Text | Kaori

Editor | Sleepy

Sam Altman once called advertising ChatGPT’s “last resort.”

For a long time, this was a form of restraint. OpenAI still brands itself as a research company, an infrastructure company, and a company trying to popularize AI capabilities for everyone. Advertising, the most familiar monetization method of the old internet, was seen as an alternative.

But the shift to advertising came quickly.

On May 5, OpenAI launched the self-serve Ads Manager platform, allowing advertisers to place ads directly or through agencies like Dentsu, Omnicom, Publicis, WPP on ChatGPT. Less than three months after the initial ad pilot on February 9.

The platform is still in testing, but the direction is clear: ChatGPT is no longer just a dialogue product; it’s also becoming an ad inventory. OpenAI aims to reach $2.5 billion in ad revenue by 2026 and push ad income to $100 billion by 2030.

With 900 million users, ChatGPT finds that the free route is becoming increasingly difficult.

Annual losses of hundreds of millions, recovering through ads

OpenAI is growing rapidly, so fast that traditional internet companies find it hard to compare.

But it also burns money quickly.

HSBC analysts estimate that by the end of 2025, OpenAI could still face a funding gap of $207 billion. Its cloud and AI infrastructure expenses from late 2025 to 2030 might reach $792 billion, with long-term compute commitments possibly approaching $1.4 trillion by 2033.

These figures explain why they are building out their advertising business.

Subscription revenue proves users are willing to pay but struggles to cover the reasoning costs of all free users. Enterprise APIs can generate cash flow but face price wars and model convergence. Capital funding can extend life but dilutes equity and pushes higher valuation pressures back into the company.

Ads are the fastest non-dilutive revenue source. They don’t require free users to pay, don’t need to re-educate the market, and are easier to pitch to investors.

According to Reuters, OpenAI’s ad pilot has generated over $100 million annualized revenue in six weeks. Ads target only free and Go plan users, do not affect ChatGPT responses, and do not share user data with marketers.

Setting aside user privacy, there’s a more fundamental question behind this strategy.

Ads sold to free users, but advertisers want paying users

ChatGPT has 900 million weekly active users, about 50 million paid subscribers, and less than 6% conversion from free to paid. Since ads are only for free users, OpenAI’s ad inventory comes entirely from the 94% who are unwilling to pay.

The problem is, advertisers willing to spend at least $50k usually aren’t selling to individual consumers. Decision-makers for enterprise software, SaaS tools, B2B services—these high-ticket categories—are most likely to be ChatGPT’s paying users. They spend $20 to $200 a month on better models and larger context windows, and their screens will never show ads.

Beyond audience mismatch, there’s a deeper issue: even if ads reach free users effectively, how much ad value can their usage scenarios support?

High intent doesn’t equal high conversion

OpenAI’s ad narrative is built on a core assumption: ChatGPT users enter conversations with genuine intent, making high-intent ad targeting more valuable.

This assumption is only half correct.

Over the past twenty years, brands most wanted to dominate the search box because it represents intent. Searching for a hotel suggests booking; searching for tax software indicates procurement; searching for the best noise-canceling headphones shows the user is at the decision-making threshold.

Google built its ad empire on this. After ChatGPT appeared, users directly entrust decision processes to AI. This is more enticing and frightening for advertisers than search ads. The allure is that ChatGPT sees a full demand picture; it not only knows what users want to buy but also why they buy it. The danger is, if AI provides direct answers, users might skip the search results page altogether.

But “help me buy a pair of running shoes” and “help me write an email” are two entirely different intents. The former is a consumption scenario; the latter is productivity. In daily use, the latter far exceeds the former. Users come here to write, translate, code, plan, and organize emotions—high frequency, but not naturally linked to product purchases.

This will directly lower ad effectiveness metrics. Advertisers are willing to pay high prices for high-certainty purchase intent. Google search ads are expensive because users often have clear intent to buy, compare, book, or order. Meta ads are cheaper but leverage social profiles and vast conversion data to repeatedly filter low-intent users into potential consumers.

ChatGPT sits in the middle. It’s more like an entry point for needs than social media, but harder to judge commercial intent than search. It’s more private than search but harder to attribute. It can solve user problems but may not generate ad clicks.

That’s why OpenAI shifting from CPM (cost per thousand impressions) to CPC (cost per click) isn’t just a product upgrade; advertisers are reluctant to pay long-term based on “next-generation search.” They’ll ultimately ask: who brought this click? Where did the conversion happen? How much budget should be shifted from Google, Meta, TikTok to ChatGPT?

Category fit is also an issue. Low-risk categories like home, travel, education, and software tools can experiment first. High-margin categories, often heavily regulated—finance, healthcare, insurance, recruitment—pose risks beyond ad effectiveness, including misinformation, discrimination, and compliance.

