Preparing data for AI is less about chasing the latest models and more about building the right foundation. This involves creating robust, extensible platforms that unify and curate enterprise data for responsible, scalable use. While legacy systems were designed for specific, narrow needs, modern data platforms must be adaptive—capable of handling change, supporting governance, and enabling flexible, AI-driven architectures.
Join Tim Padilla of Datavid for a practical discussion of the art and practice of preparing enterprise data for AI—covering proven strategies, semantic foundations, and real-world lessons that drive readiness, velocity, and business value.