What Is Ad Context Protocol (AdCP) and How Is It Shaping Programmatic?

For the past decade, the digital advertising ecosystem has been defined by the incredible speed and scale of real-time bidding. OpenRTB revolutionized our industry, moving us from manual insertion orders to automated, millisecond-level auctions. It was a necessary leap that brought unprecedented efficiency to the market.

However, while micro-efficiency has long been a core focus of programmatic trading, it isn't the only metric that matters. Indeed, we have seen advertisers place value elsewhere and focus a majority of their digital ad spend with Meta, Alphabet, and Amazon, who attract over half (55.8%) of total advertising spend outside of China. While the open web remains the place many consumers turn for news and content, these walled gardens have struck the right balance of consumer attention and targetable, measurable ad products to attract marketer investment.  

Buying workflow can be one thing the walled gardens get right, and at Equativ, we believe one solution to simplifying programmatic workflows lies in agentic advertising, where AI agents act as efficient intermediaries to buy and sell through structured conversations following a common language such as AdCP.

AdCP — an acronym that stands for Ad Context Protocol — is an open standard for advertising automation that enables AI agents to interact with advertising platforms through unified interfaces.

This empowers AI agents to reason about budgets and outcomes over weeks or months, rather than bidding on individual impressions in milliseconds. While OpenRTB is perfected for high-frequency trading, AdCP is built for campaign-level investment.

Think of it as the difference between day-trading and long-term portfolio management. As industry experts have noted, this protocol seeks to bridge the "intent gap" by allowing agents to negotiate parameters that rigid, static APIs simply cannot handle.

A common industry concern is whether AdCP is intended to replace the existing programmatic stack; however, the relationship is fundamentally symbiotic, as AdCP operates at the strategic campaign level while OpenRTB remains the standard for individual, millisecond-level impression execution.

This integration reflects a core industry reality highlighted by Anne Coghlan, Co-Founder and COO of Scope3: the vast majority of global ad spend still flows through direct relationships — such as traditional media, digital direct deals, and programmatic guaranteed — rather than open auctions. By standardizing these complex interactions, AdCP digitizes high-value relationships without removing human control.

We are already operationalizing this vision at Equativ with our Media Planning Agent, which enhances buyer efficiency and outcomes by automating the strategic discovery phase, while keeping decision-making human-led.

To provide you with some practical use cases of this protocol, a publisher can utilize an AI sales agent to negotiate and commit to a media buy via AdCP while continuing to use their existing ad server and infrastructure to deliver the actual ads. Similarly, an advertiser can deploy a buying agent to reason about budgets and relationships over months, securing a "commitment" (a digital insertion order) with a premium streaming platform. Once this relationship is established at the protocol level, the advertiser's existing Demand-Side Platform (DSP) can execute the individual bids through traditional programmatic pipes or through direct insertion orders.

As explained in the documentation, AdCP is an open standard for advertising automation that runs over MCP (Model Context Protocol) and/or A2A (Agent-to-Agent Protocol). This standard uses a layered conversation flow that enables flexible, strategic negotiation between agents.

Here’s how the process works:

• Capability Discovery: Buyer agents can discover available sales agents via a standardized adagents.json file. They can then query those agents about product availability. This eliminates weeks of manual back-and-forth, providing instant clarity on what’s possible and setting the stage for meaningful dialogue.
• Negotiation Layer: Agents use structured dialogue to discuss campaign parameters, timing, and outcome-based KPIs. Unlike static rate cards, this dialogue allows deals to be shaped around business intent, ensuring campaigns reflect strategic priorities rather than just available inventory.
• The Commitment Primitive: The protocol concludes in a mutual agreement (a "commitment") that functions as a programmatic insertion order. This is the moment when strategy becomes a binding agreement that both buyer and seller can rely on over the duration of the campaign.
• Creative & Measurement Sync: Agents exchange assets and establish reporting loops based on agreed-upon outcomes. This ensures campaign delivery and measurement remain fully aligned, without requiring changes to the existing ad servers, DSPs, or programmatic infrastructure.

In short, AdCP transforms strategic conversations into executable campaigns, bridging the gap between intent and action, and enabling AI agents to operate at the campaign level rather than bidding millisecond-by-millisecond.

The true promise of AdCP for advertisers is diversification without complexity. AdCP changes this dynamic by:

• Collapsing Execution Costs: It eliminates the need for dozens of different negotiations, allowing a single team to manage 20+ publishers without increasing headcount.
• Unlocking "Stuck" Budgets: AdCP enables meaningful diversification — a fundamental principle of investment safety — by lowering the barrier to entry for new partnerships. This allows for a partial reallocation of the billions currently concentrated within Alphabet, Meta, and Amazon due to operational constraints.
• Diversification Insurance: It serves as a safeguard against over-concentration in the triopoly and shifts in platform policies.

To sum up, by reducing the friction of entry into new environments, AdCP transforms media diversification from a resource-heavy burden into a scalable competitive advantage.

For publishers — especially those in the premium and CTV space — AdCP is a powerful tool to preserve value. Many high-end platforms, such as Netflix, HBO Max, and Disney+, have historically stayed away from open auctions to avoid the commoditization of their inventory.

• Preserving Differentiation: AdCP allows publishers to leverage proprietary data and unique formats without turning inventory into a commodity.
• Accessing New Demand: By speaking a standard protocol, specialized platforms become easily accessible to any advertiser using an AI buying agent.
• Outcome-Based Pricing: It enables pricing models based on actual business results rather than just CPMs.

Ultimately, AdCP empowers premium sellers to automate their direct-sales business at scale while maintaining the pricing integrity and exclusivity that their high-value environments demand.  All without giving up on programmatic.

To prevent the "black box" issues often associated with AI, AdCP is built for high-resolution auditability and managed as a neutral, open-source initiative by the AgenticAdvertising.org community. Rather than being a proprietary tool favoring any single vendor, the protocol is governed by a diverse working group of advertisers, publishers, and independent ad tech players like Equativ to ensure a "common language" that allows platforms to compete on a level playing field. 

The list of members includes companies like Scope3, Equativ, PubMatic, Yahoo, Triton Digital, AccuWeather, Butler/Till, LG Ads, Samba TV, and The Weather Company.

This open structure mirrors the protocol’s internal mechanics: because AdCP is based on structured conversations, every step — from discovery to final commitment — leaves a clear, inspectable trail. AdCP enables structured, loggable exchanges that can support audit trails and human-in-the-loop approvals, depending on implementation, allowing both buyers and sellers to verify that every campaign aligns with their specific outcome targets and brand-safety standards.

In summary, AdCP is a framework that lets AI agents translate strategic conversations into actionable campaigns. Rather than relying on rigid, one-off bid requests, it supports a structured, multi-step dialogue that mirrors how real media deals are made while leaving the actual ad delivery to the systems advertisers already trust.

That said, the protocol is currently in its early stages, with specifications and reference implementations being developed by the community at AgenticAdvertising.org. For advertising teams and marketing leaders, the "Innovator's Dilemma" is real: why adopt a standard before the entire ecosystem does?

The answer lies in the speed of the AI shift. As agentic infrastructure becomes the default for enterprise tasks, those who help shape these standards today will define the rules of engagement for the next decade. As industry debates highlight, the standardization of agentic demand is key to preventing a new era of proprietary "black boxes." 

At Equativ, our mission is to ensure that the future of advertising remains open and interoperable. In today's advertising landscape, AdCP is a vital step toward a world where technology doesn't just make transactions faster: it makes partnerships smarter.