LiveRamp donates User Context Protocol to IAB Tech Lab for agentic advertising

LiveRamp donated the User Context Protocol to IAB Tech Lab on November 3, 2025, establishing an open standard for how artificial intelligence agents exchange identity, contextual, and reinforcement signals across advertising systems. The donation marks a transition from proprietary development to industry-wide governance, addressing technical infrastructure needs as autonomous agents begin managing millions of advertising decisions per second.

According to Anthony Katsur, CEO of IAB Tech Lab, the organization received the protocol as part of its Open Source Initiative. The technology joins existing open-source projects including OM SDK, ads.cert, and Trusted Server in the IAB Tech Lab GitHub repository. Katsur announced the donation in a LinkedIn post, stating that artificial intelligence is experiencing its first true exponential surge and that open, interoperable standards will transform that surge into enduring business value.

The protocol emerged from recognition that artificial intelligence systems require fundamentally different communication methods than current advertising infrastructure provides. Text-based prompts prove too verbose and slow for real-time bidding, which demands sub-100 millisecond response times. Raw feature vectors lack semantic meaning and cannot transfer across independently developed systems. Proprietary formats prevent interoperability between buyer, seller, and measurement agents.

Embeddings replace text exchanges

UCP solves these challenges through embeddings—dense vector representations that compress thousands of data points into 256 to 1,024 dimensions. The compact format enables fast vector operations supporting real-time inference while capturing semantic relationships between similar intents and behaviors. According to technical documentation, embeddings can simultaneously encode who the user is, what they are doing, and how they have responded to past interactions.

The protocol defines three critical signal types that agents exchange. Identity signals encode user characteristics through hashed identifiers, behavioral segments, and historical patterns without exposing raw personal data. Contextual signals capture current user activity including content being viewed, device type, time of day, and real-time engagement patterns. Reinforcement signals represent user responses to advertising through impressions, clicks, conversions, and deeper engagement metrics that continuously improve model performance.

Traditional advertising systems position demand-side platforms as central hubs managing connections between advertisers and supply sources. The shift to agentic systems creates direct connections between AI agents and advertising touchpoints, potentially bypassing established programmatic infrastructure. Industry analysis published in July 2025 by Ari Paparo, founder and CEO of Marketecture Media, suggested that autonomous AI systems could automate campaign setup, targeting, and optimization functions currently handled by DSPs.

Three-phase implementation roadmap

LiveRamp structured UCP development across three distinct phases. Phase one establishes an agent interoperability layer enabling existing large language model agents to exchange structured marketing context through standardized inputs and outputs. The focus centers on context engineering, schema alignment, and real-time messaging between buyer, seller, and measurement agents.

Phase two introduces a context learning layer where deep learning models train on contextual and behavioral data exchanged through the protocol. These models learn to represent user journeys, ad impressions, conversions, and marketplace signals as dynamic embeddings that capture patterns across the advertising lifecycle.

Phase three implements an embedding intelligence layer where agents exchange embeddings rather than textual context. These embeddings encode understanding of user intent, campaign state, and performance. Agents sharing a compatible vector space can transfer these embeddings as memory between systems, enabling near real-time optimization without large prompt contexts.

The protocol builds upon and extends the Ad Context Protocol, which six advertising technology companies launched on October 15, 2025. ADCP defines the control plane for how agents interact with advertising platforms through signals activation, media buy, and curation protocols. UCP defines the data plane for how agents exchange embeddings that encode learned representations of users, contexts, and outcomes.

Technical specifications and governance

IAB Tech Lab will provide stewardship through a lightweight Commit Group governing UCP development. The organization plans to integrate existing relevant standards with the protocol, including the Data Transparency Standard for ensuring data quality and transparency. The Global Privacy Protocol and Transparency Consent Framework will ensure agents share data in privacy-compliant ways with proper signaling.

