Displayce, a France-based technology company specialising in digital out-of-home advertising, today announced a suite of three specialised AI agents accessible through the Model Context Protocol, positioning itself inside the agentic workflows that media agencies are beginning to adopt at scale. The announcement was made on 25 June 2026 at the Cannes Lions International Festival of Creativity.

What Displayce is launching and why it matters

The company calls this new category Agentic DOOH - a framework in which specialised AI agents participate directly in media decision-making across the full campaign lifecycle, from interpreting a client brief through to generating post-campaign analysis. The three agents are accessible via MCP (Model Context Protocol), the open standard originally developed by Anthropic in November 2024 that has since spread rapidly across advertising technology infrastructure. As PPC Land has tracked through its coverage of MCP adoption across advertising platforms, Google, Amazon, Meta, Yahoo DSP, Microsoft, and DoubleVerify have all built on the protocol since late 2025. Displayce is now the first DOOH-specialist platform to expose its data and planning infrastructure via MCP to media agencies.

The core ambition is clear enough in principle but technically ambitious in execution: Displayce wants DOOH to become a native component of the agentic environments media planners already use to design, recommend, and optimise campaigns. That means agencies working inside ChatGPT, Claude, or other AI assistants would be able to query Displayce's DOOH data infrastructure directly from those environments without switching between tools or engaging a specialist DOOH sales team for an initial recommendation.

"DOOH is still too often treated as an execution channel. We want to turn it into a decision-making lever from the campaign design stage," said Laure Malergue, CEO of Displayce.

The distinction between execution channel and decision-making lever is more than semantic. DOOH has historically entered media plans late - after budgets have been committed to digital and broadcast channels, and often as a supplementary addition rather than a foundational element of planning. Displayce's argument is that the timing of the entry point, not just the quality of the inventory, is what constrains the channel.

The three agents in detail

Displayce's agentic suite is built around three distinct tools, each targeting a different stage of the campaign workflow.

The first agent addresses the planning stage. It takes a brief written in natural language - a description of campaign objectives, budget, target audience, and positioning - and generates a written and visual media recommendation within minutes. According to Displayce, the output includes a selection of programmatically available screens aligned with the brand's budget and objectives. The underlying data infrastructure draws on more than ten years of proprietary audience, mobility, contextual, and inventory data that Displayce has assembled across its programmatic DOOH operations. The process this agent is designed to replace is largely manual today and depends heavily on local market expertise. An agency planning a DOOH campaign across multiple European markets would typically require multiple contacts, multiple turnaround cycles, and multiple days to assemble what this agent aims to return in minutes.

The second agent focuses on campaign performance analysis. It analyses the results of a completed DOOH campaign, identifies the factors that drove effectiveness, and translates those findings into narrative reports that can be edited by agencies. Reporting on DOOH campaigns has traditionally required substantial manual effort. Performance data needs to be extracted from platform dashboards, contextualised against audience and mobility signals, and reformatted into client-facing documents. Displayce's second agent is designed to compress that process. The result, according to the company, is that agency teams can redirect time toward demonstrating strategic value to advertisers rather than spending it on report assembly.

The third agent targets the sales teams of DOOH media owners. It automatically transforms targeting strategies developed by experts into editable sales presentations ready to be delivered by commercial teams. Drawing on Displayce's data expertise and analysis of previous campaigns, it generates an AI-powered sales narrative adapted to the context of each pitch. Static materials replace nothing here - the agent's stated purpose is to produce dynamic, agency-focused presentations that respond to the specific context of each client conversation.

Together, the three agents cover the full arc of a media transaction: initial planning, post-campaign measurement, and the sales process that sits between inventory supply and media agency demand. Each targets a bottleneck that has historically made DOOH slower and more expensive to transact than comparable digital channels.

The technical infrastructure beneath the agents

Displayce describes more than ten years of programmatic DOOH expertise as the foundation for its agentic suite. The company has operated as a demand-side platform connected across 80 countries, as noted in PPC Land's coverage of JCDecaux's 2025 full-year results, where Displayce is identified as part of JCDecaux's programmatic ecosystem alongside VIOOH. That positioning gives Displayce access to a significant breadth of DOOH inventory data, including the contextual and mobility signals that underpin its agents' recommendation capabilities.

