Will the Rise of AI Agents Result in a Stablecoin Boom?
BlackRock argues that AI agents could become a new source of demand for stablecoins and digital assets. But where do blockchain-based payments offer a real advantage over existing rails—and is an agent-driven stablecoin boom actually close?
On September 22, 2026, BlackRock published the white paper The Machine-Native Economy: How digital assets connect intelligence, commerce, and compute, written by Will Su, Robert Mitchnick, Jay Jacobs and William Helm.
BlackRock's central argument is that AI and digital assets, which have largely developed separately, may increasingly intersect as AI agents become capable of making payments, trading assets and purchasing computing resources autonomously.
BlackRock’s The Machine-Native Economy states:
“At the core of this convergence, AI and digital assets both arise from a common foundation: AI represents machine-native intelligence, while digital assets represent machine-native money.”
Part of BlackRock's argument is that increasing use of AI agents capable of autonomously making decisions and executing transactions could increase demand for stablecoins. BlackRock cites a Bitcoin Policy Institute study that tested 36 frontier AI models across 9,072 monetary scenarios. The models selected stablecoins in 53.2% of payment scenarios, while Bitcoin was selected in 79.1% of long-term store-of-value scenarios.
The paper’s concluding thesis is as follows:
“As AI adoption broadens and agentic systems become more capable, digital assets could become increasingly integral to AI’s economic infrastructure, expanding utility across stablecoins, tokenized RWAs, and native cryptoassets that support blockchain settlement.”
BlackRock’s paper makes the case that AI agents could become a new source of demand for stablecoins and other digital assets. Yet AI agents can already use existing payment infrastructure, raising a more practical question: where do digital assets offer something existing systems do not?
BlackRock illustrates one potential use case with an AI agent tasked with booking flights and hotels. The primary agent sends the research task to a specialized travel agent, which uses x402, an open payment protocol introduced by Coinbase, to pay for access to flight and lodging pricing data. Once the information is returned, the primary agent books the trip through the providers’ standard checkout processes.
While this represents a workable payment flow, the benefit of introducing a digital asset payment layer over existing payment methods is less clear. Other types of transactions provide a clearer case for their use.
The case for digital assets is stronger in transactions that existing payment rails are less suited to handle, including high-frequency micropayments for compute, data or API access and direct payments between autonomous agents. Beyond payments, tokenized markets could allow agents to trade and rebalance assets around the clock without being limited by traditional market hours. If these types of activities grow alongside the use of AI agents, they could create a new source of demand for stablecoins and other digital assets.
The open question is how much additional demand AI agents will actually generate. Many of the transactions agents may perform can already be handled by existing payment systems, while agent-to-agent payments and sub-cent transactions for computing resources remain emerging use cases. BlackRock makes a case for AI and digital assets becoming increasingly complementary as autonomous agents take on a larger economic role. There is not yet evidence, however, that this convergence will translate into an imminent boom in stablecoin usage.
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