Overview

What are the privacy governance challenges when AI agents share data, memory, and inferences with each other? We’ll continue exploring that question in the second session of agentic data minimization series, Agentic Data Flows: A Closer Look at Data Realities, Risks, and Safeguards, hosted by FPF’s Center for AI on Tuesday, December 15, 2026, from 9:30 to 11:00 am ET.

In our first session, Agentic Data Flows: Privacy, Data Minimization, and PETs in Agentic Deployment, we highlighted how agentic systems reshape privacy risks, introduced an agentic privacy risk taxonomy, and heard from practitioners on how agents break current static permissions and consent frameworks, among many other topics.

In this session, we will dive deeper into agentic data realities, related privacy risks, and safeguards. We’ll revisit how data is flowing through agentic systems, and then ask what’s known and unknown about related privacy risks? What are the existing safeguards? Of those safeguards, which are effective and enforceable today? What are the gaps and where do we need to go? We’ll explore what these questions mean for privacy and AI governance practitioners, agentic AI deployers, agentic AI procurers, and policymakers.

Stay tuned for upcoming speaker announcements. This discussion will be recorded, and the recording and a summary report will be published following the event.

This webinar is the second event in a four-part series on agentic data minimization from FPF’s Center for Artificial Intelligence, presented in collaboration with Working Paper. Find information about the first event here. 

This project is part of the Research Coordination Network (RCN) for Privacy-Preserving Data Sharing and Analytics, which is supported by the U.S. National Science Foundation (Award #2413978) and the Department of Energy (Award #DE-SC0024884).