{"id":4021,"date":"2026-06-16T17:55:44","date_gmt":"2026-06-16T17:55:44","guid":{"rendered":"https:\/\/finzexpert.com\/blog\/the-new-oil-inside-the-effort-to-turn-ai-computing-power-into-a-tradeable-commodity\/"},"modified":"2026-06-16T17:55:44","modified_gmt":"2026-06-16T17:55:44","slug":"the-new-oil-inside-the-effort-to-turn-ai-computing-power-into-a-tradeable-commodity","status":"publish","type":"post","link":"https:\/\/finzexpert.com\/blog\/the-new-oil-inside-the-effort-to-turn-ai-computing-power-into-a-tradeable-commodity\/","title":{"rendered":"The new oil? Inside the effort to turn AI computing power into a tradeable commodity"},"content":{"rendered":"\n
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For decades, companies have turned to futures markets to manage uncertainty. Airlines hedge fuel costs. Farmers hedge crops. Manufacturers hedge metals.fcomm<\/p>\n

Now a startup wants to bring that same financial machinery to artificial intelligence.<\/p>\n

Silicon Data, a company that tracks pricing across cloud providers and GPU marketplaces, has partnered with CME Group to launch what could become the world’s first futures contracts tied to the computational power needed to run AI, allowing companies to hedge against fluctuations in the cost to train and run AI models. The contracts are still awaiting regulatory approval.<\/p>\n

Early signs suggest investor interest is quickly emerging. Within days of Silicon Data’s announcement with CME Group, asset managers including ProShares and Rex Shares filed proposals for exchange-traded funds tied to the proposed contracts, including leveraged and inverse products.<\/p>\n

Founder and CEO Carmen Li believes the market could eventually rival some of the world’s largest commodity markets.<\/p>\n

“I think it will be larger” than oil futures, Li said in an interview, adding that energy demand tied to running artificial intelligence will eventually surpass all other energy uses, combined.<\/p>\n

Like jet fuel<\/h3>\n

The idea stems from a simple observation: AI companies increasingly depend on compute in the same way airlines depend on jet fuel. <\/p>\n

Most companies don’t own the high-end graphics processing units, or GPUs, that power modern AI systems. Instead, they rent access through cloud providers and a growing ecosystem of so-called neoclouds. As demand for AI infrastructure surges, the cost of that compute can fluctuate, making it difficult for businesses to forecast expenses.<\/p>\n

“Right now we’re at a high point of uncertainty,” said Seoyoung Kim, a finance professor at Santa Clara University. “A lot of people don’t know how much computing power they’ll need in the next year, and a lot of suppliers of that computing power right now don’t know how many GPUs and to what capacity they should order and the manufacturers, like Nvidia, they don’t know how much they should produce.”<\/p>\n<\/div>\n

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