Generative AI is gaining traction across industries, but its success relies heavily on the availability and quality of data. Data management and governance are critical components in building effective AI systems, with panelists highlighting challenges such as handling large volumes of data, ensuring compliance with regional regulations, and balancing real-time insights with security concerns. The ability to unlock the value of text data has been a key breakthrough, enabling businesses to leverage text data in powerful ways through retrieval-augmented generation (RAG). To achieve AI success, companies should start small, focus on achievable goals, and prioritize building strong data foundations. With data being the engine powering GenAI, tackling infrastructure roadblocks, data complexity, and security concerns first is crucial for unlocking its full potential.