Federal Reserve's Waller discusses FRED's evolution at FRED Con 2026

Summary

Governor Waller delivered a speech at the FRED Con 2026 conference, emphasizing the importance of the Federal Reserve's economic data platform, FRED, which he views as the greatest public good created by the Federal Reserve. Waller discussed how FRED has evolved since its inception in 1961, now hosting over 850,000 data series and reaching 18 million unique users in 2025. He also highlighted the role of artificial intelligence (AI) in enhancing data accessibility while acknowledging the associated risks, such as misattribution and bias, which FRED is actively working to mitigate. This conference aims to explore these opportunities and challenges, underscoring the Federal Reserve's commitment to providing reliable economic data to support informed decision-making in the market economy.

Analysis

Christopher J. Waller: Member of the Board of Governors of the Federal Reserve System, with prior roles including executive vice president and director of research at the Federal Reserve Bank of St. Louis. He delivered the keynote speech at FRED Con 2026, focusing on the evolution of economic data tools amid advances in artificial intelligence. Federal Reserve System: The central banking system of the United States, responsible for conducting monetary policy, supervising banks, and providing financial services. Governor Waller, speaking on behalf of the Federal Reserve, highlighted FRED as one of its greatest public goods and discussed ongoing efforts to adapt it for AI-driven data access. Public Data Service: The Federal Reserve continues to prioritize trusted, non-commercial distribution of economic data through FRED, ALFRED, and FRASER to support informed decision-making in the market economy. Data Platform Evolution: FRED is expanding its architecture to support AI agents through tools like the Model Context Protocol Connector, enabling better integration with external AI systems. AI Opportunities and Risks: Artificial intelligence is improving data summarization and accessibility for economic users while introducing challenges such as potential hallucinations, bias, and source misattribution that FRED is actively addressing.

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