Data Standards for the Agentic Age

The digital advertising industry is entering exciting and uncharted territory. As artificial intelligence evolves from simple automation to sophisticated agentic systems capable of making millions of autonomous decisions per second, the ecosystem needs new infrastructure to support this transformation. LiveRamp has donated the User Context Protocol (UCP) to IAB Tech Lab, marking a pivotal moment in the development of open standards for the agentic web.

IAB Tech Lab is excited to bring the value of existing standards to the agentic conversation, starting with this donation, which becomes part of our Open Source Initiative . UCP joins other Tech Lab open-source innovations, such as OM SDK , ads.cert , Trusted Server , in Tech Lab’s GitHub repository. Open-source projects aren’t just about making code publicly available – they’re about establishing transparent, inclusive governance that ensures long-term trust and collaboration, which is why a lightweight Commit Group will govern UCP. To ensure agility and rapid adaptation, IAB Tech Lab will provide support for the contributors to the initiative and apply existing relevant standards to the UCP, such as the Data Transparency Standard , ensuring data quality and transparency, and both the TCF and Global Privacy Protocol to ensure agents are sharing data in a privacy-compliant way with proper signaling.

The advertising technology ecosystem continues evolving to address privacy, measurement, and automation challenges facing the industry.

This work will enable the industry to adopt and demonstrate the value of these new technologies quickly, and to contribute to open standards that define how intelligent agents exchange data and user context in a trusted and transparent way. UCP ( User Context Protocol ) is an open standard that defines how intelligent agents in advertising exchange signals—identity, contextual, and reinforcement information—that represent a consumer’s real-time intent and response to advertising.

Unlike traditional text-based exchanges, which are too slow for modern programmatic advertising, UCP leverages embeddings — compact, learned vector representations that efficiently encode complex signals in a privacy-preserving, interoperable format. Embeddings can be thought of as the universal language of AI systems. They map relationships between words, ideas, or images so the system can think in context, not just keywords. Rather than exchanging thousands of raw data points or verbose text descriptions, agents can communicate through dense vectors of 256-1024 dimensions that capture semantic meaning, enable transfer learning across systems, and support the sub-100ms response times required for real-time bidding.