Technical documentation available on GitHub outlines protocol interfaces for APIs and schemas exchanging context, signals, and results. Context management strategies maintain scoped, composable context windows in large language model-driven agents. Embedding interoperability standards define shared embedding structures, dimensional alignment, and vector-space identity. Agent coordination flows establish request and response patterns for cross-agent actions.

Privacy and consent controls implement mechanisms for secure signal sharing, security and authentication, permissible uses, and time-to-live parameters for consented data. Agentic attestation ensures confidentiality and integrity of code and information accessed or executed through agents, including provenance and controlled execution environments. Token exchange and settlement enable agents to exchange tokens or perform value transfers for advertising events, supporting integration with emerging payment and attribution protocols.

Travis Clinger, Senior Vice President at LiveRamp, emphasized the need for governance that evolves in lockstep with innovation in a November 3 blog post. The company hosted artificial intelligence forums in London, New York, Seattle, and San Francisco during recent weeks, gathering executives and practitioners to explore how artificial intelligence reshapes marketing, identity, and the broader digital ecosystem.

Measurement and attribution systems

According to technical documentation, over 15 model categories across the advertising lifecycle will consume and produce embeddings exchanged via UCP. Audience discovery models transform campaign briefs into targetable segments using embeddings that encode demographic patterns, behavioral signals, and contextual preferences. Lifetime value prediction models generate user-level embeddings capturing purchase propensity, engagement likelihood, and long-term revenue potential.

Click prediction and conversion modeling systems consume contextual and identity embeddings to estimate user response probabilities. Creative optimization models process embeddings representing creative elements, user preferences, and performance history to recommend optimal ad variations. Multi-touch attribution models analyze embeddings representing user journeys across touchpoints to assign credit for conversions.

Incrementality measurement systems compare embeddings from exposed and control groups to isolate true advertising impact. Cross-media measurement models process embeddings that capture user behavior across television, digital, social, and retail channels to provide unified performance views. Budget allocation models consume performance embeddings and market condition signals to optimize spending across channels and tactics.

The protocol addresses long-standing challenges in consent management for autonomous systems. Consumer consent today operates through consumer-facing banners and policy pages. In environments where autonomous agents act on behalf of consumers, the industry must collectively agree on what consent means when a consumer's only point of contact with a company is through a single agent-to-agent interaction.

Industry investment patterns

McKinsey data indicates $1.1 billion in equity investment flowed into agentic AI during 2024, with job postings related to the technology increasing 985 percent from 2023 to 2024. Multiple advertising technology platforms introduced AI agent capabilities throughout 2025. LiveRamp launched agentic orchestration on October 1, enabling autonomous AI agents to access identity resolution, segmentation, and measurement tools. Adobe announced Experience Platform Agent Orchestrator on September 10 for managing agents across Adobe and third-party ecosystems.

Amazon introduced agentic AI capabilities on September 17, transforming marketplace management through systems that monitor accounts, optimize inventory, and manage advertising campaigns autonomously. Newton Research announced on November 4 a specialized advertising and media analytics agents integration with Snowflake Cortex AI, enabling brands to run media mix modeling and incrementality analysis directly within secure data environments.

Microsoft announced on May 14, 2025, that it would discontinue Microsoft Invest (formerly Xandr) effective February 28, 2026. According to Microsoft Advertising Corporate Vice President Kya Sainsbury-Carter, the company cited incompatibility between traditional DSP models and their vision for conversational, personalized, and agentic advertising futures.

The protocol launch generated industry discussion about whether advertising needs additional standards before addressing fundamental transparency issues. Lindsay Rowntree, COO at ExchangeWire, questioned whether agentic AI represents programmatic advertising promises repackaged with new technology during a podcast discussion. She noted that major platforms including Google, The Trade Desk, and Amazon DSP have not signed up for recent agentic protocols, potentially creating more fragmentation through new walled gardens.

