LiveRamp today launches agentic AI upgrades enabling autonomous agents to build audiences, measure cross-media performance, and optimize ad spend with governed data access.
LiveRamp today announced the deployment of new agentic AI capabilities that allow specialized AI agents to autonomously execute marketing tasks - from audience building to cross-media measurement and spend optimization - directly within the company's data collaboration platform. The San Francisco-based company, listed on the New York Stock Exchange under the ticker RAMP, framed the March 3, 2026 launch as a step toward replacing manual, fragmented marketing workflows with governed, automated execution.
The announcement introduces two active agent integrations at launch. Newton Research agents are live today, enabling marketers to query LiveRamp's Cross-Media Intelligence using natural language questions and receive instant measurement insights. SemantIQ agents are also live today, allowing health and life science marketers to build and activate healthcare provider audiences directly from the LiveRamp Clean Room. Both integrations are the first of what LiveRamp described as many future partner agents to be brought onto the platform.
"We're making it possible for AI agents to do what marketers have been doing manually - build audiences, measure cross-media performance, and optimize spend - but faster and within the governed environment our customers already trust," said Matt Karasick, Chief Product Officer at LiveRamp. "The agents from Newton Research and SemantIQ are live today, and they're the first of many partners we're bringing onto the platform."
The March 3 launch builds on a January 2026 announcement in which LiveRamp signaled its intent to allow clients to license partner AI agents and applications through its platform. Today's release fulfills that commitment, moving from a stated roadmap to working integrations. Clients can now license partners' AI-powered agents, granting them governed access to premium data - all from a single central hub, according to the company.
That January signal itself followed a broader October 1, 2025 launch in which LiveRamp introduced three foundational AI capabilities: agentic orchestration, AI-powered segmentation using natural language prompts, and AI-powered search for the Data Marketplace. That announcement positioned LiveRamp as the first data collaboration platform to give AI agents governed access to its complete suite of marketing tools, which spans identity resolution, segmentation, activation, measurement, clean rooms, and a network of over 900 partners.
Then in January 2026, LiveRamp expanded its Data Marketplace to include data and models specifically designed for AI applications - licensing training datasets, accessing pre-built AI models, and deploying AI-powered applications through a governed infrastructure. Today's agentic deployment is the operational extension of that architecture: agents are not just accessible through the marketplace in theory but running production workflows today.
The progression matters because it reflects a deliberate build. LiveRamp is not launching an experimental pilot. The agents from Newton Research and SemantIQ are live, processing real queries and activating real audiences in the platform as of today.
Understanding what "agentic" means in practice here requires a closer look at how the two live partners operate.
Newton Research, founded by entrepreneurs who previously sold Data Plus Math to LiveRamp, specializes in advertising and media analytics. Its agents connect to LiveRamp's Cross-Media Intelligence system, which aggregates performance data across media channels. Marketers interact with the agents through natural language questions rather than structured query interfaces. The agent interprets the question, runs the appropriate analysis across LiveRamp's cross-media dataset, and returns measurement insights directly. Newton Research launched agentic AI analytics capabilities within Snowflake for advertising measurement on November 4, 2025, so this LiveRamp integration extends a measurement infrastructure already in production.
"LiveRamp and Newton Research have leaned in together to help marketers use AI to drive quantifiable performance increases, today," said John Hoctor, CEO and Co-founder at Newton Research. "As Newton Research unlocks media performance gains from analytics with specially-trained intelligent agents, and LiveRamp streamlines adoption of these next-gen agents, every marketer will be able to easily tap the power of AI as part of their everyday workflows."
SemantIQ addresses a distinct vertical challenge. Healthcare provider audience building has historically involved complex data licensing, compliance checks, and manual segmentation work. SemantIQ agents automate this process within the LiveRamp Clean Room, which already provides a governed, privacy-preserving data environment. Health and life science marketers can instruct the agent to build and activate healthcare provider audiences without manually assembling datasets or writing segmentation queries.
Access to these agent capabilities follows each organization's AI policies and the usage guidelines of the underlying AI provider, according to LiveRamp. This governance layer is not incidental - it is a deliberate design choice that distinguishes LiveRamp's implementation from open agent frameworks that place fewer constraints on autonomous execution.
Alongside the agent integrations, LiveRamp today introduced two additional platform capabilities that agents can leverage.
The first is enhanced lookalike modeling that draws across first-party, second-party, and third-party data sources simultaneously. This is technically distinct from lookalike models that draw only on first-party seed audiences or single data sources. By combining data tiers, the model can identify audience expansion candidates whose characteristics appear across multiple data contexts, not just within a brand's own CRM. Ananda Chakravarty, Research VP for Retail Insights at IDC, framed the significance directly: "Marketers have historically struggled with incorporating lookalike audiences due to three main friction points: data, workflow, and connectivity," Chakravarty said. "With this release, LiveRamp addresses these factors by sourcing from first-, second-, and third-party data, adapting to workflows, and ensuring seamless connectivity and activation across the ecosystem, resulting in a marketer focused solution."
The second capability is an identity-powered control group that applies consistently across surfaces and channels. Measurement via control groups has long suffered from inconsistency - control populations defined on one channel may not align with those used on another, making cross-channel attribution unreliable. LiveRamp's update applies a single identity-powered control group across all surfaces, meaning the control population is defined once and remains consistent regardless of where the campaign runs. This makes cross-channel incrementality testing more reliable, since the counterfactual baseline is the same whether measuring on connected TV, display, or social.
Both capabilities compound in value when accessed through agents. An agent that can continuously build and expand lookalike audiences using all three data tiers, while also managing a consistent control group across channels, can run persistent optimization cycles that would require significant manual coordination to replicate.
