Kalshi Inc., a private prediction-markets exchange, has developed a new instrument that maps anticipated costs for computing power. The firm intends to provide a forward curve for compute - a term encompassing the electricity, data storage, memory, and other assets essential for AI operations.
"We are using prediction markets to build the forward curve, which will provide the market a view of what compute costs will be in the future for different grades and time-frames of GPUs," said Udesh Jha, Kalshi's chief risk officer.
In commodities markets like oil and gas, forward curves are a common tool that enables producers and consumers to secure prices and control volatility. For AI compute, the emergence of such financial instruments signals that computing power is becoming a standardized, tradeable commodity, much like electricity or bandwidth. This development could attract institutional investors and provide liquidity to a previously opaque market.
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The curve's form is expected to indicate the direction of GPU rental rates (graphics processing units). The boom in technology has spurred capital into fresh data-center projects, and certain analysts forecast that outlays on new facilities could eventually climb into the trillions of dollars.
"It's a key enabler for a lot of subsequent hedging, risk management and even speculative activities," Jha said.
As artificial intelligence workloads expand, the cost of compute has become a critical variable for tech companies and investors. Forward curves allow market participants to lock in future prices and plan capital expenditures. The emergence of such financial tools reflects the growing maturity of the AI industry, where predictable pricing can reduce uncertainty for large-scale deployments.
This development also underscores a broader shift: computing power is increasingly viewed as a resource that can be traded and hedged like traditional commodities. For example, data center operators facing volatile electricity costs or fluctuating GPU rental demand could use forward curves to stabilize their budgets. Similarly, AI startups developing long-term training projects could secure compute pricing in advance, protecting their margins. The ability to price and trade compute risk is likely to accelerate investment in AI infrastructure, as it provides financial clarity for multi-year capital commitments.
Kalshi is not alone in spotting this opportunity. Other derivatives marketplaces are similarly exploring the listing of compute-related futures.
In May, CME Group Inc. announced plans to introduce futures tied to a computing-power index developed by Silicon Data. Intercontinental Exchange Inc., which owns the New York Stock Exchange, is partnering with financial infrastructure company Ornn to offer compute futures.
A forward curve captures traders' expectations for an asset's or commodity's price at a particular future date. It displays the cost for future delivery and serves as a critical benchmark for buyers and sellers aiming to control their exposure and mitigate risks.
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