Traditional testing isn't keeping pace with the speed of DevOps and Continuous Delivery, but hope is not lost; AI will be used to make testing faster and more accessible to all. Existing QA solutions were built for a world where software changed infrequently. Highly adopted tools such as Selenium, Appium, and JUnit require a specialized skillset, and require too much maintenance once you start factoring in the brittle nature of tests, and the infrastructure required to run tests at scale. But there is still hope for QA in machine intelligence. Next-generation ML tools are here to help QA keep up with the agility of modern software delivery practices. You'll learn what ML strategies are being employed to make this possible, and what the future of QA - intelligent testing - looks like. Takeaways: •An overview of the QA tooling and vendor landscape •Demystifying the buzzwords - what machine intelligence in testing means today and tomorrow •How implementing DevTestOps can help increase test coverage and improve product quality