Empowering Generative AI with Trusted Federal Data: Strategies for Quality & Usability

Generative Artificial Intelligence (AI) is rapidly transforming how the public interacts with federal statistical data. As AI systems increasingly draw on public datasets, ensuring that federal statistics are accurately and reliably represented has become a critical priority.

This webinar, hosted by the National Institute of Statistical Sciences and Federal Committee on Statistical Methodology, will present the findings and recommendations from the recent FCSM report, AI-Ready Federal Statistical Data: An Extension of Communicating Data Quality (FCSM 25-03) and some of the early work in this space.

The session will explore how agencies can prepare their data assets for seamless integration with generative AI tools and agent models, which rely on machine-understandable data to deliver accurate, context-rich responses to users. A key focus will be on the adoption of Model Context Protocols (MCPs)—emerging open-source standards designed to enable AI agents to retrieve, interpret, and utilize federal data in a controlled and standardized way. By enhancing APIs and metadata with MCPs and other AI-friendly features, agencies can ensure that both human users and AI agents have access to authoritative, high-quality statistical information.