By Ronan Shields  •  March 3, 2026  •

Ivy Liu

The announcement positions Criteo’s demand platform as the connective layer between brands and OpenAI’s early-stage ad environment. In practical terms, marketers using ChatGPT will be able to tap Criteo’s commerce data and activation tools as part of OpenAI’s experimental monetization framework, extending Criteo’s reach beyond retailer sites and the open web into conversational interfaces.

The partnership builds on Criteo’s broader thesis, i.e., that LLMs will require structured, transaction-linked commerce signals to support monetizable discovery as generic web-crawl data is insufficient for high-quality product recommendations.

In late 2025, Criteo teased some of its early experiments with LLM — at that point, the partnership between the pair hadn’t been confirmed publicly — which involved piping signals such as product relevance, trendiness, and retailer-level performance into LLM environments via its Model Context Protocol server, effectively allowing AI agents to query Criteo’s APIs when generating recommendations.

“The capability in the engine drives the full funnel… our deep learning capability can make sense of scattered interactions to uncover product recommendation opportunities,” said CEO Michael Komasinski speaking at the time, underscoring the company’s argument that its two decades of recommendation modeling give it an edge in a commerce ecosystem mediated by AI.

Internally, Criteo has been embedding AI into campaign setup and optimization workflows, with tools such as its “audience agent” allowing marketers to describe objectives in plain language. Through MCP integrations, those workflows can now be executed from within LLM interfaces, rather than solely inside Criteo’s native UI.

Chief product officer Todd Parsons has also framed the shift as an evolution of the company’s earlier shift towards commerce media, a conversation that proved crucial in the early part of the 2020s, as traditional static identifiers, crucial to Criteo’s retargeting roots, were challenged. “In the past, you would have to look up our taxonomy, and you would have had to select or deselect a load of audience attributes,” he earlier explained, arguing that AI now collapses those manual planning steps.

Commercially, the contours remain fluid. Criteo executives have referenced models ranging from data licensing and pay-per-query structures to native ad formats within LLMs. But strategically, the direction is clear: if conversational AI becomes a primary “shop window,” Criteo intends to supply the recommendation infrastructure behind it.

For a company long associated with retargeting — and more recently with retail media and post-cookie reinvention — the OpenAI pilot offers validation of its attempt to reposition itself as the commerce intelligence layer for an agentic era.

As detailed in Digiday’s earlier coverage of its LLM experiments, the bet is not that AI displaces ad tech, but that it reshapes where ad tech operates — shifting the front end to AI while vendors like Criteo power relevance behind the scenes.

The development is likely to assuage investor concerns, which may have been raised after the company earlier reported a 2% dip in its Q4b revenues ($541 million), with its top-line guidance for Q1 revenue – excluding traffic acquisition costs this was estimated to be in the range of $245 million to $250 million – considered to be relatively soft by the markets.

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