Chainlink Labs’ head of institutional strategy, McCormick, said autonomous AI agents and physical robots could become a growing source of blockchain activity as software and machines require systems to make payments, settle transactions and exchange data without human intervention.
Speaking on Aug. 20 at the Wyoming Blockchain Symposium 2026 during a discussion with Sparks, McCormick argued that crypto networks could increasingly operate as settlement infrastructure for automated systems. In that model, AI agents would use digital assets and stablecoins to pay for services, move funds and execute instructions across blockchain networks, including when users are offline.
The prospect places interoperability—the ability for separate blockchains to exchange assets and messages—closer to the center of the industry’s institutional pitch. McCormick said cheaper blockchain development, aided by improving AI tools, could lead to a larger number of specialized networks. More networks would create a greater need for technology that connects them rather than leaving liquidity and information confined to individual chains.
Ai agents could transact beyond market hours
McCormick described AI-driven software agents that could trade or act on a user’s behalf in tokenized markets operating beyond conventional market hours. Tokenized markets refer to blockchain-based representations of financial assets, which can be designed to settle or change hands outside the schedules used by traditional exchanges.
Such systems would need rules governing how much capital an agent can use, which assets it can acquire and when it must seek human approval. The technical ability to transact continuously does not remove those constraints, particularly for regulated financial products. Yet it gives automated systems a payment and settlement route that could run across weekends and global time zones.
The idea is already beginning to show up in blockchain transaction data. A Keyrock industry report cited in the source material said autonomous programs executed roughly 176 million on-chain transfers between May 2025 and April 2026. The report also found that nearly 99% of machine-initiated payments were settled using USD Coin, or USDC.
That preference points to a practical requirement for machine-to-machine commerce. Software agents handling many small payments need an asset whose value is relatively predictable; sharp price changes in the token used for settlement could alter the cost of a service or cause a pre-set payment limit to fail. Dollar-linked stablecoins are therefore more suited to routine automated transfers than volatile cryptocurrencies whose prices can move significantly within minutes.
High transaction counts alone do not show that autonomous agents are driving substantial economic value. Bots have long carried out repetitive on-chain tasks, including arbitrage, liquidations and protocol maintenance. The more consequential development would be agents that can independently purchase data, compute power, transport services or tokenized financial products under defined permissions. That would turn blockchain payments from an application-specific feature into a component of automated software operations.
Wyoming’s Frontier Token used as cross-chain example
McCormick pointed to Wyoming’s Frontier Token as an example of a stable token designed for distribution across multiple blockchains. He said the project uses Chainlink’s Cross-Chain Interoperability Protocol, or CCIP, to support that multi-network approach.
CCIP is designed to let applications transmit tokens and data between supported blockchains. For a token issuer, cross-chain infrastructure could reduce the need to build separate systems for every network where the asset is available. It could also help keep an asset usable where different institutions, applications or users have selected different chains.
Wyoming’s involvement gives the discussion a public-sector dimension. State-linked token projects face a different set of demands from experimental crypto launches: distribution mechanisms, controls, security reviews and operational accountability can matter as much as the underlying blockchain. A token meant to function across networks must also avoid becoming fragmented into disconnected versions whose supply, ownership records or redemption processes cannot be reliably reconciled.
McCormick’s framing suggests that interoperability providers are seeking to serve this coordination layer. If AI lowers the cost of launching customized chains, institutions may choose networks optimized for distinct assets, privacy settings or compliance processes rather than concentrating activity on a small number of general-purpose blockchains. The resulting system would make the links between chains more commercially valuable, especially where payments and information must travel together.
Physical machines add a second use case
McCormick extended the argument beyond software agents to physical machines, including humanoid robots working in docks and factories. These machines could potentially communicate with other systems and pay for resources using stablecoins, digital assets and blockchains, he said.
A factory robot, for example, might need to obtain access to data, book a maintenance service, pay a charging station or verify delivery status. Blockchain-based rails could provide a shared record and settlement mechanism where several companies’ systems need to coordinate. Stablecoins could offer a way to price those automated payments in familiar currency terms.
That vision remains dependent on systems outside the blockchain itself. Robots require reliable identity controls, secure hardware, network access and clearly defined legal responsibility when a machine makes an erroneous or unauthorized payment. Companies would also need to decide whether a blockchain is more efficient than conventional payment APIs or internal databases for a given operation.
The strongest near-term use cases are likely to involve controlled environments where participants already have contractual relationships and where a shared settlement record reduces reconciliation work. Ports, logistics networks and industrial supply chains are examples where multiple organizations can exchange data and payments around the same physical event.
McCormick joined Chainlink Labs in June after previous roles at eToro and Morgan Stanley. His remarks reflect a strategy that connects the AI narrative to infrastructure rather than to a single consumer-facing product: more autonomous systems could mean more small, continuous transactions, while more specialized blockchains could increase demand for tools that move assets and verified information between them.
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