What is LLM advertising and why could it reshape digital marketing?

LLM advertising is the placement of ads inside large language model environments, where users ask questions, compare options, and work through decisions in natural language.

ChatGPT ads open a new opportunity for advertisers: the chance to reach consumers inside one of the fastest-growing AI environments on the web. That alone makes this important for marketers. 

According to an EMARKETER forecast, AI search ads will claim a double-digit share of search budgets by 2029.

But the bigger story is that advertising is entering a space where user intent is expressed through conversations—not just clicks, content consumption, or keyword searches.

For years, search has been the closest thing marketers had to a direct line into intent. But LLMs are introducing a more conversational and context-rich version of that signal, one that’s reshaping how brands think about relevance, discovery, and performance.

So far, OpenAI has positioned ChatGPT ads cautiously. The company says ads are intended to support broader access to ChatGPT, while remaining clearly labeled, visually separated from answers, and governed by privacy, user-control, and safety guardrails. OpenAI has also emphasized that ads do not shape ChatGPT’s answers.

Recently, StackAdapt announced it’s offering access to advertising within ChatGPT, giving advertisers a way to start testing this new format through our platform.

The rollout is still controlled and early.  Even so, it signals the start of something larger: the arrival of advertising in AI-native environments.

That’s the real reason marketers should pay attention. LLM ads are yet another sign—after AI search—of a broader shift in how digital advertising evolves as AI becomes a more central part of how people research, compare, and make decisions.

How does LLM advertising change the intent signal?

LLM advertising changes the intent signal by adding conversational context to what users ask. Instead of relying only on a keyword, LLM ads can reflect the user’s question, prior context, decision stage, and stated need.

For years, digital advertising has treated keywords as one of the clearest signals of intent. Search became so valuable because it let brands respond to what people were actively looking for at high-interest moments.

LLM advertising changes that model. Instead of capturing a single query, it captures the context around it. 

“AI has context and history and deeper concepts,” says Yang Han, StackAdapt’s Co-founder and CTO. “Usually, you have a conversation with an AI, whereas in search, you just enter a few words or keywords. With AI, it can go a lot deeper in terms of understanding intent.”

That’s what makes LLM ads different from traditional search ads: 

• A keyword can show what someone wants in the moment. 
• A conversation can reveal why they want it, how far along they are in the decision process, and what kind of response would actually be useful.

This doesn’t make search irrelevant. Search will remain valuable because it’s simple, proven, and highly actionable. But LLM advertising points to a more context-rich version of relevance, one based not just on matching terms, but on understanding need more deeply.

For advertisers, LLM ads suggest a future where marketing can respond to what people mean, not just what they type.

How could LLMs become a powerful marketing channel?

LLMs could become a powerful marketing channel because people use them during high-intent moments: researching products, comparing options, narrowing choices, and working through decisions.

That makes them potentially valuable for marketers because they bring brands closer to high-intent moments.

“With AI, there’s a lot more deterministic signals, but you have the history as well,” says Han. “So you kind of get the best of both worlds. When it comes to advertising and marketing, it has way greater potential than any other channel we’ve seen on the market.”

Rather than interrupting passive consumption, LLM ads have the potential to appear alongside active problem-solving. If done well, that could make them more relevant, more useful, and ultimately more effective.

Over time, that opens up a much bigger opportunity. As these environments improve in relevance, personalization, and measurement, LLM advertising could become a meaningful layer across the customer journey, influencing not just discovery, but evaluation and decision-making, too.

Why the channel is still early

Marketers should evaluate early tests around four questions: what inventory is available, how ads are targeted, how performance is measured, and how results connect to the broader media mix.

The opportunity is real, but the channel is still taking shape. OpenAI has begun rolling out capabilities like conversion tracking, giving advertisers a clearer way to start measuring performance. Even so, formats and controls are still evolving, and the buying infrastructure is not yet as mature as other digital channels.

That matters because early promise does not automatically translate into scalable performance. For now, LLM advertising is best understood as an emerging space with strong potential, where marketers can begin testing, measuring, and evaluating how it fits into their broader marketing and advertising strategy.

