AI for Continuous Testing

Software development teams are constantly challenged by increasing demands for new features, shorter times to market, and quicker turnarounds for testing fixes. To cope with these pressures, teams are leveraging methods for continuous deployment and shifting testing to the right -- towards production. Daily pushes are gated by pre-production unit and integration tests while the rest of the testing now happens in production. However, traditional test automation strategies do not effectively adapt to quickly evolving, highly dynamic systems and environments. Thankfully, AI-driven testing tools are helping teams create less procedural, more resilient tests that are able to self-heal in the presence of rapidly changing user interfaces and feature variations. AI allows us to teach the machines to recognize and interact with the system and its environment and generate tests based on training from existing test cases. This results in leaner and smarter test automation that allows us to scale and achieve truly continuous testing in production. Join Dionny Santiago as he describes how to harness the power of AI in your SDLC, and achieve CI/CD without sacrificing quality. Dionny will share much of what AI-driven testing has to offer and prepare you to break into AI today.