MCP functions as the communication layer that exposes this proprietary data infrastructure to external AI environments. The protocol specifies a standardised interface through which AI agents can query APIs and data sources without requiring custom integration work for each connection. An agency already working inside Claude Enterprise or another MCP-compatible AI environment can connect to Displayce's agents the same way it might connect to any other MCP server - by adding Displayce as a data source within its existing assistant. No separate DOOH-specific software interface is required, at least in principle.

The awards context Displayce cites in its announcement reflects genuine external recognition. The company received the Grand Prix Strategies de l'IA 2026 and the Technology Company of the Year title at the UK Media Leader Awards, both referenced in the press release as context for its position in the market.

The broader agentic advertising context

Displayce's announcement does not arrive in isolation. It lands at a moment when the advertising industry is building agentic infrastructure at a pace that has no precedent. The IAB Tech Lab's Agentic Advertising Management Protocol, or AAMP, was formally named on 26 February 2026, establishing the umbrella framework under which agentic advertising standards are being developed. AAMP covers three task forces - buyer agents, seller agents, and agentic audiences - and is built on existing industry standards including OpenRTB, AdCOM, and OpenDirect, extended with modern protocols including MCP.

The Ad Context Protocol (AdCP), a parallel initiative launched on 15 October 2025 by six companies including Scope3, Yahoo, PubMatic, and Optable, specifically builds on MCP to standardise how AI agents discover inventory, compare pricing, and activate campaigns across advertising platforms. Displayce's choice of MCP as the integration layer for its agents aligns it with both AAMP and AdCP, positioning the company within the emerging interoperability frameworks rather than operating as a proprietary silo.

Within DOOH specifically, VIOOH announced at Cannes Lions on 26 June 2026 that its Seller Agent had automated more than 100 curated private marketplace deal packages during the first half of 2026. VIOOH's agent targets the supply side of the transaction - it automates deal package creation in response to natural language campaign briefs from buyers. Displayce's first agent, by contrast, operates on the demand and planning side - it interprets a brief and generates inventory recommendations, rather than assembling a deal package for an existing brief. The two approaches address different parts of the same workflow, which means agentic DOOH may eventually involve multiple agents on both sides of each transaction communicating with each other through shared protocols.

The market trajectory supporting both announcements is consistent. According to VIOOH's 2026 State of the Nation report, programmatic DOOH is forecast to feature in 48% of all campaigns globally within 18 months, up from 34% over the preceding period. Average investment in programmatic DOOH is projected to rise 44% over the same period. US adoption is projected to reach 52% - the highest of any market surveyed. JCDecaux's Q1 2026 results, published on 5 May 2026, showed programmatic DOOH growing at 27.2% organically in the quarter - roughly twice the growth rate of DOOH overall. These numbers establish the demand context that makes Displayce's agentic bet relevant. Programmatic DOOH is scaling fast enough that the manual friction in planning and analysis has become a real constraint on growth.

The Gartner forecast and adoption caution

Displayce's announcement cites a Gartner forecast that 60% of brands are expected to use agentic AI systems by 2028. The figure signals rapid adoption beyond the experimentation stage, according to the company. That projection is worth contextualising. A separate Gartner prediction, from June 2025, estimated that more than 40% of agentic AI projects would be cancelled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls - a figure that has appeared repeatedly in advertising industry coverage as a counterweight to bullish adoption forecasts.

What this means in practice is that agentic AI projects face real selection pressure. The 60% adoption figure and the 40% cancellation figure are not necessarily in conflict - they suggest that adoption will be widespread but that a significant fraction of deployments will not survive evaluation against measurable business outcomes. For a company like Displayce, building agents that target specific, time-consuming manual tasks - brief-to-plan conversion, performance report assembly, sales deck generation - is a more defensible approach than agents whose value is diffuse or hard to quantify.

