OpenAI Is Bringing Ads to ChatGPT. Here’s What It Means for Marketers

OpenAI is preparing to introduce advertising to ChatGPT. The company has confirmed it is exploring an ad-supported tier as part of its broader push toward profitability, which would make the world’s most widely used AI assistant a commercial media channel for the first time. For marketers, this is not a distant possibility to monitor. It is a structural shift worth thinking through now.

The question is not whether advertising will come to conversational AI. It is what form it takes, how users respond, and whether the inventory will actually deliver for brands or simply add another line to a media plan that nobody can properly measure.

Why Is OpenAI Moving Toward Advertising?

OpenAI is burning through capital at a rate that makes advertising an obvious pressure valve. Running large language models at scale is extraordinarily expensive, and a freemium subscription model alone does not cover those costs. The company has been open about its financial position, and the logic of ad revenue is straightforward: hundreds of millions of users who currently pay nothing represent significant untapped commercial value.

This is not a new story in tech. Google built one of the most profitable businesses in history by placing ads inside a tool people used for free. Meta followed the same playbook. The difference with ChatGPT is that the user relationship is more intimate. People do not just search on ChatGPT. They ask it to help them think, write, plan, and decide. That creates a very different context for commercial messaging.

OpenAI’s chief financial officer Sarah Friar confirmed in late 2024 that the company was exploring advertising as a revenue stream, though the company has been careful to frame it as exploratory rather than imminent. The signal is clear enough. The question for marketers is what to make of it.

If you want a broader view of how AI is reshaping the marketing landscape beyond just this development, the AI Marketing hub at The Marketing Juice covers the full picture, from tools and strategy to where the real commercial opportunities sit.

What Would Advertising in ChatGPT Actually Look Like?

Nobody outside OpenAI knows the exact format yet, but there are a few plausible models worth thinking through.

The most conservative approach would be sponsored responses, where a brand pays to have its product or service mentioned when a user asks a relevant question. If someone asks ChatGPT for the best project management tools, a sponsored result from a software company might appear alongside or within the organic answer. This mirrors the sponsored placement model that has existed in search for decades.

A more integrated approach might involve brand partnerships where ChatGPT draws on proprietary content or data from a paying partner when generating responses. This is closer to a content licensing or sponsorship model than traditional display advertising, and it would be harder for users to identify as commercial.

There is also the possibility of an ad-supported free tier alongside a clean paid tier, which is the model Spotify and others have used effectively. Users who pay get an uninterrupted experience. Users who do not see commercial content. This is probably the cleanest structural solution, because it preserves user trust on the paid side while monetising the free side.

What seems unlikely, at least initially, is banner-style or interruptive display advertising. The conversational format does not lend itself to that, and OpenAI has too much brand equity to risk with a clumsy implementation. The company has watched what happened to Twitter’s advertiser relationships when trust eroded quickly. They will be cautious.

How Is This Different From Search Advertising?

I spent years running paid search campaigns at scale, including a period at iProspect where we were managing significant budgets across dozens of verticals. One thing I learned early is that the format shapes the behaviour, and the behaviour shapes the value. A click on a search ad carries a very specific intent signal. The user typed something, which tells you a great deal about where they are in a decision process.

Conversational AI changes that dynamic considerably. When someone asks ChatGPT a question, the intent can be much harder to read. Are they researching? Deciding? Just curious? The same question, asked in different ways, can represent wildly different commercial moments. A search query is a snapshot. A conversation is a thread, and the context shifts as it develops.

This creates both an opportunity and a problem. The opportunity is that conversational context might allow for more precise targeting than keyword matching ever could. If a user has spent ten minutes discussing home renovation with ChatGPT, a well-placed mention of a relevant brand could land at exactly the right moment. The problem is that this level of contextual targeting raises significant privacy questions, and the regulatory environment around AI is still evolving.

There is also the question of user trust. Search users have been conditioned over two decades to understand that some results are paid. They may not extend the same tolerance to a conversational AI they have come to think of as neutral. The moment ChatGPT feels like it is selling something, the relationship changes. OpenAI knows this. How they handle disclosure and labelling will matter enormously.

For marketers thinking about how to stay visible in AI-generated responses more broadly, Ahrefs has published useful thinking on improving LLM visibility that is worth working through alongside this development.

What Does This Mean for Existing Ad Platforms?

Google should be paying close attention, and it almost certainly is. ChatGPT has already begun to erode the top of the search funnel for certain query types. People who used to Google a question and click through several results are increasingly asking ChatGPT directly and getting a synthesised answer. If OpenAI adds advertising to that interaction, it becomes a direct competitor to Google’s core business model, not just a complementary tool.

Meta’s position is more complicated. Social advertising works because of the targeting infrastructure Meta has built over years. OpenAI does not have that infrastructure yet, and building it would require data collection practices that would attract significant scrutiny. In the near term, ChatGPT advertising is unlikely to threaten Meta’s performance marketing dominance. Over a longer horizon, if OpenAI can build a compelling targeting model from conversational data, the picture changes.

For independent publishers and content businesses, the implications are already being felt before a single ChatGPT ad has run. If users are getting answers from AI rather than clicking through to articles, the traffic model that underpins digital publishing is under pressure. Advertising inside ChatGPT would accelerate that shift rather than reverse it.

I have seen this pattern before in different contexts. When I was building out agency capabilities in the mid-2000s, every new channel that emerged created a version of the same anxiety: does this replace what we do, or does it add to it? The honest answer was usually both. Some revenue migrated. Some new revenue appeared. The agencies that did well were the ones that understood the new channel on its own terms rather than trying to force it into existing frameworks.

Should Marketers Be Preparing for ChatGPT Advertising Now?

The short answer is: not by opening a new budget line. The longer answer is more interesting.

