a16z:几乎所有我们称作消费 AI 的东西其实是 prosumer AI,只有三类专业用户在付费;社交、约会、电商、旅行、金融、健康六个品类至今没有 AI 入局
a16z’s Olivia Moore on the state of consumer AI
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导读
作者本周刚写过消费 AI 的惨淡经济性,而 a16z 负责消费 AI 的合伙人 Olivia Moore 在周一发布了消费 AI 应用 Top 100 报告,看到的是机会。ChatGPT 仍是遥遥领先的最大玩家,但 Suno 与 ElevenLabs 这类较小玩家显示出真实的续航力;更有意思的是看不到的部分——报告点出至少六个看似完全没被 AI 触碰的消费品类。Moore 的核心判断有两个。其一是变现路径不该只靠订阅与 API:她其实不希望付费用户数继续往上(《State of Markets》报告提醒只有 2.2% 的美国家庭在为 AI 付钱),更想回到一种消费者不以自掏腰包的订阅金被变现的世界——硅谷高收入、有公司信用卡的人当然愿意为产品付钱,但大多数人其实宁愿免费用、看一些广告,再自己决定是否订阅去去掉广告。其二是「几乎所有我们称作消费 AI 的东西,我认为其实是 prosumer AI」:营收榜上基本只有三类专业用户在付费——做产品的应用(Lovable、Replit、Fal)、产品营销(Higgsfield、HeyGen 这类 AI 广告生成器)与通用工作管理(Manus、Fireflies AI、Granola)。关于成本,她注意到 ChatGPT 已有每月 8 美元的 Go 档,推测跑的是更便宜的模型,因为「并非每个任务都需要前沿智能」;她预计更多消费公司改用开源模型,「最近从创始人那里听到很多,感觉真的开始变了」。她还印证了消费与企业边界正在模糊:AI 之前像 Canva 这样以消费者为先的公司往往要六七年才加上团队或企业档,而现在 Gamma、ElevenLabs、Cursor 从消费起步、18 个月内 majority 变成企业业务。至于空白品类(社交、约会、市场、零售、旅行、金融、健康),Top 100 里没有任何入局者——她认为接下来六个月要看的就是这些。被问到「也许我们还没真正见过消费级 AI」,她答:「确实非常早。」
推荐理由
prosumer AI 这一概括加上六类空白品类与三类专业用户清单,是消费 AI 讨论里有辨识度的框架;但形态是访谈问答,多数判断未附原始数据支撑。
主体与标签
Andreessen Horowitz#观点/评论#行业动态
正文
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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