Grayscale has issued an analysis that wider adoption of AI will increase demand for public blockchains.

On Aug. 12, blockchain media outlet CoinPost reported that Zach Pandl (잭 팬들), head of Grayscale Research, published a report saying AI and public blockchains are complementary.

The report argues that as AI grows, the areas where blockchains are needed will also expand. Pandl identified three fields where demand could rise: financial transactions and payments; verification of records for computation, identity and reputation; and decentralised AI infrastructure. "AI and public blockchains are complementary," he said, adding that public blockchains can address AI-specific demand that existing systems struggle to process.

It cited payments by AI agents as the most direct source of demand. For AI agents to act in place of humans, they need programmable wallets that can hold and deploy funds without intermediaries, it said. That structure could lead to demand for micropayments, instantly processed cross-border payments, automated trading and risk management, it added.

In this process, it mentioned Ethereum (ETH) and Solana (SOL) as public blockchains that can perform related functions. The report said that as AI agents carry out economic activity more autonomously, on-chain payment systems could be used more than existing financial infrastructure.

It also said the deeper companies use AI, the greater the need for a verifiable record layer. As companies delegate more decision-making to AI, they need to verify which models, data and rules were used to reach decisions, and users must be able to distinguish online whether the counterpart is a human or an AI agent, it said.

Pandl cited the operation of social networking services, saying there could be a need to confirm whether an account is run by a real individual without revealing identity information about the account holder. He also pointed to the growing importance of trustworthy reputation records as more critical tasks such as investing or making purchases are delegated to AI agents.

It cited Worldcoin as an example of an identity service built on public blockchains. He presented as an advantage the ability to leave such records on a "transparent and neutral foundation" rather than with a single company or government. He argued that recording identity and reputation data on verifiable public infrastructure, rather than having a specific entity manage them exclusively, could become more important during the spread of AI.

The report also focused on the concentration of AI infrastructure. Pandl said capital, computing resources and control around AI development are currently concentrated in a handful of cutting-edge AI research institutions and large cloud providers. He said such a structure increases concerns over governance, bias and censorship.

As an alternative, it presented decentralised networks such as Bittensor. Pandl described Bittensor as an "open AI ecosystem approach" that anyone can access, contribute to and own part of. He viewed it as an alternative model in which network participants share resources and outcomes, rather than AI infrastructure being run by a small group of operators.

Grayscale's report ultimately concluded that the spread of AI could create three streams of demand for blockchains. These are demand for financial infrastructure that manages funds without intermediaries, demand for a record layer that verifies computation, identity and reputation, and demand for a foundation for an open AI ecosystem in which users can have ownership. It said the intersection of AI and blockchain could expand beyond a simple combination of technologies to include payment infrastructure, digital identity and decentralised computing structures.