Google’s approach is a mirror. In Q1 2026, Google’s search ad revenue hit $77.25 billion. Yet, even so, ad placements in AI Mode and AI Overviews remain cautious; the independent Gemini app still doesn’t have formal ads.

OpenAI expanding into advertising is exploring broader business models for the entire large model track.

OpenAI needs to make users feel AI is close and familiar, while convincing advertisers there’s enough commercial intent. If this balance tips, ChatGPT risks losing both: users may see it as impure, advertisers as unconvertible.

But the changes brought by advertising go beyond that; they are reshaping how brands compete.

GEO’s focus is shifting

Over the past year, brands worried about disappearing from AI responses. The market frames this as GEO, but it’s not a new concept—just an old search marketing anxiety repackaged for the AI era.

OpenAI’s Ads Manager hits this anxiety right, but also shifts its focus.

In a no-ads era, the core issue for GEO is “how to enter AI’s context.” Brands compete by providing product documentation, media coverage, third-party reviews, and community discussions to be referenced by the model, emphasizing information quality and data structuring.

After the ad platform launched, precise traffic can be directly purchased. Brands no longer rely solely on organic mentions. But the focus of competition has shifted from “buy more exposure” to “how does AI evaluate my product.”

The reason is simple: after seeing an ad, the most natural next step for users is to ask AI “Is this product good?” AI’s answer becomes the real conversion gate. Advertisers can buy exposure but not positive AI reviews. If AI gives negative feedback based on public data, every dollar spent accelerates user loss rather than conversion.

This means brands need to build positive reputation within AI’s evaluation system. Signals like product quality, review density, and third-party assessments—readable by AI—will matter more for conversions than ad spend itself.

GEO is shifting from “entering the context” to “winning evaluations,” and this is a key trend after OpenAI’s new ad platform launch.

Not doing ads will be the most expensive advertising in 2026

Talking about OpenAI, we must mention its rival Anthropic, which is taking a completely different “ad model” approach.

On February 4, 2026, two days before the Super Bowl, Anthropic published a blog stating that Claude will never run ads. No sponsorships, no third-party integrations.

This statement itself is a costly ad.

Super Bowl ads are expensive. Anthropic spent heavily to tell users it doesn’t sell ads, essentially buying brand recognition through the absence of ads.

Going ad-free is not just a moral stance; it’s a business positioning. It signals to enterprise clients, professional users, and high-sensitivity scenarios that Claude’s answers won’t be influenced by advertisers, and its product direction isn’t optimized for ad inventory. Claude’s revenue comes from what you pay.

The effect is immediate. Claude’s ranking on the US App Store rose from 42nd early in the year to the top. On February 28, after OpenAI signed a Pentagon contract sparking the QuitGPT movement, Claude hit number one in the US App Store’s free apps—surpassing ChatGPT for the first time ever. Free active users grew 60%, daily sign-ups quadrupled, and paid users doubled within a week.

Anthropic’s revenue structure is completely different from OpenAI’s: over 80% comes from enterprise clients, with annual recurring revenue soaring from about $9 billion to $19 billion. Tools like Claude Code and Cowork have contributed at least $1 billion. Anthropic doesn’t need free-user ad value; it relies on enterprise trust that data won’t be used for ads, creating a premium for privacy.

Choosing not to advertise is a precise business decision—by sacrificing ad revenue, it strengthens trust with enterprise clients, supporting higher subscription prices.

But “not advertising” isn’t an eternal virtue.

Stanford’s AI Index shows that the cost to reach GPT-3.5 performance levels has dropped 280 times in two years—from $20 per million tokens in November 2022 to $0.07 in October 2024. As model capabilities converge and API price wars ignite, the enterprise subscription premium Anthropic enjoys today may erode. When model costs fall so all competitors can offer similar performance, why would enterprise clients keep paying more for Claude?

No conclusion yet, but time will tell what this choice means.

There’s no free lunch

OpenAI chooses ads; Anthropic turns “no ads” into a premium. They seem opposite but are actually answering the same question: when AI product inference costs can’t be covered long-term by free models, who pays?

OpenAI’s Ads Manager isn’t just an ad product; it’s a signal that the AI industry is shifting from free expansion to cost recovery.

But OpenAI’s way of stopping the bleeding exposes the most fragile part of this business. It relies on a user base with the least commercial intent—three times more expensive than Meta—to sustain a higher ad price.

This isn’t a problem that can be solved by user scale alone. 900 million weekly active users is a nice number, but if they come to ChatGPT to write emails rather than buy things, advertisers will eventually vote with their feet.

Ads can be a revenue source for AI products, but shouldn’t be the only answer. Because if a product’s business model depends on users staying as long as possible and exposing as many intents as possible, it’s no longer a user assistant—it’s an advertiser’s assistant.

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