Few people pay for AI, but those who do spend big

Andreessen Horowitz tracks actual US consumer spending for the first time in its latest Top 100 AI list. AI is widely used, but only a small group pays for it, and that group pays a lot.

Venture capital firm Andreessen Horowitz has published the seventh edition of its ranking of the most-used consumer AI products. After three years, the top of the list looks increasingly locked in, with only eleven products making it on for the first time, the fewest newcomers ever.

Beyond web traffic and mobile user counts, a16z now also tracks observed spending on US consumer cards using data from YipitData. The figures come from panels and don't represent total revenue, but they offer a new view of how people actually pay for AI.

Wide adoption, shallow monetization

Consumer AI gets broad use but little depth. Nearly half of US consumers now use AI, according to a16z, but only a quarter do so daily. Just 4.5 percent had an active paid personal subscription to ChatGPT, Gemini, or Claude in August, up from roughly half that a year earlier.

Within that narrow base, revenue is extremely concentrated. The top one percent of spenders accounts for nearly a fifth of all observed AI spending, more than the entire bottom half combined. That top one percent averages about $900 per month and keeps climbing, while the typical paying user spends about $25 and has held steady at that level for a while.

Their product choices reveal who they are. They favor building and automation tools like n8n, Manus, or fal at much higher rates, along with creative tools like Higgsfield, Figma, and HeyGen. In practice, they're prosumers buying software to build, design, and work, with professional use clearly driving the spending. Consumer AI has found its first real paying market in this group, according to a16z. Only seven companies rank in the top tier across all three rankings, including ChatGPT, Claude, Perplexity, and Canva.

The gap between many users and few payers also reflects how deeply people engage with AI. Paid accounts offer far more features but are more complex and demand a steeper learning curve, so free users typically scratch the surface of what AI can do. That creates a growing skills gap between people who use AI at a high level and those who barely know how or don't use it at all, which could deepen existing social inequality. Or AI simply keeps getting easier and cheaper until it doesn't matter. OpenAI CEO Sam Altman talks about "unlimited brilliance" for everyone in this context, though with a fairly naive outlook.

Three language models, three strategies

At the top, nothing has changed. ChatGPT leads the web with roughly double Gemini's traffic and six times Claude's, and on mobile the gap is even wider. The biggest shift is Claude's rise to a clear number three, a model that didn't even appear on the first web list in 2023 but has since passed Deepseek and Perplexity in traffic and pulled even with Gemini among US subscribers.

Anthropic monetizes better than its rivals, with a much larger share of Claude users on the priciest tier starting at $100 per month compared to similar plans from OpenAI and Google.

By midsummer, the momentum shifted. Daily Claude sessions fell in July and August, while ChatGPT picked up speed again with new models and ChatGPT Work. The question, according to a16z, is less about who wins and more about how well each company capitalizes on its window.

The race for the personal assistant

Six months ago, an agent like OpenClaw wasn't usable for most consumers, according to a16z. Now startup agents like Instinct and Tomo report hundreds of thousands of users, and the big players are countering with Meta's Muse, OpenAI's Dots, and xAI's Grok Bot.

Agents become an economic force once they start triggering real purchases. Instinct founder Noah Shinn says 40 percent of users link a credit card within three weeks and then spend four-figure amounts per month through the service, much of it on travel.

As revenue grows, platforms are picking sides. Amazon blocked Meta's Muse within two weeks, while Shopify, Instacart, OpenTable, and others signed official integrations. Muse hit a quarter million daily users in its first week and topped five million downloads in under a month, though compared to Meta's Threads, which pulled in more than 15 million downloads in three weeks at launch, that's still modest.

The business model is the real problem

Established players are the ones most likely to make money from AI. Canva and Notion rank in the web top ten, and Google alone holds five web spots. Startups carve out space mainly through a differentiated model, a multi-model experience, a specific audience, or by bypassing entrenched interfaces, according to a16z.

How money gets made at all, though, is the harder question. The vast majority of top AI-native products rely on subscriptions or usage fees, with only a small fraction using ads or transaction fees.

According to a16z, this inverts the pre-AI internet, where users themselves were the product and advertising drove the bulk of revenue for Meta and Alphabet. High model costs prevent AI companies from forgoing early revenue to build a large user base first.

Alternative approaches are starting to take shape. OpenAI reported an annualized revenue run rate of $1 billion from ChatGPT advertising in August, and personal agents could open a new path through affiliate fees or transaction cuts.

Six months ago, the sixth edition of the same ranking already showed a market in flux. That report focused more on geographic splits, such as the rise of Yandex Browser with its AI assistant Alice in Russia and Deepseek's role as a bridge between Western and Chinese user bases. Even then, a16z warned that web traffic and app downloads say less and less about which AI products people actually use as AI shifts from a standalone product to an embedded feature. The new spending data is a direct attempt to close that gap.