to ensure the quality of your application by validating the expected behavior. Mabl’s solution combines existing company technology with generative AI to capture a tester's goals, guide them through the test creation process and automatically integrate best practices, significantly reducing effort during test creation and maintenance.

Leveraging Different AI Techniques for Maximum Software Testing Impact 

On the left is a figure 8, representing the testing stages; on the right are the ways mabl addresses ML, GenAI, Expert Systems, and Computer Vision.

An advantage to having almost a decade of experience in harnessing AI and machine learning for software testing is that the mabl team has an in-depth understanding of what AI techniques are best suited to different testing tasks. From using unsupervised machine learning to identify test coverage gaps to leveraging expert systems and probabilistic models to automatically adapt tests to selector/attribute changes, mabl has a diverse set of AI capabilities that make each software testing step smarter and faster.

Faster Test Creation with AI

  • Intelligent Find Strategies: AI pinpoints elements with precision, eliminating manual selector tasks and accelerating test creation.
  • Early Flakiness Detection: AI proactively identifies potential flakiness, requesting context to improve test stability.
  • Test Coverage Insights: Leverages unsupervised machine learning techniques like clustering to identify gaps in test coverage.

AI-Powered Reliability and Resilience

  • Intelligent Wait: Supervised machine learning models learn your application timing to dynamically adjust tests for faster and more reliable execution in any environment.
  • Enhanced Auto-Healing: Expert systems and probabilistic models to automatically adapt tests to selector/attribute changes, drastically reducing test maintenance.

User Experience Insights

  • Visual Change Detection: Computer vision to detect unexpected UI changes, ensuring that your users always have a good experience.
  • Performance Anomaly Detection: Mabl keeps track of page load and test run time with clustering to detect potential regression early.

AI Experience, Not AI Washing

Every company is attempting to “AI wash” their products to appear innovative, particularly in software development. But mabl has been in the trenches of AI innovation for almost a decade, and we didn’t get here by accident. Since Izzy and I co-founded the company in 2017, we have made deliberate, thoughtful investments in building AI capabilities that support and augment software testing teams. Mabl has been an intelligent test automation platform since day one, and those long-term efforts continue to draw recognition from experts like Gartner and Vista Equity Partners. We’re honored to be included in the Gartner Market Guide for AI-Augmented Software Testing Tools, and more importantly, we’re proud to be the AI-augmented software testing partner of choice for quality leaders around the world. 

See how mabl uses AI to amplify human insight, build reliable tests, and improve the user experience by registering for a 14-day free trial