Sam Altman once referred to advertising as ChatGPT's "last resort".
For a long time, this statement was a form of restraint. OpenAI still positioned itself as a research company, an infrastructure company, and a company striving to democratize AI capabilities for everyone. Advertising, the most familiar monetization method of the old internet, was treated as a fallback option.
But the adoption of the advertising strategy came quickly.
On May 5, OpenAI launched the self-service advertising platform Ads Manager, allowing advertisers to place ads directly on ChatGPT or through agencies such as Dentsu, Omnicom, Publicis, WPP. This move came less than three months after the initial ad pilot on February 9.
While the platform is still in the testing phase, the direction is clear: ChatGPT is no longer just a conversational product but is also becoming an advertising inventory. OpenAI aims to achieve $25 billion in ad revenue by 2026 and push ad revenue to $1 trillion by 2030.
With a user base of 9 billion, ChatGPT has found that the path of offering free services is becoming increasingly challenging.
Annual Loss of Hundreds of Billions, Banking on Advertising
OpenAI is growing rapidly to a point where traditional internet companies find it hard to compare.
But it is also burning cash at a rapid pace.
HSBC analysts estimated by the end of 2025 that OpenAI may still face a funding gap of $207 billion by 2030. Its cloud and AI infrastructure spending could reach $792 billion between the second half of 2025 and 2030, and its long-term compute commitment could approach $1.4 trillion by 2033.
These figures explain why they are venturing into the advertising business.
Subscription revenue can prove user willingness to pay but is challenging to cover the inference costs for all free users. Enterprise APIs can contribute to cash flow but face price wars and model convergence. Capital financing can extend the company's life but dilutes equity, reintroducing the pressure of higher valuations internally.
Advertising is the fastest non-dilutive revenue stream. It doesn't require payment from free users, doesn't need market re-education, and is easier to pitch to investors.
According to Reuters, OpenAI's advertising pilot project achieved an annualized revenue of over $100 million within six weeks. The ads are only shown to free and Go plan users, do not impact ChatGPT response generation, and do not share user data with marketers.
Setting aside user privacy concerns for now, there is a more fundamental issue behind this strategy.
Ads are sold to free users, but advertisers are looking for paying customers.
ChatGPT has 900 million weekly active users, with approximately 50 million in paid subscriptions, resulting in a free-to-paid conversion rate of less than 6%. Since ads are only shown to free users, it means that OpenAI's ad inventory is entirely dependent on that 94% unwilling to pay.
The problem is that advertisers willing to spend $50,000 and up in ad campaigns often sell products not targeted at individual consumers. Enterprise software, SaaS tools, B2B services — decision-makers in these high-average-order-value categories are most likely ChatGPT's paying users. They spend $20 to $200 monthly on more powerful models and larger context windows, but their screens will never display ads.
Beyond audience mismatch, there is a deeper issue: even if ads successfully reach free users, can the usage scenarios of these users themselves support a high ad value?
High Intent Does Not Equal High Conversion
OpenAI's ad narrative is built on a core assumption: ChatGPT users enter conversations with real intent, making ad reach in these high-intent scenarios more valuable.
This assumption is only half correct.
For the past two decades, brands have been most eager to occupy the search bar because it represents intent. When a user searches for a hotel, it indicates a potential booking; searches for enterprise tax software indicate a likely purchase; searches for the best noise-canceling headphones mean the user is at the doorstep of a buying decision.
Google built its ad empire on this premise. With the emergence of ChatGPT, users now delegate the decision-making process directly to AI. This is more enticing and more alarming for advertisers than search ads. It's enticing because ChatGPT sees a complete demand scenario. It not only knows what the user wants to buy but also why they want to buy it. It's alarming because if AI provides the answer directly, users might not even glance at the search results page.
However, "help me buy a pair of running shoes" and "help me write an email" are two completely different intents. The former is a consumer scenario, while the latter is a productivity scenario. In the daily use of ChatGPT, the latter far outweighs the former. Users come here to write, translate, code, brainstorm, and manage emotions, frequently engaging in tasks that do not naturally translate to product purchases.
This directly impacts advertising effectiveness metrics. Advertisers are willing to pay a premium for high-intent purchase intent. Google search ads are expensive because users often enter the search box with a clear intent to buy, compare, book, or order. Meta ads are slightly cheaper, but they leverage social profiles and massive conversion data to algorithmically filter low-intent users into potential consumers repeatedly.
ChatGPT sits in the middle. It is more like a demand entry point than social media but harder to determine commercial intent than search. It is more private than search but harder to attribute. It can solve user problems but may not necessarily generate ad clicks.
This is also why OpenAI shifted from CPM (cost per mille) to CPC (cost per click), which is not just a product upgrade. Advertisers are not willing to pay based on the vision of the "next-generation search entry point" in the long term. They ultimately want to know, who brought in this click? Where did the conversion happen? How much of the budget should be allocated from Google, Meta, or TikTok to ChatGPT?
Category alignment is also a concern. Low-risk categories such as home, travel, education, and software tools can be tested first. High-profit categories are often highly regulated, such as finance, healthcare, insurance, and recruitment. If ChatGPT runs ads in these areas, the platform must bear not only advertising effectiveness risks but also risks of misinformation, discrimination, and compliance.
