A Program Built Around the Workflow Gap
LiveRamp has launched its Agent Builders program, branded LAB, on June 17, and the framing tells you how the company reads the market. The program is designed to make it faster for partners to bring AI agents onto the LiveRamp platform, targeting the planning, measurement, activation, and data transformation workflows that sit between raw consumer data and a running campaign. Chief Product Officer Matt Karasick described the goal as continuing to make it easier for partners to bring agents onto our platform, unlocking more selection and easier deployment for customers prioritizing value and returns.
The strategic bet embedded in that framing is important. LiveRamp is not positioning agents as a way to gather more data, it already sits atop an enormous quantity of it. It is positioning agents as a way to solve the workflow problem, the persistent difficulty of turning data assets into repeatable, scalable outcomes. That is a mature diagnosis. Plenty of vendors have treated AI as a data acquisition story. LiveRamp is treating it as an orchestration story, and in a data rich, workflow poor industry like commerce media, orchestration is where the real friction lives.
The Founding Partners and Their Roles
The program launched with four founding partners, and each illustrates the specialization the model encourages. SemantIQ builds AI native workflows for healthcare provider audience building inside the clean room. Newton Research provides intelligent agents for analytics and media optimization across data environments. Akkio delivers an agentic workflow for audience discovery through activation. Datalinx automates first party data standardization and mapping. Rather than building every capability itself, LiveRamp is curating a marketplace of agents that plug into its platform, each attacking a specific slice of the data to activation pipeline.
The partner quotes reveal the shared theme of governed automation. Manik Khanna of SemantIQ stressed that AI agents can transform how healthcare marketing teams interact with complex data, but only if they operate within governed, auditable environments. Jon Reilly of Akkio described the value as a faster path from what audience should we target to a segment that is built, validated, and ready to activate. Joe Luchs of Datalinx pointed to delivering 99 percent plus data mapping accuracy in minutes. The consistent message is speed and accuracy under governance, which is exactly what enterprise buyers demand before they trust automation with real budgets.
Pilots Aimed at Commerce Media Networks
Running alongside the partner program, LiveRamp is piloting agentic AI specifically for commerce media networks, and the segmentation of those pilots is instructive. They span food delivery, targeting net new customer acquisition, purchase frequency, and reactivation, big box and specialty retail, focused on product launches, basket expansion, and loyalty, and grocery. Each pilot is tied to concrete business goals rather than vague promises of AI transformation. That specificity matters, because it means the pilots can be judged against measurable outcomes rather than aspirational narratives.
The problem the pilots address is a real one. Commerce media networks hold genuinely differentiated assets, first party transaction data, direct consumer relationships, and media inventory positioned close to the point of purchase. Yet they have struggled to turn those assets into repeatable, scalable advertiser outcomes. The pilots layer automated orchestration on top of existing clean room environments, APIs, and interfaces, connecting consumer insight to campaign activation, measurement, and optimization. In other words, they attack the last mile between having valuable data and reliably producing advertiser results, which is precisely where so many retail media efforts stall.
Why Clean Rooms Plus Agents Is the Right Architecture
The architectural choice to build agents on top of clean rooms rather than around them is worth dwelling on. Clean rooms exist because commerce media runs on sensitive consumer data that must be handled within strict privacy and governance boundaries. Any automation that ignores those boundaries is a non starter for serious retailers and brands. By layering agentic orchestration on top of the existing clean room, API, and interface infrastructure, LiveRamp keeps the governance intact while adding the automation. The agents operate inside the guardrails rather than bypassing them.
This is the pattern we expect to win in regulated, data sensitive domains generally. The naive version of enterprise AI bolts an agent onto a data source and hopes the governance sorts itself out. The durable version embeds the agent inside the existing controls, so that speed does not come at the cost of compliance. SemantIQ's insistence on governed, auditable environments is the same principle stated from the partner side. In commerce media, where a privacy misstep can be both a regulatory and a reputational catastrophe, building automation that respects the clean room is not a constraint, it is the entire point.
The Broader Signal for Retail Media
LiveRamp's moves are a useful barometer for where retail media is heading. The category has grown explosively, becoming an operational necessity rather than a growth experiment, but its next phase depends on solving the efficiency problem. There are too many manual steps between a retailer's first party data and an advertiser's activated, measured campaign, and that friction caps how much of the opportunity actually gets captured. Agentic automation is the industry's bet on collapsing those steps, and LiveRamp is positioning itself as the neutral platform on which that automation runs.
The neutrality point is strategically deliberate. Karasick emphasized building neutrality and trust into data collaboration, and in an ecosystem where retailers, brands, and platforms are often wary of each other's motives, a neutral orchestration layer has real value. We would watch whether the pilots produce the measurable outcomes they are scoped against, because that is the test that separates genuine capability from marketing. If agents can reliably compress the data to activation cycle inside governed environments, the productivity gain for commerce media networks would be substantial, and LiveRamp would have a defensible position at the center of it.
What Retail and Brand Leaders Should Take Away
For retail and brand technology leaders, the practical lesson is to reframe the retail media problem as a workflow and orchestration challenge rather than a data collection one. Most established retailers are not short on first party data. They are short on the repeatable, governed processes that turn that data into consistent advertiser value at scale. Evaluating partners on their ability to automate that pipeline, within privacy controls and with measurable outcomes, is a more useful lens than chasing whoever claims the largest data set or the flashiest AI.
We would also encourage leaders to treat governance as a feature, not a friction. The partners LiveRamp assembled all foreground auditability and control, which reflects an understanding that in commerce media, trust is the currency that makes collaboration possible. The organizations that succeed in the agentic phase of retail media will be the ones that pair automation with rigorous governance, delivering speed without sacrificing the privacy discipline that regulators and consumers increasingly demand. LiveRamp is betting that combination is the winning formula, and the bet looks well aimed.
