Of course they’re putting ads in AI | Andreessen Horowitz
Of course they’re putting ads in AI
The internet is a miracle of universal access to opportunity, inquiry and connection. And ads pay for that miracle. As Marc has long argued, “if you take a principle stand against ads, you’re also taking a stand against broad access.” Ads are why we have nice things.
So, the announcement last month that OpenAI plans to launch ads for free users is probably the biggest piece of news-that-isn’t-actually-news of 2026 (so far). Because of course, if you’ve been paying attention, the signs that this would happen have been everywhere. Fidji Simo joined OpenAI in 2025 as CEO of Applications, which many people interpreted to mean “implement ads, just like she did at Facebook and Instacart.” Sam Altman had been teasing the rollout of ads on business podcasts. And tech analysts like Ben Thompson have been predicting ads pretty much since ChatGPT launched.
But the main reason that ads aren’t a surprise is because they’re the best way to bring a service on the internet to the largest possible number of consumers.
The long tail of LLM users
“Luxury beliefs”, a term that came into vogue a few years ago, are stances taken not really for principled reasons, but for optical reasons. Tech has plenty of these, especially when it comes to advertising. For all the moralistic hand-wringing over “Selling data!” or “Tracking!” or “Attention harvesting” and other bingo words, the internet has always run on ads and most people like it that way. Internet advertising has created one of the greatest “public goods” in history, for the negligible price of occasionally having to look at ads for cat snuggies or hydroponic living room gardens. People who pretend this is a bad thing usually are trying to prove something to you.
Any internet history buff knows that ads are a core part of how platforms eventually monetize: Google, Facebook, Instagram, and TikTok all started free, and then figured out monetization with targeted ads. Ads can also be a way to supplement the ARPU of a lower-value subscriber, as in the case of Netflix’s newer $8/month option, which introduced ads to the platform. Ads have done a very good job of training people to expect most things on the internet to be free or extremely low-cost.
This pattern can now be seen across frontier labs, as well as specialized model companies, and smaller consumer AI companies. From our survey of consumer AI subscription companies, we can see that converting subscription users can be a real challenge for all of them:
So what’s the solution? As we all know from past consumer success stories, ads are often the best way to scale your service to billions of users.
To understand why most people don’t pay for AI subscriptions, it helps to understand what people use AI for. Last year, OpenAI published data on exactly this.
In short, most people use AI for personal productivity: things like writing emails, searching for information, and tutoring or advice. Meanwhile, higher value pursuits, like programming, make up a very small percentage of overall queries. Anecdotally, we know that programmers are some of the most committed users of LLMs, with some even calibrating their sleep schedules to optimize for daily usage limits. For these users, a $20 or $200/month subscription doesn’t feel exorbitant, because the value that they’re getting (the equivalent of a swarm of highly productive SWE interns) is likely orders of magnitudes greater.
But for the users who are using LLMs for general queries, advice, or even writing help, the onus of actually paying is too great. Why would they pay for an answer to questions like “why is the sky blue” or “What are the causes for the Peloponnesian War” when previously a Google search would direct you to a good-enough answer for free. Even in the case of writing help (which some people are using for email jobs and rote work), it often doesn’t do enough of a person’s job to justify an individual paying for a subscription. Additionally, advanced models and features often aren’t needed by the majority of people: you don’t need the best reasoning model to write emails or suggest recipes.
Let’s take a step back and acknowledge something for a moment. The absolute number of people paying for a product like ChatGPT is still enormous: 5-10% of 800M WAUs. 5-10% of 800M is 40-80M people! On top of that, the price point for Pro at $200 is ten times what we thought the ceiling was for consumer software subscriptions. But, if you want to get ChatGPT to a billion people (and beyond) for free you need to introduce a product other than subscriptions.
The good news is that people actually do like ads! Ask the average Instagram user, and they’ll probably tell you that the ads they get are ridiculously useful: they get served products they actually want and need, and make purchases that actually make their lives better. Framing ads as exploitative or intrusive is regressive: maybe we feel that way about TV ads, but targeted ads are actually pretty great content most of the time.
I’m using OpenAI as an example here (since they have been one of the most forthcoming labs when it comes to comprehensive disclosures around usage trends). But this logic applies to all frontier labs: they will all need to introduce some form of advertising eventually if they want to scale to billions of users. The consumer monetization model is still unsolved in AI. In the next section, I’ll walk through some approaches.
Possible AI Monetization Models
My general rule of thumb in consumer app development is that you need a minimum of 10M WAUs before introducing ads. Many AI labs are already at this threshold.
We already know ad units are coming to ChatGPT. What might they look like, and what other ad and monetization models are viable for LLMs?
Monetization is still an unsolved problem in AI, with the majority of users still enjoying the free tier of their preferred LLM. But this will only be temporary: the history of the internet has taught us that ads find a way.
If you’re working on building the next generative AI-native ad stack, or if you’re scaling your way to tens of millions DAUs, reach out at bryan@a16z.com or @kirbyman01 on X.
Bryan Kim
is a partner at Andreessen Horowitz, where he invests primarily in consumer AI applications.
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