BlackRock expects standardized compute products, such as exchange-traded compute futures, to emerge as artificial intelligence adoption expands, according to a new research paper from the world's largest asset manager. The paper, "The Machine-Native Economy", also positions stablecoins as the payment rail for autonomous AI agents, sketching a vision of computing power traded like a commodity and dollar-pegged tokens settling machine-to-machine payments.

A commodity market for compute

BlackRock casts compute—the processing power that trains and runs AI models—as a resource that could follow the trajectory of large commodity markets, which built trading infrastructure over time to improve liquidity and risk management. Energy and agricultural markets spent decades building standardized, exchange-traded contracts so producers and buyers could hedge volatile prices—the infrastructure BlackRock argues compute has yet to grow into.

"We expect standardized products, including exchange-traded compute futures, to support more transparent price discovery and more effective hedging for both providers and consumers of compute capacity," the paper says.

The firm said claims on compute capacity could be represented, transferred, pledged as collateral, and settled on blockchains, a shift it believes could bring more institutional investors into the market.

Obstacles remain. The productivity of different generations of chips varies, the cost of energy differs by region, and workable standards have yet to emerge for cash settlement or for delivering contracted capacity. BlackRock described these as "important but ultimately resolvable design considerations." Those settlement and delivery standards are the precondition for any listed compute contract to function, which makes them the near-term milestone to watch.

Hyperscaler cloud revenue could reach $1.1 trillion by 2030

Sell-side analysts project that AWS, Microsoft's Intelligent Cloud segment—home to Azure—and Alphabet's Google Cloud will generate roughly $1.1 trillion in combined revenue by 2030, implying annual growth of about 29% in the years after 2025.

The paper suggests AI agents could use marketplace APIs to assess available capacity and compare offerings on price, latency, location, and hardware, before settling payment over rails such as x402, the Coinbase-introduced protocol that revives the web's long-unused HTTP 402 "Payment Required" status code to enable native, machine-to-machine payments.

Dollar-pegged tokens moved over $11 trillion in 2025

The paper draws on BlackRock's digital assets and ETF research teams. It was written by Will Su, head of digital assets research, and Robert Mitchnick, the firm's head of digital assets, and co-written by Jay Jacobs, U.S. head of equity ETFs, and William Helm, head of U.S. iShares product innovation.

"AI represents machine-native intelligence, while digital assets represent machine-native money," the paper says.

BlackRock argued that card networks and ACH carry onboarding requirements and settlement economics that are poorly suited to always-on, very low-value payments.

The circulating market capitalization of stablecoins topped $300 billion in September 2026. Adjusted stablecoin volume surpassed $11 trillion in 2025, on par with Visa and Mastercard, after growing at an 80% annual rate from 2020 through 2025—compared with roughly 8.5% for ACH. That expansion unfolded alongside new regulatory footing in the U.S., where the GENIUS Act, signed in July 2025, created the first federal framework for payment stablecoins.

Since May 2025, AI agents likely accounted for 0.6% to 7.5% of the $25.62 million in screened x402 payments, according to research from TRM Labs—a sliver of activity that shows how early machine-to-machine payments remain.

BlackRock is one of the founding validators of Circle's Arc blockchain, which launched its mainnet this month and was built in part for AI agents transacting autonomously. Arc uses Circle's USDC stablecoin as its native gas asset, tying the network directly to the dollar-pegged rails the paper describes.

Source: Cryptopolitan