BlackRock is arguing that the wider adoption of AI could create new demand for stablecoins and blockchain payments.
According to the asset manager, autonomous AI systems may require financial infrastructure built for machines, and blockchains could also become a way to pay for the computing resources those systems use.
Three Areas of Convergence
In a paper it published on September 22, the firm described AI as “machine-native intelligence” and digital assets as “machine-native money.”
It argued that the technologies, which have largely developed along separate tracks, are beginning to converge as AI systems gain the ability to interact with financial networks and carry out transactions with limited human involvement.
BlackRock focused on three areas of overlap, with the first being tokenization. Here, large language models divide text into tokens that can be processed numerically, while blockchains represent value and ownership claims as digital tokens. Their functions may be different, but both systems translate information into standardized formats that machines can handle.
Another area BlackRock identified was agentic commerce, where AI agents can make financial transactions. According to the company, this could increase demand for programmable payment infrastructure, and stablecoins and other cryptocurrencies could serve as payment and settlement instruments.
Traditional systems such as card networks and the Automated Clearing House (ACH) already support automated payments; however, per the paper, their onboarding requirements and settlement economics can make them less suited to continuous, very low-value transactions that require programmable execution.
The third area is computing capacity. BlackRock cited analyst estimates that hyperscaler cloud revenue could exceed $1 trillion annually by 2030, and standardized claims on computing capacity, the paper argues, could become a digital asset use case for financing and programmable settlement.
CZ and Arthur Hayes Have the Same Idea
The firm’s argument extended beyond using crypto to pay for goods and services. It also posited that as AI agents become more capable and operate for longer periods, they need access to computing resources through standardized, transferable claims.
Such assets could then allow financing and settlement to take place through programmable systems rather than relying entirely on conventional processes. The report also drew a distinction between the two technologies’ roles. AI interprets information and directs activity, while blockchains can provide machine-readable assets and rules for transferring them.
Smart contracts can apply predefined conditions to transactions, allowing assets to move when the required criteria are met. Essentially, BlackRock describes AI as a potential structural catalyst for digital asset adoption, while presenting digital assets as possible infrastructure for an increasingly autonomous economy.
However, the paper’s case rests on whether autonomous systems can create enough demand for programmable payments and tokenized claims to justify broader use.
As CryptoPotato reported previously, Arthur Hayes has argued that agents consume floating-point operations, not groceries, and may want a token redeemable for compute. Additionally, in June, Changpeng Zhao told Galaxy Research that agentic trading and payments would arrive in months, not years, and would use crypto because blockchains already speak in APIs.
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