Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
System Design
Martin Fowler·Aug 27·5 min read
Making Your Data Ready for Agentic AI
TL;DR
To prepare data for autonomous AI agents, a structured approach is needed, including layers for trust, context, and access. This ensures agents can operate effectively on reliable data.
✦ Why It Matters
Implement data contracts today to ensure your AI agents operate on high-quality, trustworthy data.
Key Takeaways
- Establish data contracts to define quality expectations.
- Implement a context layer to clarify data meaning for agents.
- Ensure traceability for auditing AI decision-making processes.
- Create an access layer to control agent interactions with data.
Full Summary
For decades, data systems were designed for human analysts who could interpret and question data quality. In contrast, autonomous AI agents lack this critical judgment and act on the data provided without skepticism.
To make data suitable for these agents, a multi-layered approach is necessary: a foundational layer that ensures data trustworthiness, a context layer that imparts meaning to the data, and an access layer that governs how agents interact with the data. Continuous observability is essential to maintain data governance and provide an audit trail for decision-making.
This structured preparation not only enhances the reliability of AI outputs but also mitigates risks associated with poor data quality.