The brands that will perform well in any new ad environment are the ones that understand the user behaviour first. Before ChatGPT has even launched a formal ad product, marketers can be doing useful work. That means understanding how your target audience is already using ChatGPT, what kinds of questions they are asking, and what role the tool plays in their decision-making process.

It also means thinking about brand visibility in AI-generated responses more broadly. If ChatGPT is already mentioning competitors when users ask relevant questions, that is worth knowing. Moz has written about using LLMs for competitive research and gap analysis, which is a practical starting point for understanding where your brand sits in the AI information landscape right now.

There is also a content angle here. If sponsored responses or brand partnerships become part of the ChatGPT model, the brands with the richest, most authoritative content will likely have an advantage. OpenAI will not want to serve low-quality commercial content inside a premium user experience. The brands that have invested in genuine depth and expertise are better placed than those relying on thin, keyword-stuffed pages.

Early in my career, I was told there was no budget to build a new website for the company I was working for. Rather than accept that, I taught myself to code and built it myself. The lesson was not that resourcefulness beats budget. It was that understanding the tool deeply enough to use it yourself gives you a perspective that no briefing document can provide. The marketers who will do best with ChatGPT advertising are the ones who have already spent serious time inside the product.

The Measurement Problem Nobody Is Talking About

I have spent a significant portion of my career in rooms where people are arguing about attribution. It is one of the most consistently mishandled areas in marketing, and the arrival of conversational AI advertising is going to make it harder, not easier.

When I was at lastminute.com, we ran a paid search campaign for a music festival that generated six figures of revenue within roughly a day. The attribution was relatively clean because the path from ad click to purchase was short and trackable. Conversational AI creates a much longer, more diffuse influence chain. A user might encounter a brand mention in a ChatGPT conversation, leave without clicking anything, and then purchase three days later through a completely different channel. Standard last-click or even multi-touch attribution models will not capture that.

This is not a reason to avoid the channel. It is a reason to build the right measurement approach before committing budget. Incrementality testing, brand lift studies, and controlled experiments will matter more than click-through rates in a conversational ad environment. Marketers who have already moved away from vanity metrics will find this transition easier than those who are still optimising for cost-per-click.

The broader challenge is that OpenAI will need to provide some form of measurement infrastructure for advertisers, and whatever they build will shape how the industry thinks about effectiveness in this channel. Semrush has published guidance on AI and SEO that touches on some of the visibility measurement challenges that are already emerging, which is a useful frame for thinking about the broader attribution problem.

What the Effie Awards Taught Me About New Channels

Judging the Effie Awards gave me a useful vantage point on how the industry actually evaluates marketing effectiveness. The campaigns that win are not the ones that used the most channels or the newest technology. They are the ones where there is a clear line between a commercial problem, a strategic choice, and a measurable outcome.

Every time a new channel emerges, a certain type of marketer rushes to be first. There is a version of that instinct that is genuinely valuable, the people who learn the channel early and develop real expertise. But there is also a version that is just novelty-seeking dressed up as innovation, and it tends to produce expensive experiments with no clear learning.

ChatGPT advertising will attract both types. The marketers who approach it with a clear commercial hypothesis, a defined target audience, a realistic measurement plan, and a willingness to iterate based on evidence will extract value from it. The ones who add it to the media plan because it is new and defensible will waste budget and conclude the channel does not work.

The channel is not the strategy. It never has been.

For a broader perspective on where AI is genuinely creating commercial value in marketing, and where the hype is outrunning the reality, the AI Marketing section of The Marketing Juice is where I cover these questions in depth.

Which Brands Are Best Positioned?

Brand matters more in a conversational context than it does in a pure performance context. When a user is asking ChatGPT for a recommendation and a sponsored result appears, they will apply a different level of scrutiny than they would to a banner ad. They are in a problem-solving mindset. They want the best answer, not a paid placement. If the brand behind the sponsored result is one they already trust, that placement reinforces something real. If it is a brand they have never heard of, the commercial intent of the placement becomes more visible and more likely to create friction.

This means that brand-building investment, which has been under pressure from CFOs for years in favour of performance marketing, may turn out to have been quietly compounding in value. Brands that have maintained consistent presence and genuine reputation will have an advantage in conversational ad environments that pure performance brands will not be able to buy their way into quickly.

Equally, brands with strong content assets and genuine subject matter authority are better positioned. If OpenAI’s ad model involves surfacing authoritative brand content in response to relevant queries, the depth and quality of that content will determine whether the brand appears at all. HubSpot has written usefully about how different LLMs handle information, which is relevant context for thinking about how brand content gets processed and surfaced by these systems.

Niche brands with deep expertise in a specific domain are also potentially well-placed. A conversational ad environment rewards precision. If your brand genuinely has the best answer to a specific type of question, that is a more defensible position than being a generalist with a large budget.

The Bigger Picture

OpenAI bringing advertising to ChatGPT is a significant moment in the history of digital marketing, not because it is surprising, but because it marks the point at which conversational AI formally enters the commercial media ecosystem. The implications will take years to fully play out.

What I would caution against is treating this as either a threat to be feared or an opportunity to be seized immediately. Both reactions are premature. The product does not exist yet in any defined form. The user response is unknown. The measurement infrastructure is not built. The regulatory position is unclear.

What is worth doing now is building understanding. Use the product. Think about your audience’s relationship with it. Audit your brand’s current visibility in AI-generated responses. Moz has covered how to build AI tools into SEO workflows in ways that are relevant to this kind of preparatory work. And start thinking seriously about measurement, because the brands that figure out how to evaluate conversational ad effectiveness will have a genuine edge over those still arguing about last-click attribution.

The channel is coming. The strategy is yours to build.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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