BlackRock Says AI Agents Could Fuel Crypto Demand as Autonomous Systems Need Payment Infrastructure

BlackRock Identifies AI Agents as Overlooked Crypto Demand Driver

BlackRock, the world's largest asset manager, released a research paper this week titled "The Machine-Native Economy," arguing that AI agents could become a major, underappreciated source of crypto demand1

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. The paper from BlackRock's Digital Assets Research team, led by Will Su and Robert Mitchnick alongside the firm's U.S. equity ETF and iShares product leads, positions artificial intelligence—not regulation or institutional buying—as the next structural catalyst for digital asset adoption1

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. The core thesis rests on a simple premise: "AI represents machine-native intelligence, while digital assets represent machine-native money," making their convergence inevitable1

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Agentic AI Creates Payment Infrastructure Gap

The research focuses on agentic AI—autonomous systems capable of planning and executing multi-step tasks with minimal human oversight1

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. These AI agents don't just recommend actions but complete them independently, booking flights, paying bills, and handling transactions without human intervention. This autonomy immediately surfaces a critical problem: traditional payment rails weren't built for machine-to-machine transactions2

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. Opening bank accounts or obtaining credit cards requires human identification, while merchant fees make economic sense for $40 purchases but become prohibitive for fraction-of-a-cent API calls1

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. Account setup, credentialing, and authorization often demand human involvement, creating friction for autonomous systems2

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Stablecoins Positioned as Solution for Machine-Native Economy

BlackRock identifies stablecoins—cryptocurrencies pegged to stable assets like the U.S. dollar—as the ideal instrument for AI-driven financial interactions1

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. Stablecoin adoption has accelerated dramatically, with adjusted transaction volume topping $11 trillion in 2025, placing it in the same range as Visa and Mastercard's annual payment volumes1

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. While still smaller than the $93 trillion moved through traditional ACH bank transfers that year, stablecoin volume has grown roughly 80% annually since 2020, compared with about 8.5% for ACH1

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. The circulating market cap for stablecoins exceeded $300 billion as of September 20261

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. These digital assets can move around the clock, settle almost instantly, and operate without traditional banking infrastructure1

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. BlackRock argues that stablecoins, native cryptocurrencies, and tokenized real-world assets are particularly well-suited to high-frequency, sub-cent payments that autonomous systems require2

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Programmable Payment Rails Already Under Construction

Several companies have already built programmable payment rails to support AI-driven machine-to-machine transactions. Coinbase developed the x402 protocol around the largely unused "HTTP 402: Payment Required" web code, enabling software to pay for data feeds or API calls within the same request without accounts or human authorization1

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. Amazon integrated stablecoin payments into its AI cloud tools through partnerships with Coinbase and Stripe, allowing AI agents to automatically pay for APIs, data feeds, and bookings mid-task1

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. Google built its own agent-payments layer with backing from Coinbase and the Ethereum Foundation, extending its Agent2Agent framework to handle cards, stablecoins, and real-time bank transfers1

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. Circle introduced agent wallets and USDC payment tools in May, while OKX's Agent Payments Protocol supports recurring payments and escrow arrangements2

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. Tempo's Machine Payments Protocol offers another avenue for autonomous payment processing2

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Current Usage Remains Limited Despite Infrastructure Growth

Despite the infrastructure buildout, real-world usage by AI agents remains thin. Blockchain analytics firm TRM Labs examined $52.7 million in x402 settlements this year and found AI agents likely accounted for somewhere between 0.6% and 7.5% of that value—most traffic resembled ordinary automated scripts rather than genuine autonomous agents1

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. BlackRock acknowledges this isn't happening at scale yet but believes the financial infrastructure is being built ahead of widespread adoption1

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Tokenized Computing Capacity Opens New Digital Asset Market

Beyond payments, BlackRock sees opportunity in tokenized computing capacity. Running AI is expensive, and demand for cloud computing continues climbing. The firm cites analyst estimates projecting combined 2030 revenue for Amazon, Microsoft, and Google's cloud divisions at roughly $1.1 trillion1

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. The research envisions compute packaged into standardized contracts similar to oil or wheat futures that could be bought, sold, used as collateral, or settled automatically on blockchains1

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. AI agents could shop for the cheapest available server capacity and pay directly, job by job, without humans negotiating cloud contracts1

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. As AI companies seek to lock in costs and manage risk, claims on computing capacity represented as tokenized assets could be transferred, pledged as collateral, or traded, potentially broadening institutional investor participation2

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. "As agents become more capable and persistent, standardized claims on compute capacity could become a significant digital asset use case for financing and programmable settlement," BlackRock stated1

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Industry Executives Align on AI-Crypto Convergence

BlackRock's thesis echoes arguments from crypto industry leaders. Coinbase CEO Brian Armstrong pushed back against calls for crypto to pivot to AI in July, arguing that AI agents will increase demand for crypto-based financial services. "AI being a megatrend takes nothing away from crypto," Armstrong wrote, because AI agents need programmable money rather than traditional banking rails. "If anything, it makes crypto more important," he added2

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. BlackRock's institutional perspective lends weight to this argument, potentially bringing the AI-crypto thesis to a broader audience of institutional investors2

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. The authors conclude that "together, these developments position AI as a structural catalyst for digital asset adoption and digital assets as a potential facilitator of the AI economy," while noting this relationship "remains underappreciated and could expand the role of digital assets as core infrastructure for an increasingly autonomous digital economy"2

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