Ethereum co-founder Vitalik Buterin on Saturday proposed using personal AI agents to vote on behalf of users in decentralized governance systems, a model he said could reduce the concentration of power among delegates and address one of the core structural limits of DAOs.
In an X post outlining the concept, Buterin argued that the main barrier to effective decentralized decision-making is not voter participation but human attention.
With thousands of proposals spanning multiple technical and economic domains, most token holders lack the time or expertise to evaluate each issue, leading them to delegate their voting power to a small group of active participants.
AI Agents Positioned As Alternative To Delegation
Buterin said personal large language models trained on an individual’s preferences, writings and past decisions could automatically vote on routine matters while escalating only high-importance or ambiguous proposals for direct input.
Such a system would allow governance to scale without transferring long-term control to professional delegates, a dynamic that has increasingly drawn criticism in major DAO ecosystems where a small number of addresses influence a large share of outcomes.
Governance Markets And Machine-Ranked Proposals
The post also outlined “suggestion markets,” where proposals or arguments could be tokenized and evaluated through prediction-market-style mechanisms, with AI systems allocating capital toward the highest-quality inputs.
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This structure would shift governance from simple token-weighted voting toward a model that financially rewards useful contributions and filters large volumes of information before it reaches participants.
Privacy Infrastructure Seen As Critical
Buterin said privacy-preserving technologies such as zero-knowledge proofs and secure multi-party computation would be required for the model to function in areas involving sensitive information, including internal disputes, funding allocations and negotiations.
In such a framework, AI systems could analyze confidential data and output only a decision, allowing collective governance without exposing underlying information or granting unilateral authority to a small group.
Broader Implications For Digital Democracy
The proposal frames AI not as a replacement for human decision-making but as a coordination layer that enables large-scale participation.
If implemented, the model could alter how decentralized organizations, online communities and potentially public institutions manage decision flows, shifting governance from attention-limited voting toward continuously active, preference-driven systems.
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