In the modern software industry the movement toward the software-defined vehicle, the frequency of software development increases, and with it, the need to update these components frequently through OTA. The modern cockpit has a multi OS model and all the displays run over one or another operating system based on criticality of function. To test the UI rendering and frame rendering for all of these, either we need visual inspection or we need tools like profilers. With the traditional testing methodology, testing, validating and fixing any abnormalities is time-consuming. This presentation introduces an AI-driven framework which validates the automation system that utilizes computer vision for semantic analysis of HMI. This framework is independent of any OS running underneath an automotive framework. This framework also uses AI agents to detect any abnormalities and ensure safety-critical icons are rendered with 100% integrity regardless of system load. This AI vision language model observes the screen in real time via API bridge and compares it with the visual requirement specification. This will reduce the total workaround time for developing and deploying any HMI application significantly compared to traditional manual testing.