When does LLM advertising become scalable?

LLM advertising becomes scalable when advertisers can activate, measure, optimize, and govern LLM ad inventory through the same planning systems they use for the rest of their media mix.

That’s where the programmatic question comes in.

Today, LLM ads are still closer to an emerging access point than a fully operationalized buying channel. As long as execution remains limited, advertisers will have a harder time integrating this inventory into broader planning, measurement, and optimization workflows.

Scalability begins when LLM advertising becomes easier to activate, measure, and connect to audience, creative, and budget strategies across channels. That’s what turns a promising environment into one that fits more naturally within modern media operations.

In that sense, programmatic infrastructure can play a major role in helping LLMs mature as an advertising channel. The more seamlessly LLM ads fit into the systems marketers already use to run omnichannel campaigns, the faster this moves from an interesting test to a more scalable opportunity.

How should marketers test LLM advertising now?

Marketers should test LLM advertising with clear goals, realistic expectations, and a plan to connect early learnings to broader media strategy.

The channel is still early, but that doesn’t mean marketers should wait on the sidelines. 

• Start testing early, but keep expectations realistic. Treat LLM advertising as a learning opportunity while the channel continues to evolve.
• Focus on use cases where intent is likely to be strongest. Prioritize categories, products, or moments where users are actively researching, comparing options, or working through a decision.
• Define success before launch. Decide upfront what you’re measuring, whether that’s engagement, clicks, assisted conversions, or directional performance signals.
• Use new measurement capabilities to learn. As OpenAI introduces tools like conversion tracking, marketers can begin assessing how LLM ads contribute to performance and where they fit in the broader mix.
• Use these tests to build internal knowledge. Pay attention to what kinds of messaging, offers, and user needs seem to resonate in LLM environments.
• Prepare your data and creative strategy. The long-term value of LLM ads will depend on how well brands can connect intent signals to audience strategy, and more adaptive creative.
• Think beyond the channel itself. Plan for how insights from LLM advertising could inform search, social, display, and broader omnichannel planning.
• Stay flexible. The market, product capabilities, and measurement standards are still evolving, so marketers should be ready to adjust quickly as the channel matures.

Why should LLM advertising be part of an omnichannel strategy?

LLM advertising should be part of an omnichannel strategy because conversational intent is most valuable when it informs the rest of the media mix.

Even if these environments become highly effective, they’ll still sit within a broader customer journey that spans search, social, display, video, and other touchpoints.

“You don’t want to execute in isolation,” says Han. “You want to execute holistically.” 

Because LLM ads can reveal richer intent in a conversational setting, marketers may be able to use those signals to better align messaging across channels, connect upper-funnel activity to lower-funnel outcomes, and make more informed budget decisions.

In that sense, LLMs belong inside an omnichannel strategy because they can add a clearer layer of intent to the rest of the media mix. 

Used well, that can help brands decide which audiences to prioritize, what kind of message to deliver, and where different channels are contributing across the journey. 

Rather than treating LLM advertising as a separate experiment, marketers should think about how it can improve cross-channel consistency, sequencing, and measurement.

What will separate winners in the new intent economy

In the new intent economy, advantage will come from how well brands translate conversational signals into media decisions, creative strategy, and measurable outcomes.

Advertisers must build the ability to interpret conversational intent and apply it across media, creative, and measurement.

That means treating LLM ads as part of a broader marketing capability. 

• Brands will need to connect these signals to creative strategy, measurement, and cross-channel execution. 
• They’ll need to understand the kind of need, question, or decision a user is working through, then respond with messaging and media strategies that match that moment.

Advertising in AI environments gives marketers access to a richer form of intent than they have typically had through keywords, clicks, or browsing behavior alone. Over time, that can reshape how brands define relevance, plan campaigns, and evaluate performance.

LLM advertising points to the beginnings of a new intent economy. As intent becomes more directly expressed through conversation, the brands that succeed will be the ones that turn that signal into stronger messaging, better coordination across channels, and more informed marketing decisions.

Talk to our team to learn how to start testing LLM advertising as part of your omnichannel campaigns.