Software-Defined Vehicles (SDVs) offer significant benefits to the automotive industry but also bring considerable complexity to software integration. This presentation examines the challenges of integrating diverse software components and ensuring compliance with ever-changing requirements and regulations - a core concern that resonates with COVESA’s mission of fostering open and standardized automotive software architectures. By leveraging AI and data—including requirements, compliance matrices and metrics, and qualitative insights—the idea is to create an environment that provides early warning systems and that detects potential issues well before the integration phase. This proactive approach mitigates integration risks, streamlines development processes, and creates a cleaner, more agile environment that improves time to market while maintaining high quality. In addition, the discussion introduces continuous development as a natural complement to continuous integration. By coupling iterative development with real-time feedback loops and harnessing open-source tools to optimize key phases like compile times and pre-integration testing, teams can accelerate the development lifecycle and proactively identify mismatches and regulatory non-compliance. The presentation ultimately explores ways and uses cases how AI and data-driven insights can reshape SDV software integration while fostering innovation, resiliency, agility and compliancy in automotive systems - all in alignment with COVESA’s vision for open, connected, and collaborative development.