Agentic testing is an innovative approach in UI automation that leverages AI agents capable of autonomously executing, monitoring, and adapting test processes without relying on predefined scripts. Unlike traditional methods, agentic testing uses advanced AI technologies, such as Large Language Models and computer vision, to intelligently interact with user interfaces by identifying elements, understanding context, and adjusting to changes in real-time. This approach enhances various aspects of UI test automation, including test case generation, element recognition, and test maintenance, by automatically generating test scripts, recognizing UI elements through intelligent object recognition, and self-healing capabilities that adapt to UI changes. Agentic testing offers significant advantages in industries like education, healthcare, and finance, where it ensures UI stability and performance under dynamic conditions. Despite its early stage, agentic testing is poised for growth, with tools like RadView's WebLOAD and KaneAI leading the way in integrating AI-driven solutions to make testing processes more efficient and less reliant on human input.