Zach Pandl, Head of Research at Grayscale, stated that the proliferation of artificial intelligence will create new demand for public blockchains. In his research for Grayscale, he highlighted three key directions—AI agent-involved finance, verifiable records of computations and identity, and decentralized alternatives to centralized AI.
According to Pandl, infrastructure for these scenarios could be provided by four cryptocurrency networks, linked to three potential needs of the AI economy:
- Ethereum – settlement infrastructure for AI agent finance;
- Solana – fast blockchain settlements for the agent economy;
- World – verifiable digital identity;
- Bittensor – decentralized alternative to centralized AI platforms.
AI Agents Will Create Demand for Blockchain Payments
Pandl believes that artificial intelligence and public blockchains are complementary technologies. As AI spreads, traditional financial infrastructure may face new requirements that are better met by the capabilities of programmable blockchain networks.
The most obvious example, according to the researcher, is finance involving AI agents. Such systems will be able to act on behalf of users, but they will need programmable wallets capable of storing and using funds without constant human intermediation.
According to Pandl, the activity of AI agents could stimulate demand for:
- micropayments;
- instant cross-border settlements;
- automated trading;
- automated risk management.
It is precisely for such scenarios, in Grayscale's view, that Ethereum and Solana are suitable as infrastructure for settlements.
At the same time, the development of agentic AI will require not only payments but also ways to verify the actions of the agents themselves. For example, companies will need to determine which models, data, and rules the AI used when making a particular decision.
Blockchain Could Become a Layer for Identity and Reputation
Another direction Pandl mentioned is creating verifiable records of computations, human identity, and the reputation of AI agents.
This is especially important in cases where a user grants an AI the right to perform financial or other high-risk actions on their behalf. Before making an investment or purchasing goods on a person's behalf, an agent may need a verified reputation.
Separately, the researcher drew attention to the problem of distinguishing between humans and AI on the internet. For example, social platforms could verify whether an account belongs to a unique human without requiring disclosure of their identity.
In this context, Grayscale sees a potential role for World. The World infrastructure could be used to verify human identity and distinguish between humans and AI agents.
Bittensor Offers an Alternative to Centralized AI
The third direction Grayscale identified is decentralized artificial intelligence. Pandl noted that the development of AI concentrates capital, computational resources, and control in the hands of a small number of technology companies.
In his opinion, this raises questions regarding the governance, bias, and censorship of AI systems. An alternative could be open, decentralized networks that users can access, contribute to, and own a stake in.
One example Pandl named is Bittensor and its token $TAO.
However, the network itself was previously at the center of a debate about its level of decentralization. One of the key developers, Covenant AI, announced its departure from Bittensor, accusing the project's leadership of de facto centralization and pressure on the ecosystem. Amid the conflict, the market capitalization of $TAO decreased by approximately $820 million.
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