Ads, rate limits, feature restrictions, price hikes. The AI free ride is over.
Earlier this month, millions of OpenClaw users woke up to a sweeping mandate: The viral AI agent tool, which this year took the worldwide tech industry by storm, had been severely restricted by Anthropic.
Anthropic, like other leading AI labs, was under immense pressure to lessen the strain on its systems and start turning a profit. So if the users wanted its Claude AI to power their popular agents, they’d have to start paying handsomely for the privilege.
“Our subscriptions weren’t built for the usage patterns of these third-party tools,” wrote Boris Cherny, head of Claude Code, on X. “We want to be intentional in managing our growth to continue to serve our customers sustainably long-term. This change is a step toward that.”
The announcement was a sign of the times. Investors have poured hundreds of billions of dollars into companies like OpenAI and Anthropic to help them scale and build out their compute. Now, they’re expecting returns. After years of offering cheap or totally free access to advanced AI systems, the bill is starting to come due — and downstream, users are beginning to feel the pinch.
Over the past few years, most top AI labs have introduced new subscription tiers to court power users. OpenAI and Anthropic shifted their pricing plans for enterprise. OpenAI introduced in-platform advertisements. Anthropic, of course, restricted third-party tools.
In some ways, this is a tale as old as time, and particularly, a clear echo of the tech boom of the ’10s. Venture capitalists helped startups subsidize fast growth in all kinds of areas: ride-hailing apps, e-commerce, takeout and grocery delivery. Once companies cemented their power, they raised prices, added new revenue streams, and delivered a return to investors. Or they didn’t — and they crashed and burned.
But AI companies have gone through more investor money at a faster pace than any other sector in recent history. AI companies have broken ground on data centers around the world, dedicating billions of dollars with promises of better models, lower costs, and AI for everyone. Even stemming the flow of losses will be difficult — let alone making the kind of money investors are hoping for. “When you sink trillions of dollars into data centers, you’re going to expect a return,” said Will Sommer, a senior director analyst at Gartner, who specializes in economic forecasting and quantitative modeling.
“Is the era of basically free or close-to-free AI kind of coming to an end here?” said Mark Riedl, a professor in the Georgia Tech School of Interactive Computing. “It’s too soon to say for certain, but there are some signs.”
Gartner’s Sommer studies long-term economic market trends related to generative AI, including calculating just how much money is at stake. Between 2024 and 2029, he said, Gartner estimates that capital investment in AI data centers will reach about $6.3 trillion — a “massive amount of money.”
To avoid a write-down of these assets, major AI model providers would ideally generate a return on invested capital (ROIC) of about 25 percent, Sommer said. (That’s about what Amazon, Microsoft, and Google tend to earn on their overall capital investments.) On the other hand, if the returns fall below 12 percent, institutional capital loses interest — there’s better money elsewhere, Sommer said. Below 7 percent, you’re in write-down territory, which is “an unmitigated disaster for all of the investors in this technology,” Sommer said.
To reach that bare minimum of 7 percent, Gartner forecasts that large AI companies would need to earn cumulatively close to $7 trillion in AI-driven revenue through 2029, which is close to $2 trillion per year by the end of the period. In order to achieve “historic returns,” the providers would need to earn nearly $8.2 trillion in the same period.
OpenAI has already made $600 billion in spending commitments through 2030, the company said in February, which Sommer says is already a “massive step down” from the $1.4 trillion it had planned before. Based on OpenAI’s revenue forecasts and potential compound annual growth, Sommer said that even in the best-case scenario, he predicts that the lab would only hit a fraction of the overall spend required to hit that 7 percent ROIC.
How do model providers like OpenAI make this money? By selling access to what are known as tokens. A token is essentially a unit of data input that an AI model can understand and process — it could be text, images, audio, or something else. One token is generally worth about four characters in the English language — the word “bathroom,” for instance, would likely be processed as two tokens. One paragraph in English is generally about 100 tokens, and a 1,