AI will become a catalyst for demand for public blockchains: Grayscale analysis
The development of artificial intelligence is shaping fundamentally new use cases for public blockchains—from operations with AI agents to verifiable digital records. This is not just a hypothesis but a conclusion that an increasing number of experts are reaching, including the head of Grayscale's research division, Zach Pandl.
Payments as the Main Driver
The most obvious source of future demand is payment infrastructure. Digital assistants performing tasks on behalf of users require programmable wallets with the ability to self-custody and spend funds. This opens up a need for solutions for micropayments, cross-border settlements, automated trading, and risk management.
In this context, Ethereum and Solana look like the most promising networks. Open ledgers provide round-the-clock capability for executing programmable transactions, which is critical for autonomous systems.
AI Verification and Decentralization of Resources
The second important direction is the recording of verifiable logs about the operation of algorithms. As AI is delegated an increasing number of tasks, companies will need to document which models, data, and rules were used in decision-making. A public blockchain can serve as an independent registry of such information, as well as be used to identify people and digital agents and store their reputations. An example here is the World project.
The third factor is the concentration of computing resources and control over AI in the hands of a limited circle of corporations. Decentralized networks, where participants provide resources and take part in managing infrastructure, could become a real alternative to this monopolization.
Skepticism and Prospects
However, one should not ignore the critical stance either. Researchers from the IC3 consortium have noted that many arguments about the benefits of blockchain for AI require additional evidence. A record in a distributed ledger confirms the existence of data at a specific moment but does not guarantee the correctness of the model's operation itself.
Nevertheless, the trend is obvious: at Franklin Templeton, AI agents are already being called one of the potential drivers of crypto payments, emphasizing the possibility of settlements between autonomous programs without human involvement.
My view: The combination of AI and blockchain is not hype but an inevitable evolutionary step. The only question is which networks will be able to offer sufficient throughput and low fees for large-scale micropayments. Investors should closely watch projects that are already building the infrastructure for this future today.