Buying advertising on AI platforms

AI platforms are a new advertising channel. When someone asks an AI assistant for a product recommendation, searches an AI-powered engine, or interacts with a generative experience, there is an opportunity to show them something relevant and useful from your brand. That is AI media. But it works differently from anything you have bought before. There is no creative to upload. There is no audience segment to target. Instead, you give the AI platform everything it needs to represent your brand well — your products, your brand voice, your rules — and the platform generates the right message in the right moment. The platform is talking to the user. It knows the conversation, the intent, the context. Your job is to make sure it has great material to work with. This guide is for anyone on the buy side: agency trading desks evaluating a new channel, brand leaders rethinking their media approach, and small businesses looking to reach customers where they are increasingly spending time.

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Why existing approaches fall short

The tools and workflows built for traditional digital advertising do not transfer to AI media. Insertion orders assume you are trafficking finished creative into predetermined placements. AI platforms generate creative on the fly from your data — there is nothing to traffic. Programmatic buying sends a thin signal (a page URL, a device type, maybe a user ID) to a remote decision-maker. That decision-maker lacks the conversation context that makes AI advertising work. The platform closest to the user has the context. Sending bid requests away from that context is the wrong direction. Direct deals can work for a single platform, but every AI platform has its own API, its own data requirements, its own reporting format. Building custom integrations with each one is the same fragmentation problem the industry spent a decade solving in programmatic. AdCP exists because there is no legacy approach that works here. It is a standard protocol for pushing your data into AI platforms so they can generate effective ads on your behalf.

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The shift: from campaigns to ingredients

In traditional advertising, the buyer’s job is to set up campaigns and build creative. In AI media, the buyer’s job is to provide ingredients and define goals. Think about who has the most information. The AI platform is the one in conversation with the user. It knows what the person asked, what they care about, what they have already discussed. You know your brand, your products, your goals. The protocol connects these two sides: you push your ingredients in, and the platform assembles the best possible outcome. This pattern is not unique to AI. Retail media already works this way — you push a product feed into a retailer’s platform, and the retailer merchandises your products to the right shoppers. AI media extends this to conversational and generative experiences across every AI platform. The difference is that AI platforms can do more with your data: generating custom responses, making contextual recommendations, and even handing off to your own brand agent for a full product consultation. The better your ingredients, the better the results. This is the single most important thing to understand about AI media.

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What you provide

Everything you push into an AI platform is a building block the platform uses to create, target, and optimize ads. These fall into a few categories.

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Product and service catalogs

Your catalog is the foundation. The platform generates ads from what is in your catalog — it cannot recommend products it does not know about. If you already maintain a product feed for Google Merchant Center, a Shopify store, or any e-commerce platform, you have a catalog. The richer the data — detailed descriptions, multiple images, structured attributes — the better the platform can match your products to user intent.

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Brand identity

Your voice, visual guidelines, and positioning tell the platform how to sound and look when representing your brand. Without this, the platform generates generic sponsored content. With it, the output reflects your actual brand.

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Content standards

Your suitability rules define where and how your brand can appear. Push these into the platform and the AI enforces them at generation time — before the ad is ever created. This is fundamentally different from traditional brand safety, which classifies content after it is published and blocks what fails. In AI media, your rules are constraints on the generation process itself. Unsuitable content is never produced. This is a stronger guarantee than any post-hoc vendor can offer.

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Conversion events

Your real business outcomes — purchases, sign-ups, store visits — tell the platform what success looks like. The platform uses these to optimize toward the results that matter to your business, not just clicks or impressions.

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Optimization goals

On each campaign, you define what “good” means: a target cost per engagement, a cost per conversion, a return on ad spend. The platform optimizes toward these goals using your conversion data and catalog performance.

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Measurement does not change

AdCP changes how you buy media, not how you measure it. Your existing measurement stack — media mix modeling, mobile measurement partners, multi-touch attribution, incrementality testing — works the same way. AI media is a new channel in your media plan, not a new measurement paradigm. The protocol does make measurement easier in one specific way: because you push conversion events into platforms via sync_event_sources, the platform can optimize toward your real business outcomes instead of proxy metrics. But how you evaluate whether that spend was worth it uses the same tools and frameworks you use today.

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Getting started by role

The path into AI media depends on your organization’s size and structure. The underlying pattern is the same — provide ingredients, define goals, let the platform closest to the user do its job — but who handles each step varies.

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Brands with agencies

Your primary job is data quality. The effectiveness of your AI media campaigns depends directly on what you push in. That means:

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Agencies and trading desks

A buyer agent fills the same role in AI media that a DSP fills in programmatic — but it is not limited to programmatic. It sits alongside your DSP. Your existing programmatic stack, measurement, and reporting do not go away. You add a buyer agent that can reach AI platforms, and over time, it can reach any channel where sellers implement the protocol. A buyer agent connects to any AI platform that implements the protocol. It pushes client data in (catalogs, brand identity, content standards, conversion events), discovers available products, executes campaigns, and pulls delivery reports — across every platform, through one interface. What you build once works everywhere. A new AI platform launches and implements the protocol? Your buyer agent can activate there immediately. Build on the AdCP SDKs. When the protocol version advances, upgrading is as straightforward as updating your SDK dependency — not rewriting integrations. The first agencies with working buyer agents will capture client demand faster than those negotiating direct deals platform by platform. The work your clients need from you changes too. Instead of building and trafficking creative, you are curating the ingredients that make AI-generated ads effective. The strategic value shifts from execution mechanics to data quality and goal-setting — which gives your agency more leverage and more automation, not less.

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Small and mid-size businesses

What if you could advertise on AI platforms without hiring a standalone agency for operational execution? The protocol makes this possible. You work through a partner — an ad network, a platform integration, or a tool built into the commerce platform you already use — and the partner handles the protocol plumbing. You could also work with an agency that focuses on creative and strategy rather than one you are paying to manually set up campaigns across platforms. Your job is straightforward:

• Provide a good product feed. If you sell on Shopify, Etsy, or any e-commerce platform, you already have one. Make sure descriptions are detailed and images are high quality.
• Set up your brand basics. Your name, logo, voice, and any rules about where your brand should or should not appear.
• Define what success looks like. Sales? Store visits? Sign-ups? Your partner needs to know what to optimize toward.

The partner handles everything else: connecting to AI platforms, pushing your data in through the protocol, managing campaigns, and reporting results back to you. To find a partner, browse the member directory or ask Addie — tell her what platform you sell on and what you’re looking for, and she’ll help match you with the right company.

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