AI and Blockchain: Grayscale Expert Names Three Scenarios for Growth in Demand for Public Networks
The rapid development of artificial intelligence opens up fundamentally new horizons for public blockchains. This is not just about speculative scenarios, but about fundamental changes in how digital agents will interact with the economy. Analyzing current trends, I identify three key areas that could become growth drivers for decentralized networks in the coming years.
Payments and programmable wallets
The most obvious source of new demand is transactions conducted by AI agents. Digital assistants performing tasks on behalf of users require programmable wallets for independent storage and spending of funds. This creates a need for infrastructure for micropayments, cross-border settlements, and automated trading. Ethereum and Solana appear best prepared here: their open ledgers provide round-the-clock capability for programmable transactions without human involvement.
Verifiable records and identification
The second important aspect is the verifiability of AI operations. As algorithms are delegated increasingly responsible tasks, companies will need to record which models and data were used in decision-making. A public blockchain can serve as an independent registry for such information. The same mechanism is applicable for identifying both humans and digital agents, as well as storing their reputation. A notable example is the World project, which already applies such principles in practice.
Decentralization of computing resources
The third factor is related to the concentration of control over AI in the hands of a limited number of corporations. Decentralized networks offer an alternative: participants can provide computing power, own infrastructure, and participate in its governance. This is not only a matter of efficiency but also a matter of distributing the economic benefits of AI development.
However, the practical utility of such a symbiosis remains a subject of lively debate. Researchers from the IC3 consortium rightly note that a ledger entry can confirm the existence of data at a certain point in time but does not prove the correctness of the model's operation itself. This is an important limitation to consider when assessing prospects.
My conclusion: despite skepticism, the potential for interaction between AI and blockchain is enormous. Current discussions only confirm that we are at the beginning of the journey, and it is precisely now that the foundations for future innovations are being laid.