raditional test automation relies heavily on predefined scripts, which are often brittle, time-consuming to maintain, and difficult to scale in rapidly evolving applications. As modern systems become more dynamic—especially with microservices, frequent deployments, and UI changes—these conventional approaches struggle to keep up.

This session explores how AI-powered test automation is transforming the Quality Assurance landscape by moving beyond static scripts toward intelligent, adaptive testing systems. We will examine how machine learning and generative AI techniques can automatically generate test cases from requirements, user stories, and application behavior—significantly reducing manual effort.

A key focus will be on self-healing test scripts, where AI can automatically detect UI or API changes (such as broken locators or modified endpoints) and update test cases without human intervention. This dramatically reduces test flakiness and maintenance overhead.

Additionally, the session will cover:

Intelligent test execution and prioritization based on risk and past defects
AI-driven defect detection and root cause analysis
Integration of AI into CI/CD pipelines for continuous, smart testing
Real-world tools and frameworks enabling AI-driven QA

By the end of this session, attendees will understand how AI is not just enhancing but redefining test automation—making it faster, smarter, and more resilient.