"Building a strong identity foundation has given us confidence in the accuracy, completeness, and precision of our data," said Austin Leonard, VP and GM of DG Media Network. "As we progress to applying AI-powered lookalike modeling to scale reach for our suppliers and advertisers, we're able to develop high-quality models that help us identify the right audiences and engage them in the ways they want to be reached."
Thomas Atkins, Executive Director of Media at MGM Resorts International, pointed to the privacy dimension: "With data security and consumer privacy protected at every step, we can use AI and data collaboration to model, build, and recommend higher-quality audiences with confidence, driving stronger marketing results and enabling us to scale more efficiently."
Today's deployment does not occur in isolation. The advertising technology industry has been assembling the infrastructure required to support autonomous agent-driven workflows since at least mid-2025, and LiveRamp has been a consistent contributor to that process.
On November 3, 2025, LiveRamp donated the User Context Protocol to IAB Tech Lab, establishing an open standard for how AI agents exchange identity, contextual, and reinforcement signals across advertising systems. The protocol uses dense vector representations of 256 to 1,024 dimensions to compress identity and contextual signals into formats fast enough for real-time inference. That donation is now part of IAB Tech Lab's AAMP initiative - a broader framework formally named in late February 2026 that consolidates agentic advertising standards across seven protocol components.
The scale of investment in this area has been substantial. McKinsey data indicates that $1.1 billion in equity investment flowed into agentic AI during 2024 alone, with job postings related to the technology increasing 985 percent from 2023 to 2024. Multiple platforms moved into agentic execution during fall 2025. PubMatic launched AgenticOS on January 5, 2026, with live campaigns already running across connected television environments. Amazon unified its advertising console and introduced AI agents for campaign management in November 2025.
The question for marketers has not been whether agentic infrastructure is coming - that direction is clear - but whether specific implementations are production-ready or still experimental. LiveRamp's framing today emphasizes production status. The Newton Research and SemantIQ agents are described as live, not in beta or limited preview.
LiveRamp's partnership with Scowtt, announced on February 20, 2026, adds further context. That integration targets a 40 percent or greater improvement in return on ad spend by combining Scowtt's predictive CRM-based models with LiveRamp's identity infrastructure. It represents the same pattern as today's agentic launch: external partners bringing specialized AI capabilities into the LiveRamp platform, with the platform providing the identity layer, governance, and data access that make those capabilities actionable.
Uber Intelligence, announced on December 8, 2025, is another example of the same ecosystem model, with Uber's behavioral data accessible through LiveRamp's clean room infrastructure. Today's announcement extends that partnership logic into the agentic layer.
The practical implication of today's launch is that marketers with access to LiveRamp can now direct AI agents to perform tasks that previously required manual effort, technical expertise, or both. Building a healthcare provider audience, which involves data sourcing, matching, and compliance review, can now be initiated through SemantIQ agents without manual query construction. Getting a cross-media measurement read, which previously required analysts to run structured queries against LiveRamp's Cross-Media Intelligence data, can now be accomplished through a natural language question to Newton Research agents.
That shift has staffing and workflow implications. Campaigns that previously required data science teams to set up segmentation, measurement frameworks, and control groups can now be executed more rapidly through agent-driven workflows. This is not a marginal efficiency gain - it reflects a change in where human judgment is applied in the campaign lifecycle.
The lookalike modeling update also carries direct competitive relevance. IDC's Chakravarty identified three friction points that have historically limited lookalike audience adoption: data access, workflow integration, and connectivity. LiveRamp's approach addresses all three simultaneously by sourcing from multiple data tiers, integrating into existing marketing workflows through agents, and enabling activation across the platform's network of partners.
Whether the agent governance layer - the requirement to access capabilities in alignment with organizational AI policies and provider usage guidelines - proves adequate for enterprise adoption remains an open question. The Federal Trade Commission warned in November 2024 that data clean rooms present complicated privacy implications, noting that most clean room services are not privacy-preserving by default without appropriate constraints. Autonomous agents operating within clean room environments will face similar scrutiny as the technology matures.
LiveRamp's platform currently reaches over 900 partners and serves over 835 direct customers globally, based on financial results reported for the first quarter of fiscal 2026, which showed total revenues of $194.8 million, a 10.7 percent increase year-over-year. That customer base represents the installed market into which today's agentic capabilities are being deployed.
Who: LiveRamp (NYSE: RAMP), headquartered in San Francisco, California, along with partner companies Newton Research and SemantIQ. Key executive Matt Karasick serves as Chief Product Officer. Supporting commentary comes from executives at DG Media Network, MGM Resorts International, and IDC.
What: The deployment of live agentic AI capabilities enabling autonomous AI agents to build audiences, retrieve cross-media measurement insights through natural language, and optimize campaigns within LiveRamp's governed data collaboration platform. The launch also includes enhanced lookalike modeling spanning first-, second-, and third-party data, and a single identity-powered control group applicable across all channels.
When: Announced and deployed on March 3, 2026, building on a January 2026 commitment to enable partner agent licensing, itself an extension of the October 1, 2025 agentic orchestration launch.
Where: The capabilities operate within LiveRamp's global data collaboration platform, accessible to clients and their AI agents through API integrations, spanning LiveRamp's network of over 900 partners worldwide.
Why: Marketers have been executing audience building, cross-media measurement, and spend optimization manually and in fragmented workflows. LiveRamp's agentic platform aims to automate these tasks through governed AI agents, reducing the technical overhead required for complex campaign operations while maintaining the data security and privacy controls that enterprise customers require.
