How AI Agents Are Reshaping Crypto: Inside BlackRock’s Latest Report

BlackRock September 2026 research paper, The Machine-Native Economy: How Digital Assets Connect Intelligence, Commerce, and Compute, examines what this could mean for crypto. 

Its central argument is that AI may create new demand for digital assets because machines need money and payment infrastructure designed for machine-to-machine activity.

Key Takeaways

• Stablecoins could become machine-native money for AI agents making frequent, low-value payments.

• Bitcoin could play a savings role, rather than becoming the primary currency for everyday machine payments.

• Tokenised compute could become a new crypto market as AI agents increasingly need processing power.

Why AI Agents Need Machine-Native Money

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BlackRock describes AI as machine-native intelligence and digital assets as “machine-native money”. The idea is relatively straightforward: if software becomes capable of acting independently in economic environments, it will need financial infrastructure that software can access and operate programmatically.

Imagine an AI agent asked to organise a business trip. It could search for flights, retrieve hotel prices, compare options, access data APIs and potentially make payments. Instead of a person manually approving every small transaction, the agent could execute a series of authorised payments automatically.

This creates a different set of requirements from traditional consumer payments.

AI agents may need to make transactions 24 hours a day, seven days a week, including very small payments for API calls, data access or computing resources. 

BlackRock argues that existing payment systems can face challenges around account setup, transaction costs, settlement and the economics of very small payments.

Blockchain-based systems can potentially address some of these requirements because they offer programmable settlement and digital ownership. 

Emerging protocols such as x402 are being developed specifically around machine-to-machine payments, while other initiatives including Stripe and OpenAI’s Agentic Commerce Protocol and Google’s Agent Pay Protocol are exploring ways to connect AI agents with payment infrastructure.

Why Stablecoins Could Lead Agentic Payments

Among digital assets, BlackRock identifies stablecoins as a particularly suitable instrument for agentic commerce.

Unlike volatile cryptocurrencies, stablecoins are designed to maintain a relatively stable value against a reference currency, usually the US dollar. That makes them easier to use when an AI agent needs to pay a predictable amount for a service.

The scale of the existing stablecoin market is also significant. BlackRock says circulating stablecoin supply exceeded $300 billion in September 2026, while adjusted stablecoin transaction volume surpassed $11 trillion in 2025.

The important point is that AI agents would not necessarily need to replace traditional payments completely. Instead, stablecoins could become another layer of infrastructure for transactions where machine-to-machine speed, programmability and small payment sizes matter.

For example, an AI agent could pay a few cents for an API request, obtain the required information, and immediately continue its task. At sufficient scale, millions of these transactions could create substantial demand for stablecoin infrastructure.

Bitcoin Could Become the Savings Layer for AI

BlackRock’s argument does not suggest that Bitcoin will necessarily become the main payment currency for AI agents.

Instead, the report describes a potential two-tier monetary structure: stablecoins for spending and Bitcoin for saving.

This distinction is important because Bitcoin’s characteristics are different from those of stablecoins. Stablecoins are designed around price stability, making them more convenient for everyday transactions. 

Bitcoin, meanwhile, is a scarce, non-sovereign digital asset that some investors view as a long-term store of value.

BlackRock references a February 2026 study from the Bitcoin Policy Institute involving 36 frontier AI models and 9,072 responses. 

When models were asked where they would store value, Bitcoin was selected 79.1% of the time. When asked what they would use for spending, stablecoins were selected 53.2% of the time.

However, this should be interpreted carefully. These figures come from a simulated study of AI models, rather than actual autonomous agents managing real-world treasuries. 

The results also varied between model providers. Therefore, the research provides an interesting indication rather than proof that future AI agents will actually hold Bitcoin.

Bitcoin and the Long-Term Savings Thesis

If autonomous systems eventually manage financial resources, Bitcoin could potentially serve as a reserve asset within some AI-related protocols or digital treasuries.

