a16z’s Olivia Moore on the state of consumer AI

Olivia Moore, a partner at Andreessen Horowitz who covers consumer AI, published a report on Monday cataloguing the top 100 consumer AI apps. In an interview published by TechCrunch, she discussed what the list reveals about where the category stands and where it might go next.

ChatGPT remains the largest player by a wide margin, but Moore's report highlights smaller apps such as Suno and ElevenLabs as showing real staying power. The more striking finding, according to the report, is the absence of AI entrants in roughly half a dozen consumer categories.

The timing of the report is notable: OpenAI has moved back toward enterprise customers this year, a shift that has fueled pessimism about the consumer AI revenue picture. Moore characterizes that move less as a pivot than as an expansion, noting OpenAI continues to launch consumer products. She points out that nearly all AI revenue so far comes from subscriptions and token usage, which skews toward enterprise and prosumer buyers.

Moore is less interested in raising the share of households paying for AI than in changing how consumers are monetized. She cited the State of Markets finding that just 2.2% of U.S. households pay for AI. Rather than pushing that number up, she said she wants a return to a model where consumers are monetized without spending their own subscription dollars, suggesting most people would prefer free access with ads, with the option to pay to remove them.

Cost is the other structural problem. The marginal cost of running AI services remains much higher than for classic internet products like Facebook or Google Search. Moore sees improvement on that front, pointing to ChatGPT's $8-per-month Go plan, which she assumes runs on cheaper models. Her argument is that frontier-level intelligence is not needed for every task, opening the door to cheaper models in consumer use cases and to more consumer companies building on open-source models — something she says a16z founders have been discussing more frequently.

The catch, as she describes it, is that today's revenue-driving users are doing coding and other technical automation, work that often does require frontier intelligence. She expects lower-cost models to spread as more builders target consumers and the model stops being the product itself.

Moore also argues the consumer and enterprise lines are blurring. In a previous article she called this "The Great Expansion," contrasting pre-AI companies like Canva — which took six or seven years to add teams or enterprise plans — with newer companies like Gamma, ElevenLabs and Cursor that start consumer and become majority-enterprise businesses within roughly 18 months. Much of what gets labeled consumer AI, she says, is really prosumer AI. The revenue list bears this out: spending clusters around product-building apps such as Lovable, Replit and Fal; product marketing tools such as Higgsfield and HeyGen; and general work management tools such as Manus, Fireflies AI and Granola. These may be paid for by individuals, but she argues they are not consumer in the pre-AI sense.

The genuine whitespace she identifies includes social apps, dating apps, marketplaces, retail, travel, finance and health. No entrants in those categories appear in the top 100, a gap she calls surprising and expects to see filled over the next six months. Asked whether true consumer AI has yet arrived, she said it is definitely very early.

Why it matters: For founders and product teams, Moore's framing suggests the consumer AI opportunity may lie less in out-competing ChatGPT on subscriptions and more in categories that remain unoccupied, particularly social, dating, marketplaces, retail, travel, finance and health. If cheaper and open-source models continue to improve, consumer apps may be able to reach users without requiring frontier-model economics — though the revenue-generating workloads today still demand them. Treat the whitespace list less as a prediction than as a map of where investor attention is likely to turn next.