LLM Advertising 101: How Brands Reach Customers Inside AI Conversations

What Is LLM Advertising?

LLM advertising means placing a clearly labeled sponsored message inside an interaction with a large language model (LLM) product, such as a chatbot, an AI assistant, or an AI-powered app. The ad is selected because it is relevant to what the person is talking about at that moment. It is not chosen because the person was tracked across other websites.

Three features separate it from older formats. First, the unit of context is the conversation, not the page or the profile. Second, the user has just stated what they want in their own words, which is a far clearer signal than a click or a pageview. Third, the placement sits next to a response the person is actively reading, so relevance and clear labeling matter more than they do on a crowded web page.

How LLM Advertising Differs From Search and Social

Search advertising matches ads to a typed query. Social advertising matches ads to a profile and a feed. LLM advertising matches ads to an ongoing dialogue. The comparison below summarizes the practical differences for a media buyer.

The last row matters most. People treat AI assistants as advisers, so an irrelevant or unlabeled ad costs more trust than it would on a search results page. That is why disciplined LLM advertising starts with relevance and disclosure, not reach.

Who Sells LLM Advertising?

The supply side is fragmented. Some large AI products are building their own ad programs. OpenAI, for example, opened self-serve ads in ChatGPT to all US advertisers on May 5, 2026, with no minimum spend. Beyond those first-party programs sits a long tail of AI apps, chatbots, and assistants built by independent publishers, most of which have no sales team and no way to reach brand budgets.

That fragmentation is the reason an intermediary layer is forming. Thrad describes itself as advertising infrastructure for AI conversations: a combined demand- and supply-side platform connecting brands to AI apps and chatbots through contextual, intent-based ads, always clearly labeled as sponsored and withheld from sensitive conversations. As co-founder Andrea Tortella puts it, the aim is to aggregate "conversational surfaces wherever they may be across the internet, across the walled gardens, across the long tail." For an advertiser, the practical meaning is one buying relationship across many surfaces instead of one negotiation per app.

How Is LLM Advertising Targeted Without Cookies?

Most LLM products have no third-party cookie trail to read, and many users are not logged in to anything an advertiser can see. Targeting therefore relies on context: the subject of the conversation, the stage of the decision, and the specifics the person states. A shopper who asks for a waterproof trail shoe under a set budget has told the system a lot more than a keyword ever could.

Andrea Tortella made the same point in a Beet.TV interview: "My take is that the future of the cookie is actually context." Our guide to intent-based targeting inside AI assistants goes deeper on how that works in practice.

What Brands Should Check Before Starting With LLM Advertising

• Labeling. Every placement should be clearly marked as sponsored. If a partner cannot show you how, move on. Our safety approach explains how Thrad handles this.
• Sensitive conversations. Ads should be withheld from health crises, finances in distress, and similar moments. Ask any partner for their exclusion policy in writing.
• Measurement. Click-through rates alone understate or overstate value, depending on the surface. Read how to measure AI assistant ad performance honestly before agreeing to success metrics.
• Control over placement. Know which surfaces your ads can appear on, and whether you can exclude the ones that do not fit your brand.
• Start small. The channel is young and benchmarks are thin. A short pilot with a clear question beats a large commitment based on projections.

Common Questions About LLM Advertising

Is LLM advertising the same as advertising on ChatGPT? No. ChatGPT is one product with its own ad program. LLM advertising is the wider category, covering ads across many chatbots, assistants, and AI-powered apps.

Will people see an ad in every conversation? No. Ads should appear only when a relevant, appropriate match exists, and not at all in sensitive conversations. Most exchanges will carry no ad.

Do I need new creative? Usually yes. Banner-style creative does not suit a conversation. Short, specific copy that answers the kind of question that triggers it works better, and our guide to chatbot advertising formats and best practices shows what that looks like.

Is it only for big brands? No. With self-serve options appearing and no minimum spend at some programs, smaller advertisers can test the channel with modest budgets.

Where LLM Advertising Is Heading

Expect three shifts. Formats will multiply beyond a single sponsored card, toward product-level and follow-up-style placements. Buying will move from direct deals to platforms that span many surfaces. And disclosure standards will tighten, as the IAB AI Transparency & Disclosure Framework and new state and EU rules already signal. Brands that learn the channel now, while competition is light, will set their own benchmarks instead of inheriting someone else's.

If you want the full picture of how this category fits together for brands and publishers, start with our pillar guide to conversational advertising. For a plain-language definition of the underlying technology, see generative AI advertising, explained. See how it works for publishers and for brands.