That possibility also connects with the broader narrative of Bitcoin as a non-sovereign asset and potential hedge against currency debasement or long-term fiscal risks. However, BlackRock does not turn this thesis into a specific Bitcoin price prediction.

Instead, the report is primarily about infrastructure and potential use cases. Its forward-looking arguments are conditional, and the broader agentic economy remains at an early stage.

Tokenised Compute Could Create a New Crypto Market

Payments are only one part of BlackRock’s machine-native economy. The report also identifies computing power as a potentially important digital asset market.

AI systems require enormous amounts of compute for training and inference. As AI agents become more autonomous, they may need to obtain computing resources dynamically according to price, availability, performance and location.

BlackRock argues that standardised claims on computing capacity could eventually become digital assets that can be financed, traded or used as collateral. 

Analysts cited in the report expect the core cloud businesses of major hyperscalers to generate more than $1 trillion in annual revenue by 2030, highlighting the scale of the underlying compute economy.

The potential workflow is intriguing. An AI agent could determine how much computing power it needs, compare available providers, purchase capacity and settle the transaction automatically.

In that scenario, crypto would not simply be an investment asset. Blockchain infrastructure could become part of the underlying marketplace through which machines purchase resources.

However, BlackRock also acknowledges that the ecosystem remains in its infancy. Agentic payment activity and liquid markets for tokenised compute are still limited, meaning substantial adoption would be required before these concepts become mature financial markets.

What BlackRock’s 2026 Report Could Mean for Crypto

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The broader message is that AI could expand crypto's role beyond human trading and investing.

If AI agents increasingly purchase data, APIs, software services and computing capacity, stablecoins could benefit from a new source of transaction demand. At the same time, tokenisation could make digital assets easier for software to identify, transfer and settle.

Bitcoin occupies a different position in this framework. Rather than being the obvious payment token for every machine transaction, it could potentially become a longer-term reserve or savings asset for autonomous systems.

For the crypto market, this creates several areas worth monitoring: stablecoin transaction volumes, machine-payment protocols, tokenised compute projects, AI-agent wallets and the infrastructure connecting AI systems with blockchain networks.

The key distinction, however, is between potential adoption and actual adoption. BlackRock’s report presents a structural thesis rather than a short-term trading signal or Bitcoin price forecast.

Conclusion

BlackRock’s The Machine-Native Economy presents an interesting framework for understanding how AI and crypto could converge. 

Stablecoins could provide the payment layer for AI agents, Bitcoin could potentially function as a longer-term savings asset, and tokenised compute could create an entirely new digital marketplace. 

Much of this remains experimental, but the direction of development is worth watching as AI agents become more capable of interacting with economic systems. 

For traders and crypto users, keeping up with these emerging trends and managing transactions carefully is increasingly important. 

Bitrue provides a platform designed to make crypto trading easier and safer, while giving users access to a broad range of digital assets and emerging market opportunities.

FAQ

What is BlackRock’s Machine-Native Economy report?

It is a September 2026 research paper examining how AI agents and digital assets could converge. BlackRock focuses particularly on agentic payments, tokenisation and computing markets.

Why does BlackRock think AI agents could use stablecoins?

Stablecoins offer relatively stable pricing, programmable transfers and 24/7 blockchain settlement, making them potentially suitable for frequent and low-value machine-to-machine payments.

Could AI agents use Bitcoin as a store of value?

Potentially. BlackRock cites research in which AI models selected Bitcoin as a store of value in 79.1% of responses. However, this was a simulated study and does not demonstrate real-world AI-agent adoption.

What is a tokenised compute?

Tokenised compute refers to representing claims on computing capacity as digital assets. BlackRock suggests these assets could potentially be traded, financed or used as collateral as demand for AI computing grows.

Is BlackRock predicting a Bitcoin price increase?

No. The report presents a research framework about potential structural demand from AI and does not provide a specific Bitcoin price target. Investors should therefore distinguish the report’s long-term infrastructure thesis from a short-term trading signal.

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