Google serves as a mirror. In the first quarter of 2026, Google's search advertising revenue was $772.5 billion. However, even so, Google's advertising placements in AI Mode and AI Overviews are still very cautious, and the standalone Gemini app has yet to formally display ads.
OpenAI's expansion into advertising is part of exploring broader business models for the entire large model race.
OpenAI aims to make users feel AI is intimate enough while convincing advertisers that there is sufficient commercial intent here. Once this balance goes awry, ChatGPT will lose both sides: users will find it impure, and advertisers will feel it cannot convert.
But the changes brought about by advertising are not limited to this; they are also reshaping the way brands compete.
The Shifting Focus of SEO
Over the past year, the anxiety of brands has been whether they will disappear from AI-generated answers. The market has framed this as SEO, but it is not fundamentally a new concept; it is simply the old search marketing anxiety repackaged in the AI era.
With the launch of OpenAI's Ads Manager, it directly hit this anxiety but also changed the direction of the anxiety.
In the age of ad blocking, the core issue of SEO is "how to enter the AI context." Brands vie to be referenced by models through product documentation, media coverage, third-party reviews, and community discussions, competing based on the quality of information and the degree of data structuring.
After the ad platform went live, precise traffic could be purchased directly, and brands no longer rely solely on organic references. However, the competitive focus did not return to the traditional "buy more exposure." Instead, it shifted from "how to enter AI's answer" to "how AI evaluates my product."
The reason is simple: after seeing an ad, the most natural next step for users is to ask AI, "Is this product any good?" The AI's response then becomes the true conversion gate. Advertisers can buy exposure, but they cannot buy AI's positive evaluation. If AI gives a negative evaluation based on publicly available data, every penny spent on ads accelerates user churn instead of driving conversion.
This means that brands need to establish a positive reputation within AI's evaluation system. Signals that AI can read, such as product quality, user review density, and coverage of third-party reviews, will have a greater impact on conversion than ad placement itself.
SEO is shifting from "entering the context" to "earning evaluation," which is also a trend worth noting after the launch of OpenAI's new advertising platform.
Not Advertising Is the Most Expensive Advertising in 2026
Speaking of OpenAI, one cannot help but mention its arch-rival, Anthropic, which is pursuing a completely different "advertising model."
On February 4, 2026, two days before the Super Bowl, Anthropic published a blog post stating that Claude will never run ads. No sponsored links, no third-party placements.
This statement itself is an expensive advertisement.
Super Bowl ads are not cheap, and Anthropic is spending a fortune to tell users that they do not advertise, essentially purchasing brand awareness without advertising.
Being ad-free has never just been a moral stance; it's also a business positioning. It tells enterprise customers, power users, and high-sensitivity scenario users that Claude's responses are not influenced by advertisers, Claude's product direction is not centered around ad inventory optimization, and Claude's revenue comes from what you pay.
The effect was immediate. Claude's ranking in the U.S. App Store soared from 42nd place at the beginning of the year. On February 28, following OpenAI's signing of a Pentagon contract that sparked the QuitGPT movement, Claude topped the U.S. App Store's free app chart for the first time, surpassing ChatGPT for the first time ever. Free active users increased by 60%, daily registrations quadrupled, and paying users doubled within a week.
Anthropic's revenue structure is completely different from OpenAI's: over 80% comes from enterprise customers, and annual recurring revenue has skyrocketed from around $9 billion to $19 billion. Enterprise tools like Claude Code and Cowork have contributed at least $1 billion in revenue. Anthropic doesn't need the ad value of free users; what it needs is the trust premium from enterprise customers that their data won't be used for ads.
Not running ads in this context is a precise business decision. By forgoing ad revenue, it strengthens the trust barrier with enterprise customers, supporting higher subscription pricing.
However, "not running ads" is not an eternal virtue.
Data from the Stanford AI Index shows that the cost of achieving GPT-3.5-level performance has decreased 280 times over two years, from $20 per million tokens in November 2022 to $0.07 in October 2024. If model capabilities continue to converge and an API price war breaks out, the enterprise subscription premiums enjoyed by Anthropic today may gradually erode. When model costs drop to a point where all competitors can offer similar performance, why would enterprise customers continue to pay more for Claude?
There is currently no definitive answer to this question, but time will provide the answer to this choice.
There Ain't No Such Thing as a Free Lunch
OpenAI chooses ads, while Anthropic chooses to turn not running ads into a premium. It may seem like two opposite paths, but they are both answering the same question: when the inference costs of AI products cannot be sustained long-term by a free model, who will foot the bill?
OpenAI's Ads Manager is not just an advertising product, it is also a signal that the AI industry is transitioning from free expansion to cost recovery.
However, OpenAI's chosen approach to stop the bleeding happens to expose the most fragile part of this business. It needs to rely on a user base with the least purchase intent to support ad pricing that is three times higher than Meta's.
This is not a problem that can be solved simply by user scale. Having 900 million weekly active users is a nice number, but if these 900 million people are using ChatGPT to write emails instead of to make purchases, advertisers will sooner or later vote with their feet.
Advertising can be a revenue stream for an AI product, but it should not be seen as the only answer. Because when a product's business model requires users to stay as long as possible and to expose as much intent as possible, that product ceases to be an assistant to the user and becomes an assistant to advertisers.
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