This panel explores the end-to-end challenges and opportunities of building AI systems on strong, secure, and responsible data foundations. We'll dive into modern approaches such as knowledge graphs, data mesh, RAG, fine-tuning, and prompt engineering, while covering essential pillars like data quality, security, and governance. The discussion will address how startups can access and structure data from day one, and examine the growing importance of responsible AI practices in an era where data fuels everything.