I wrote this week about the bleak economics of consumer AI – but where some see a crisis, others see an opportunity.

Olivia Moore covers consumer AI as a partner at Andreessen Horowitz – and on Monday, she released a report on the top 100 consumer AI apps. ChatGPT is still the biggest player by a mile, but smaller players like Suno and ElevenLabs are showing real staying power. Even more interesting is what we don’t see, as Moore’s report details half a dozen consumer categories that seem to be completely untouched by AI.

Moore sees a huge opportunity in consumer AI, particularly if the industry can tap into revenue streams beyond just subscriptions and API charges. On a call this week, I talked with her about the unusual economics of consumer AI and why it’s still early days for the category.

This interview has been edited for length and clarity.

It’s an interesting moment for a report about consumer AI, since we’ve seen OpenAI pivot back to enterprise this year. It’s inspired a lot of pessimism about the overall revenue picture for consumer AI, including from me. But I take it you’re more optimistic?

I agree with you that OpenAI has moved back towards the enterprise. To me, it’s not necessarily a pivot because they’re still launching a lot in consumer. It’s more of an expansion. But I don’t blame them, as much as I love consumer, because almost all of the AI revenue thus far has come from subscriptions and then token usage. And that is much more concentrated on the enterprise and prosumer side. 

How can consumer AI products change that revenue problem? The State of Markets report reminded us that just 2.2% of U.S. households are paying for AI. Do we need that number to rise before the market becomes attractive?

I actually don’t know if I want to see that user number increase. I’m more interested in getting back to a world where the consumer is monetized in a way that isn’t subscription dollars out of their own pocket.

I think it’s very easy in Silicon Valley, with people who are high-income and have corporate cards to pay for those tools, to say, “oh well, I’d rather pay for the product.” But I think most people would actually rather have free access to something and see some ads, and then they can decide if they want to subscribe or not to make the ads go away. 

The other challenge is the marginal cost of AI services, which is still a lot higher than classic internet services like Facebook or Google Search. Do you see a lot of these services finding ways to keep those costs down, whether it’s open-source or other lightweight models?

Yeah, I think we’re seeing improvements there. Even ChatGPT now has a Go plan, which is just $8 a month, and I’m assuming it runs on cheaper models. We don’t necessarily need frontier intelligence for every task, and so that could mean cheaper models, especially for some consumer use cases. It could also mean more consumer companies building on top of open-source models. We’ve heard a lot of that from our founders lately, and it really feels like it’s starting to change.

The problem is that right now, the users driving the revenue are doing coding and other technical automation, where they probably do need frontier intelligence. I think as we get more people building for the consumer, where the model is not the product, we’ll start to see lower-cost models used more often.

It’s unusual to talk about technical automation in a consumer service, which feels like another unique feature of AI. Are we starting to blur the lines between consumer and enterprise?

I wrote an article about this maybe a year or so ago called The Great Expansion trying to get at this. Pre-AI, you would have companies like Canva that were consumer-first and often took six or seven years to even add teams or enterprise plans. Now we’re seeing companies like Gamma, ElevenLabs, and Cursor that start as consumer and within 18 months become majority-enterprise businesses.

Almost all of what we think of as consumer AI, I would argue, is prosumer AI. This really comes out on the revenue list, where there’s basically like three categories that power users are spending on. There’s product-building apps, so like Lovable, Replit, and Fal. There’s product marketing, which is AI ad generators like Higgsfield or HeyGen. Then there’s general work management, like Manus, Fireflies AI, and Granola. Those are like being paid for by consumers to start with, but I would argue that they’re not consumer in the way that we would think about pre-AI. 

There are also all these whitespace categories: social apps, dating apps, marketplaces, retail, travel, finance, health. There are no entrants in our top 100 list in those categories, which is pretty surprising. And that’s what I think we need to see over the next six months.

So maybe we haven’t really seen true consumer AI yet?

It’s definitely very early.

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Russell Brandom
Russell Brandom has been covering the tech industry since 2012, with a focus on platform policy and emerging technologies. He previously worked at The Verge and Rest of World, and has written for Wired, The Awl and MIT’s Technology Review. He can be reached at [email protected] or on Signal at 412-401-5489.
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