Article · 2026-07-31 · 6 moments

When Artificial Intelligence Is Too Valuable To Sell

Just because the AI labs have sold models on a meter until now doesn't mean they'll always do so. ✦ AI generated

Mechanism

A crowded AI frontier won't make AI a pure commodity, but it will drive down the value of the best models sold on a meter, so AI profits will accrue mostly to those who build the best products on top of the models and those who own the compute.

The author explains why crowding erodes the value of metered model sales without fully commoditizing the technology, shifting profits to product-builders and compute owners.

transcript

Alex Kantrowitz: A crowded AI frontier won't make the technology a pure commodity, because specialization and compute resources will always give certain AI labs edges in certain areas, but it will drive down the value of the best AI models (at least if your plan is to sell them on a meter). The profits in AI will thus accrue mostly to those who build the best products on top of the models, and those who own the compute that enables them to serve these products.

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Prediction◆

A frontier lab's strategy should follow from the competitive landscape: with one or two dominant players, sell models at a high markup; with several tied labs, sell products; and with a narrow lead like OpenAI's and Anthropic's today, pull up the ladder and build products competitors cannot match with older tech.

The author lays out the strategic calculus for frontier labs, arguing that the almost-tied position of OpenAI and Anthropic makes the 'pull up the ladder' product play the likely best move.

transcript

Alex Kantrowitz: How you play this as a frontier AI lab is almost a simple calculation: If there are one or two players with the best models and a long lead over the competition, the best approach is to sell those AI models at a high markup and bank the margins. If there are several labs essentially tied, the strategy is to sell the best AI products built on top of the models. If you have a relatively narrow lead over the competition, as is the case with OpenAI and Anthropic today, then things get interesting. The best move may be to pull up the ladder and use your very best models to build products that your competitors cannot with previous-generation tech, especially if you're inevitably headed to a product battle anyway.

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Claim◆

It is time to delete the assumption that frontier AI labs will always license their best models; increasingly it may be in their interest to hoard the intelligence and sell the products built with those models, not the models themselves.

The author opens by arguing the core assumption of the AI business — that the frontier labs will always sell their top models by the token — should be dropped, since it may become more profitable to keep the intelligence and sell products built on top of it.

transcript

Alex Kantrowitz: It's time to delete the assumption that the frontier AI labs will always license their best models and not hoard the intelligence for themselves. Just because the labs have, until now, sold their top-line models to all takers via an API, metered by token usage, doesn't mean they will inevitably sell it that way going forward. Instead, it may be in their best interest to sell the products they've built with these models, and not the models themselves.

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Claim

Keeping the latest models off limits to the public would be the AI labs' most controversial move and would likely demolish their API revenue ahead of IPOs — Sam Altman disavows the idea — yet nothing in the short history of generative AI has been too crazy to be taken off the table.

The author weighs the cost of hoarding — controversy and gutted API revenue before IPOs, disavowed by OpenAI's CEO — but concludes that as financial pressures escalate, the previously unthinkable might become reality.

transcript

Alex Kantrowitz: Deciding to keep the latest models off limits to the public would be the AI labs' most controversial move in a long history of them. It would also likely demolish their API revenue, a real concern as they head to IPO. And OpenAI CEO Sam Altman disavowed it in an interview this week. 'I want to put that in everyone's hands,' he said. 'Concentration of power with AI is a terrifying thing.' But however unlikely this scenario may seem, the one constant in the short history of generative AI is that nothing is too crazy to be taken off the table. And as financial pressures escalate, the previously unthinkable might turn into reality.

Context

The AI race is no longer a one- or two-lab competition: open-weights competition from China and profit-insensitive initiatives from Google, Meta, and SpaceX mean there may now be five, six, or seven labs at the top.

The author describes how the frontier has become crowded, with Chinese open-weights competition and profit-insensitive efforts from big players collapsing the notion that OpenAI or Anthropic would get there alone or even together.

transcript

Alex Kantrowitz: The AI race is no longer a competition where one or two AI labs develop superhuman-level artificial intelligence and sell it at a vast markup. The notion that OpenAI or Anthropic would get there alone, or even both together, has fallen apart in recent months. Open weights competition from China, and profit-insensitive initiatives from Google, Meta, and SpaceX, have shown that rather than one or two labs at the top, there may be five, six, or seven.

Example

The business realities are already pushing AI labs upmarket into competing with their own clients — as seen in Anthropic's Claude Code and Claude Design and OpenAI's ChatGPT superapp with Codex — and if the labs hoard their best models, they will have a strong chance to build the best AI-native products and outcompete struggling legacy-software incumbents.

The author cites early evidence of the product pivot — Anthropic's Claude Code and Claude Design, OpenAI's ChatGPT 'superapp' with Codex — and argues that hoarding the best AI lets the labs exploit incumbents' 'capability overhang' across the software landscape.

transcript

Alex Kantrowitz: AI labs moving 'upmarket' and competing with their clients has always been the threat to software (the Saaspocolypse should never have been about vibe coding your own Salesforce). And now, the business realities may force the labs to do it. We've already seen interest in moving beyond the API business from Anthropic, which has released products like Claude Code and Claude Design. And OpenAI, for its part, is pushing hard in products with its new ChatGPT 'superapp' that includes coding capabilities with Codex built-in. The leading AI labs will see opportunities to build AI-native products across the software landscape given that today's incumbents are struggling with legacy products, stubborn organizational structure, and 'capability overhang.' If the labs' best artificial intelligence is broadly available, then everyone can compete. If they hoard it, they'll have a strong chance to build the best AI-native products on the market and make their investors happy.

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Highlight slides

Delete the Assumption✦ from: It is time to delete the assumption that frontier AI labs will always license their best models; increasingly it may be in their interest to hoard the intelligence and sell the products built with those models, not the models themselves.How frontier labs should play the competitive landscape✦ from: A frontier lab's strategy should follow from the competitive landscape: with one or two dominant players, sell models at a high markup; with several tied labs, sell products; and with a narrow lead like OpenAI's and Anthropic's today, pull up the ladder and build products competitors cannot match with older tech.Sell Products, Not the Models✦ from: It is time to delete the assumption that frontier AI labs will always license their best models; increasingly it may be in their interest to hoard the intelligence and sell the products built with those models, not the models themselves.API Metering Isn't Inevitable✦ from: It is time to delete the assumption that frontier AI labs will always license their best models; increasingly it may be in their interest to hoard the intelligence and sell the products built with those models, not the models themselves.

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