Publicis, one of the world's largest communications groups, is among the holding companies developing its own agentic offerings, according to Displayce's announcement. That competitive context is relevant. Holding companies building proprietary agentic infrastructure will likely integrate DOOH data from existing supplier relationships before evaluating new specialist integrations. Displayce's bet is that the quality of its proprietary DOOH data - audience, mobility, contextual, and inventory signals accumulated over more than a decade - creates sufficient differentiation to justify a separate MCP integration even within an agency environment that already has access to general-purpose AI tools.

"We believe that the future of AI in advertising does not lie in autonomous systems operating as black boxes, but in agents capable of bringing greater understanding, transparency and intelligence to media decisions," concluded Hayssam Soueidan, CTO of Displayce.

That positioning - transparency and explainability over autonomy - echoes concerns that IAB Tech Lab CEO Anthony Katsur raised in a December 2025 podcast interview, where he warned that the industry risked chasing agentic AI without resolving foundational transparency and accountability issues. Displayce's stated design principle of agents that explain their rationale, rather than simply returning a recommendation, addresses that concern directly, at least at the level of product philosophy.

What this means for media agencies and DOOH buyers

The practical question for agencies and media buyers is where Displayce's agents fit in the workflow they already operate. Agencies that have adopted MCP-compatible AI assistants for campaign work - and the pace of adoption is accelerating - can, in principle, add Displayce as a data source without significant integration overhead. The first agent would then allow a planner to feed a campaign brief into their existing AI environment and receive a DOOH media recommendation as part of the same session that might generate audience analysis or channel comparisons for other media types.

That integration prospect is significant because it addresses the timing problem Displayce identifies. DOOH enters media plans late, the company argues, because accessing DOOH recommendations requires switching to a specialist tool or engaging a specialist team. An MCP-connected agent that responds to natural language briefs inside the planning environment the agency already uses removes at least some of that friction.

Whether that friction removal translates into earlier DOOH budget allocation is a different question - one that depends on the quality of the recommendations the first agent generates and the trust agencies place in AI-generated DOOH plans relative to expert human recommendations. The second agent's performance analysis capability could contribute to that trust-building process over time. Agencies that can generate clear, data-grounded explanations of what drove DOOH effectiveness in a previous campaign are better positioned to justify DOOH investment in the next one.

The DOOH sector has been building programmatic infrastructure at a rapid pace over the past eighteen months. VIOOH and OUTFRONT's partnership in March 2026 opened approximately 25% of the entire US DOOH market to programmatic buyers. Firefly's integration with VIOOH in April 2026 added more than 60,000 moving screens to the supply-side platform's marketplace. VIOOH's deal with Abode Media in May 2026 brought residential building screens into the programmatic ecosystem. Inventory supply is not the constraint.

What has lagged is the planning intelligence layer - the tools and data that help agencies incorporate DOOH into campaign strategy early rather than treating it as supplementary inventory. Displayce's three agents are explicitly designed to address that gap. The outcome of the announcement at Cannes Lions 2026 depends on whether agencies adopt the MCP integration and whether the agents' outputs prove useful enough in practice to change planning behaviour. That is a test that will play out over the coming months, not at a festival.

Timeline

Summary

Who: Displayce, a France-based technology company specialising in digital out-of-home advertising, with more than ten years of programmatic DOOH expertise and a DSP operating across 80 countries. Key quotes attributed to Laure Malergue, CEO, and Hayssam Soueidan, CTO.

What: The launch of three specialised AI agents - a media planning agent, a campaign performance analysis agent, and a media owner sales presentation agent - all accessible via MCP, the Model Context Protocol. The company introduces the category name Agentic DOOH and positions the suite as enabling AI environments such as ChatGPT and Claude to query DOOH data and planning infrastructure directly.

When: Announced on 25 June 2026 at the Cannes Lions International Festival of Creativity.

Where: The announcement was made at Cannes, France. Displayce is headquartered in France and operates its DOOH platform across 80 countries.

Why: DOOH has historically been integrated into media plans at a late stage, after main budget decisions have been made. Displayce argues that making DOOH data accessible natively within agentic media planning environments - via MCP - moves the channel's entry point earlier in the planning process. The three agents target specific manual bottlenecks: brief-to-plan conversion, performance report generation, and sales deck creation. The broader context is a DOOH market where programmatic transactions are growing rapidly but the planning intelligence layer has not kept pace with inventory supply.