Modern software delivery no longer follows a predictable path from requirements to release. Applications evolve continuously, user interfaces change frequently, APIs are constantly versioned, and cloud environments scale dynamically to meet demand. In this reality, quality assurance cannot function as a final checkpoint in the delivery pipeline — it must operate as a continuous capability that keeps pace with modern development speed. Amidst this backdrop, traditional testing approaches, built around manual effort and brittle automation scripts, struggle to keep up with this level of change. Even well-designed automation frameworks often require significant maintenance as interfaces shift; workflows evolve, and underlying services are updated. As a result, many organizations find that automation intended to accelerate delivery ends up consuming substantial time and effort simply to remain functional. This is where Agentic AI Testing is emerging as a transformative approach.…