BlackRock is increasingly connecting the rise of artificial intelligence with the expansion of digital assets. In a new research paper titled “The Machine-Native Economy,” the world’s largest asset manager argues that broader AI adoption could create new demand, utility and applications across the digital asset economy.

BlackRock’s thesis is not that AI and crypto are simply two parallel technology trends. Instead, the firm sees them as increasingly complementary layers of a digital economy in which autonomous software can make decisions, access services and eventually transact with significantly less human involvement.

AI Agents Could Need a New Payment Layer

BlackRock describes artificial intelligence as machine-native intelligence and digital assets as a potential form of machine-native money. Payments typically rely on bank accounts, card networks, identity checks, business hours, permissions and interfaces built around people actively initiating transactions.

Autonomous AI agents introduce a different operating model. An AI system could potentially need to pay for an API request, purchase a dataset, acquire cloud resources, subscribe to software or compensate another digital service hundreds or thousands of times without waiting for a person to manually approve each transaction.

BlackRock points to emerging infrastructure including Coinbase’s x402 protocol, Stripe and Tempo’s Machine Payments Protocol and the Agentic Commerce Protocol developed by Stripe and OpenAI as examples of new payment frameworks designed around software-driven economic activity.

EtherWorld previously covered the Polygon Agent CLI, which integrates stablecoin payments and x402 so autonomous agents can access APIs and services while abstracting away gas complexity. Similarly, Mastercard Agent Pay for Machines is exploring how traditional payment infrastructure, stablecoins and blockchain rails could work together for machine commerce.

That trend also fits a broader payments transition. EtherWorld’s explainer on what enterprises need to know about stablecoins examined how businesses are increasingly looking at stablecoins for settlement, treasury operations and cross-border payments, while Can Stablecoins Replace International Bank Transfers? explored their potential role in 24/7 global money movement.

Tokenized Assets Could Become Machine-Readable Finance

Traditional financial products often depend on separate databases, brokers, custodians and settlement systems. Tokenization can represent ownership and transfer rules directly through blockchain-based infrastructure, making assets easier for software to interact with programmatically.

Instead of merely holding a payment balance, an AI agent could eventually interact with tokenized Treasuries, funds, deposits or other financial instruments according to predefined rules. An agent managing corporate liquidity, for example, could theoretically move idle funds into an approved tokenized yield product and convert them back into stablecoins when payments need to be made.

BlackRock itself has been moving deeper into this area. EtherWorld previously reported that BlackRock expanded its Ethereum strategy through tokenized Treasury funds, while Ondo brought tokenized versions of BlackRock’s IVV ETF and Micron shares onchain.

As explored in Why Institutions Are Suddenly Taking Ethereum Seriously?, financial institutions increasingly view Ethereum not just as a speculative crypto network but as infrastructure for stablecoins, tokenized assets and settlement. That shift is also reflected in the launch and funding of Ethereum Institutional, which is focused specifically on tokenization, collateral systems, stablecoins and institutional onchain settlement.

Our latest research paper explores the growing connection between AI and digital assets and explains why broad AI adoption may drive new demand, utility and applications across the digital asset economy. https://t.co/z5T88Orble pic.twitter.com/GMxQqTVmUN

— BlackRock (@BlackRock) September 22, 2026

BlackRock Sees Compute Emerging as a Financial Asset

AI systems require enormous amounts of GPU capacity, cloud infrastructure and specialised hardware. As demand grows, BlackRock argues that access to compute could increasingly be standardised, priced and traded more like a commodity or financial contract.

An autonomous system could evaluate computing resources based on hardware type, location, latency, performance and price, purchase the required capacity and settle payment programmatically. EtherWorld’s Top 10 AI-Blockchain Projects to Watch in 2026 highlighted projects building marketplaces around decentralised compute, agents, data and AI infrastructure.

Meanwhile, Who’s Building for Ethereum’s AI Agents? has tracked the broader Ethereum stack emerging around agent identity, payments, execution and verification. BlackRock’s report brings a more institutional framing to the same trend.

Why This Matters for Ethereum & Digital Assets

BlackRock’s research should not be interpreted as an announcement that it is launching a new AI token, stablecoin or blockchain product. It is a research thesis about where digital asset infrastructure could gain additional utility if autonomous AI systems become more economically active.

Agentic payments are still early. Compute markets lack universally accepted standards. Identity, compliance, security and interoperability remain unresolved challenges. For years, much of the discussion around digital assets has centred on humans buying, trading or investing in cryptocurrencies.

EtherWorld previously examined this question in Is Crypto x AI the Next Big Hype Cycle?, where the key issue was whether autonomous finance and agent-based commerce could become crypto’s next major application category.

Grayscale has reached a similar conclusion. Its Head of Research has argued that autonomous agents could generate new demand for public blockchains through wallets, programmable payments, identity systems and decentralised infrastructure, as covered in EtherWorld’s Grayscale Research Head Bets on Blockchain for AI.

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