BlackRock, the world's largest asset manager, said in a research paper that widespread AI adoption could become an underappreciated source of demand for digital assets, positioning blockchain-based payment rails and tokenized computing capacity as foundational to an emerging machine-native economy.
In its paper titled "The Machine-Native Economy," BlackRock researchers Will Su, Robert Mitchnick, Jay Jacobs and William Helm wrote that the rise of AI and machine-to-machine payments could increase demand for blockchains and other programmable payment infrastructure, including stablecoins and on-chain assets. The paper also identified an opportunity for digital assets to support the compute market by allowing claims on AI processing capacity to be tokenized, traded and used as collateral.
"Together, these developments position AI as a structural catalyst for digital asset adoption and digital assets as a potential facilitator of the AI economy," the authors wrote. "This relationship remains underappreciated and could expand the role of digital assets as core infrastructure for an increasingly autonomous digital economy."
One of BlackRock's central arguments is that agentic AI — autonomous AI systems capable of acting independently — will increase demand for machine-native payment instruments. While existing payment rails can support some automation, they often require human involvement for account setup, credentialing and authorization. Merchant fees can also render low-value transactions uneconomic, and settlement times vary across providers.
Stablecoins, native cryptocurrencies and tokenized real-world assets are better suited to the high-frequency, sub-cent, around-the-clock machine-to-machine transactions that agentic commerce requires, BlackRock said. "Several types of digital assets may support agentic commerce, but stablecoins are likely to lead transactional use," the authors wrote.
On the compute side, the paper said the surging demand for AI processing power creates an opening for tokenization. AI companies could seek to lock in costs and capacity providers to manage risk, with those claims represented as transferable tokens that can be pledged as collateral or traded. AI agents could then automatically purchase computing resources as needed, potentially broadening institutional investor participation in the sector.
The thesis aligns with views long held by crypto executives. In July, Coinbase CEO Brian Armstrong argued that AI being a megatrend does not diminish crypto's importance, writing that AI agents would need programmable money rather than traditional banking rails. "If anything, it makes crypto more important," he said.
Crypto firms are already developing tools for that activity. Coinbase's x402 protocol and Tempo's Machine Payments Protocol were designed to let AI agents automatically pay for online services. Circle introduced agent wallets and USDC payment tools in May, and OKX launched its Agent Payments Protocol to support recurring payments and escrow arrangements where funds are released after task completion.
The research comes as broader policy discussions around AI continue to unfold, including an Australian 40-year economic outlook that recognized the "AI revolution" but omitted any mention of crypto.
