ChatGPT sells ads now: so how does AI actually make money?

A few days ago I got an email from OpenAI about ChatGPT Ads.

Seeing “Ads,” I finally properly thought about a question I’d never really chased down before:

we’re already very familiar with the ways internet products make money. Google, Instagram and TikTok have very significant ad revenue, Netflix makes you think more of subscriptions, and many SaaS products are paid for by individuals or companies.

But what about general-purpose AI like ChatGPT and Claude?

Model development takes huge investment, and after launch, every use still incurs compute costs. At the same time, they have free users, personal subscriptions, APIs and enterprise versions all at once — and now ads are starting to appear.

So I went and looked up how OpenAI, Anthropic and a few other companies charge, their product policies, and some research on AI costs, advertising and trust in recommendations.

In the end I found that the question “does AI make money from subscriptions or ads” is itself framed a bit too narrowly.

01 | General-purpose AI is running several businesses at once

OpenAI and Anthropic both face several completely different kinds of customers.

• Ordinary users pay a monthly subscription, buying stronger models, higher usage limits, more tools and a more complete product experience.
• Developers call the API based on actual usage, buying model capability they can plug into their own products.
• Companies aren’t buying just “ChatGPT with more quota.” They also pay for employee accounts, permission management, security, data controls, system integration and support.
• OpenAI now has one more kind of customer: advertisers. What advertisers buy is the chance to reach potential consumers in the right context.

So behind the same general-purpose AI, several businesses actually exist at once:

selling usage to individuals, selling model calls to developers, selling a work platform and management capabilities to companies, and also selling commercial reach to advertisers.

Anthropic has explicitly chosen to keep Claude ad-free for now, but it likewise has personal subscriptions, APIs and enterprise business.

So the two companies aren’t:

OpenAI relying on ads, Claude relying on subscriptions.

Most of their revenue models are actually very similar; ads are just one clear fork for now.

02 | Different people pay, and they aren’t buying the same thing

Once “who pays” is sorted out, the next layer is actually more interesting.

We usually say loosely:

AI companies sell AI.

But “AI” is too abstract.

• What ordinary users really buy is capability and convenience.
• Developers buy model capability they can call directly.
• Companies, besides capability, also buy security, management, integration and control.
• Advertisers buy the chance to reach potential customers.

Companies like Google and Microsoft have another path: AI doesn’t necessarily need to become a separate business; it can become part of their existing software and service bundles, making the original products more worth buying or upgrading.

So to understand an AI product’s business model, you can’t only look at:

“how much is this app a month?”

You also have to look at which customers it serves, and why each of those customers is willing to pay.

03 | So as users, what do we actually pay?

I think this question is more worth ordinary users’ attention than “how much money do AI companies actually make.”

The most direct is of course money.

If I subscribe to ChatGPT or Claude each month, that part is clear.

But using a product for free or cheaply doesn’t mean using it costs nothing at all.

We may also pay:

• the attention it takes to see ads;
• the information and context needed to complete the task;
• depending on the specific terms, permission for some content to be used for model improvement or personalization;
• our own time spent prompting, checking and revising;
• and, as use gets deeper and deeper, the cost of switching to other products.

Still, these can’t all be reduced to a very common line:

“if the product is free, you are the product.”

Applied to today, that line is actually too crude.

For example, if I tell AI:

“My budget is 5,000 yuan, mainly for editing video — which computer should I buy?”

that information is first of all for AI to complete my task.

Whether it’s later used for model training, personalization, ad matching, or provided to other companies are several completely different questions, depending on the specific product and specific terms.

Processing data isn’t the same as training models on it; using it for personalization isn’t the same as selling chat content to advertisers.

These are best looked at separately.

04 | Paying, being ad-free, and how data is used are actually three different things

After going through the material, this is the place I found especially easy to confuse.

We easily assume by default:

I’ve already paid, so there should be no ads; since I’ve paid, my data shouldn’t be used for anything else either.

But reality isn’t like that.

• A product can charge money while some plans still include ads.
• A product can be completely ad-free yet allow some consumer data to be used for model improvement.
• Personal paid plans and enterprise plans may also have completely different data rules.

So:

• paying is a business model question.
• whether there are ads is a product experience question.
• how data is used is a data policy question.

The three are related, but none automatically implies the other two.

In the future, judging an AI product still means looking separately at:

• which plan am I buying?
• does it include ads?
• how exactly will my data be used?

05 | Will ChatGPT selling ads affect our trust in it?

This was the other question the email first made me curious about.

Having looked into it, I think the answer isn’t that simple.

“Ads appearing in AI” and “commercial interests shaping AI’s answers” aren’t the same thing.

For example, I ask:

“How should I choose a pair of running shoes?”

AI answers the question normally, and then, separately below, an ad clearly marked Sponsored appears.

That’s one scenario.

But if AI tells me:

“Brand A is my top recommendation.”

and the reason it recommends A is that A paid the platform.

That’s a different problem.

What the latter really touches is:

can I still understand this recommendation as independent advice?

On this, OpenAI and Anthropic have currently made different choices.

• OpenAI’s approach is to separate ads from normal answers, and it publicly stresses that ads won’t determine ChatGPT’s answers.
• Anthropic has chosen to keep Claude ad-free.

The reason it gives isn’t only “ads are annoying.”

Anthropic believes AI assistants are somewhat different from ordinary content platforms. People hand them work, ideas, and even some private and complicated problems. If ads became a source of revenue, even without entering answers directly, they might add another commercial goal to the product, such as getting people to stay longer and engage more.

This can’t prove Anthropic’s judgment is necessarily right, nor that OpenAI’s model will necessarily damage trust.

They’re more like answering the same question:

for a product taking an ever deeper part in our work, thinking and choices, where should commercial interests stop?

Existing research on ad disclosure and generative recommendations doesn’t give a very simple answer either.

Whether people know they’re seeing commercial content, whether ads are clearly labeled, and whether the content is relevant all affect people’s judgments.

But so far there isn’t enough evidence to support a very absolute conclusion:

as soon as ads appear in AI, people will definitely lose trust in it.

What’s really worth continuing to watch may actually be the next step.

If in the future AI doesn’t only answer questions, but can also, for us:

find products, choose hotels, book services, place orders, even complete transactions directly,

and the platform can earn revenue from those transactions, then the question becomes:

have its commercial interests entered the recommendation itself?

If AI recommends a hotel, and the platform can take a cut of the booking, I’d want to know:

does it recommend this hotel because it suits me best, or because this transaction is also valuable to the platform?

Compared with “is there an ad on the page,” this may be closer to the trust problem in AI products.

06 | Understanding AI also means understanding the business behind it

After this round of research, I think from now on I’ll look at four more things when I look at an AI product:

• who is paying for this product?
• what exactly do the payers get?
• as a user, what am I paying myself?
• will commercial relationships enter the answers and recommendations it gives me?

We’re very used to comparing model capabilities now:

who’s smarter, who scores higher on benchmarks, who’s shipped another new feature.

These of course matter.

But as AI enters more and more work, consumption and everyday life, understanding an AI product may also need one more layer:

what kind of business is really behind it.

About the sources

This post is based on public material as of September 2026, mainly drawing on the official pricing, advertising and data policies of OpenAI, Anthropic and other companies, as well as the Stanford AI Index and related research on native advertising, ad disclosure and generative recommendations.

AI products and policies change fast; for specific rules, each product’s latest official documentation takes precedence.