Who pays for AI?

{"text":[[{"start":4.55,"text":"This article is an on-site version of our Unhedged newsletter. Premium subscribers can sign up here to get the newsletter delivered every weekday. Standard subscribers can upgrade to Premium here, or explore all FT newsletters"}],[{"start":18.75,"text":"Good morning. A 77 per cent increase in second-quarter earnings from Taiwan Semiconductor Manufacturing Co was not enough to boost its shares, those of the chip industry generally or indeed the Nasdaq 100. All of those fell yesterday. TSMC is the world’s most irreplaceable company and it is firing on all cylinders. However high its flying, though, expectations are flying higher. More ruminations on this theme below. Email us: unhedged@ft.com."}],[{"start":49.4,"text":"AI: monetisation or bust"}],[{"start":52.35,"text":"The era of asking cutting-edge AI models for chicken soup recipes is coming to an end. That should worry everyone on the long side of the AI trade — which, in 2026, means just about everyone, directly or indirectly. "}],[{"start":65.95,"text":"For three years, the AI investment story has gone something like this. Frontier AI model-makers such as Anthropic and OpenAI provided their products at well below cost, in the form of consumer-facing chatbots, allowing users to burn through the most precious commodity in the AI supply chain: compute capacity. AI users lived a subsidised existence while investors happily picked up the bill, as each successive fundraising round increased their paper gains (old heads will hear the echo of the eyeball- and click-based valuations at the turn of the millennium)."}],[{"start":99.25,"text":"Most of the value went straight to the chip industry — the only companies positioned to reap an immediate return from a technology that consumes more capital than it generates and may do so for years to come. Again, investors didn’t mind. They believed that once the technology achieved mass adoption, the model makers and data centre builders would capture epic profits and live happily ever after."}],[{"start":123.55,"text":"That story may be running out of road, as the model makers come under pressure to capture some of the value from their applications. In the past few months, a growing number of AI-related services have switched from flat fees to usage-based pricing, starting with Microsoft-owned coding platform GitHub, in April. This “seismic shift” marks the “end of the token subsidy” that has underwritten AI’s rapid adoption to date, argues Juan Correa at BCA Research. Companies faced with ballooning AI bills are moving from “tokenmaxxing” to token rationing, says Bank of America. "}],[{"start":160.4,"text":"Switching to consumption-based pricing has had two unintended effects. The most notable is the rapid increase in usage of Chinese AI models, which tend to be open source and lower cost:"}],[{"start":null,"text":"

"}],[{"start":171.55,"text":"The second effect of this switch is that it appears to be pulling down spending per token, as lower-cost models account for a higher proportion of token usage:"}],[{"start":null,"text":""}],[{"start":180.55,"text":"On the face of it, this raises serious questions about how the hundreds of billions in investment is expected to turn into profits, let alone revenue. But some, such as Torsten Sløk at Apollo, see this as early evidence of Jevons paradox applying to AI, the idea that an increase in efficiency leads to an increase in usage. On that view, falling unit costs will lead companies to increase their total spending on AI as they apply AI to more and more of their business. This might well be true, and the profitability of the AI companies depends on it."}],[{"start":217.20000000000002,"text":"An even more alarming notion is that AI will become commoditised. This is the idea that an abundance of AI supply and broadly interchangeable models will make the technology more like electricity than software, writes Tyler Frawley at RBC Wealth Management. In that scenario, the real economic value accrues not to the producer but to the companies that build the most effective systems on top of it. If that’s right, the bulk of the investment in the model makers has been misallocated and the returns will be terrible. "}],[{"start":251.05,"text":"If the model layer is being commoditised, the infrastructure layer isn’t obviously safer. Investors in hyperscalers are increasingly questioning how the massive capital spending needed for AI infrastructure — estimated by Morgan Stanley to rise to $1.2tn next year, at just five companies — will be financed. Many have pointed to the collapse in free cash flows and the tsunami of hyperscaler bond issuance. The ratio of capex to revenue is also mounting:"}],[{"start":null,"text":""}],[{"start":280.7,"text":"Summing up, the AI trade rests on two big assumptions. The first is that AI will be profitable. But as noted above, just because a technology leads to a huge increase in productivity doesn’t mean it will generate strong returns. The second is that there will be widespread demand for AI, and soon. AI adoption has been fast, to be sure. But we’re still a long way from peak adoption. Goldman Sachs estimates that it could take as long as 15 years, which would still be faster than the median adoption rate of 29 years for previous general-purpose technologies. Bloomberg reported earlier this month that Meta is looking to sell its excess compute capacity. It probably won’t be the last, and it smells of malinvestment. "}],[{"start":327,"text":"But perhaps the clearest evidence that all is not well in the AI trade is hyperscaler stock price performance over the past three months, which has gone nowhere even as capex guidance keeps rising:"}],[{"start":null,"text":""}],[{"start":338.6,"text":"Excitement about AI as a technology is different from exuberance about AI as a trade. Unhedged has lots of the former but, at the present juncture, not much of the latter. Feel differently? Email us. "}],[{"start":351.75,"text":"One good read"}],[{"start":353.7,"text":"Yellow journalism."}],[{"start":null,"text":""}],[{"start":null,"text":""}],[{"start":355.65,"text":"Can’t get enough of Unhedged? Listen to our new podcast, for a 15-minute dive into the latest markets news and financial headlines, twice a week. Catch up on past editions of the newsletter here."}],[{"start":null,"text":""}],[{"start":368.79999999999995,"text":"Due Diligence — Top stories from the world of corporate finance. Sign up here"}],[{"start":374.65,"text":"The AI Shift — John Burn-Murdoch and Sarah O’Connor dive into how AI is transforming the world of work. Sign up here"}],[{"start":388.2,"text":""}]],"url":"https://audio.ftcn.net.cn/album/a_1784294181_1615.mp3"}