Privacy and data protection frameworks

UCP specifications emphasize security of personally identifiable information through encryption. Privacy of user identity prevents participants from learning the identity of end-users not in their own dataset. Privacy of group membership ensures participants cannot determine which of their end-users are in computed overlaps. The protocol employs advanced technologies including Private Set Intersection and Trusted Execution Environments to guarantee data security throughout processing.

IAB Tech Lab maintains working group structures for industry participation in standards development. Groups focus on specific technical challenges across digital advertising sectors, including privacy technology implementation, measurement standards, and programmatic trading protocols. The organization emphasizes standardization to support efficient implementation and operation of advertising technologies across different platforms and environments.

The protocol complements IAB Tech Lab's Attribution Data Matching Protocol, launched for public comment on October 15, 2024. ADMaP enables advertisers and publishers to securely share and measure conversion data without compromising user-specific details, leveraging Privacy Enhancing Technologies to address signal loss limiting advertisers' ability to measure campaigns accurately.

Gartner predicted on June 25, 2025, that over 40 percent of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls. The research firm's January 2025 poll of 3,412 webinar attendees revealed uneven investment patterns, with 19 percent reporting significant investments in agentic systems while 42 percent made conservative investments.

Implementation challenges persist despite growing investment momentum. The transition from prompt-based advertising automation to embedding-based intelligence requires substantial technical infrastructure changes. Companies must develop capabilities for generating, managing, and exchanging embeddings at scale while maintaining privacy protections and regulatory compliance.

Timeline

• November 4, 2025: Newton Research launches agentic AI analytics app within Snowflake for advertising measurement
• November 3, 2025: LiveRamp donates User Context Protocol to IAB Tech Lab
• October 15, 2025: Ad Context Protocol divides advertising industry on agentic AI standards
• October 1, 2025: LiveRamp introduces agentic AI tools for marketing automation
• September 17, 2025: Amazon introduces agentic AI capabilities across seller platform
• September 10, 2025: Adobe launches Experience Platform Agent Orchestrator
• August 20, 2025: IAB Tech Lab launches Content Monetization Protocols for AI working group
• July 27, 2025: McKinsey identifies AI agents reshaping advertising landscape
• July 21, 2025: Agentic AI threatens traditional DSP business models says industry veteran
• July 16, 2025: IAB Tech Lab releases PAIR 1.1 protocol to simplify encrypted data matching
• January 29, 2025: IAB Tech Lab unveils technical standards roadmap for digital advertising in 2025

Summary

Who: LiveRamp, a San Francisco-based data collaboration platform company, donated the User Context Protocol to IAB Tech Lab, the global digital advertising technical standards-setting body led by CEO Anthony Katsur. The protocol development involved collaboration from industry stakeholders across advertising technology platforms.

What: The User Context Protocol establishes an open standard defining how intelligent agents in advertising exchange signals—identity, contextual, and reinforcement information—through compact, learned vector representations called embeddings. The protocol enables autonomous buyer, seller, and measurement agents to communicate efficiently while processing billions of signals per second in real-time advertising environments.

When: LiveRamp completed the donation to IAB Tech Lab on November 3, 2025. The organization announced the transfer through LinkedIn posts and blog content published that day. IAB Tech Lab immediately began governance through its Open Source Initiative, with plans for community-driven development continuing through 2026 and beyond.

Where: The protocol operates globally across digital advertising infrastructure, including demand-side platforms, supply-side platforms, data clean rooms, and measurement systems. Technical specifications reside in IAB Tech Lab's GitHub repository alongside other open-source advertising standards. Implementation will occur across multiple cloud environments, warehouses, and programmatic advertising platforms worldwide.

Why: The donation addresses urgent infrastructure needs as artificial intelligence transitions from passive tools to autonomous agents managing advertising operations. Current text-based exchanges cannot support the sub-100 millisecond response times required for real-time bidding. Proprietary formats prevent interoperability between independently developed agent systems. Standardized embedding exchange enables agents to share learned representations of users, contexts, and performance signals while maintaining privacy protections and supporting real-time optimization across fragmented advertising environments.