How AI Agents Consume Data Products

Data products are curated, documented, and governed datasets designed to serve both humans and AI agents, offering a high-quality, trustworthy, and reusable foundation for analytics and artificial intelligence workloads. These products bridge the gap between raw data and business value by providing metadata, lineage, and access controls, enabling AI-driven decision-making and automation. Data architecture plays a crucial role in defining how data is collected, stored, and consumed, supporting efficient integration across systems and ensuring data quality and governance. With the shift towards agent-first data consumption, AI agents now directly access data products through programmatic means, bypassing traditional human interfaces, which allows for improved decision-making and insight generation. This transition emphasizes the importance of data governance to ensure compliance, transparency, and trust, especially in regulated sectors. The use of data lakehouses and federated data products facilitates AI-ready data access, enabling organizations to effectively manage decentralized data estates while avoiding vendor lock-in and preserving compliance. Starburst's approach, leveraging its lakehouse architecture, empowers AI agents by embedding the discovery, governance, and consumption of data products, thus aligning with the evolving needs of AI-driven business strategies.