Vitalik Buterin proposes artificial intelligence voting assistants to reshape decentralized governance models across the global Ethereum and DAO ecosystem

When Vitalik Buterin talks about the future of governance, people in crypto tend to listen.

The Ethereum co-founder recently shared his thoughts on how artificial intelligence might help decentralized communities make better decisions — and perhaps fix some of the nagging issues that have followed DAOs for years.

In a post on X, Buterin argued that AI isn’t just about chatbots or code generation.

It could actually reshape how decentralized governance works, especially in systems where thousands of people are expected to vote on complex proposals.

The Real Problem Isn’t Voting — It’s Attention

At the heart of the issue, according to Buterin, is something surprisingly human: limited attention spans.

Decentralized autonomous organizations (DAOs) are designed to be democratic.

In theory, token holders can vote on proposals, funding decisions, protocol upgrades, and more.

In reality, most people don’t have the time — or the technical expertise — to carefully review every proposal that pops up.

Research suggests average DAO participation rates sit somewhere between 15% and 25%. That means the vast majority of token holders don’t actively engage in governance.

Over time, that can lead to power concentrating in the hands of a small, active minority.

And in worst-case scenarios? It opens the door to governance attacks.

If a malicious actor quietly accumulates enough tokens, they could push through a harmful proposal while most members aren’t paying attention.

Delegation Helps — But It Comes at a Cost

To deal with low engagement, many DAOs allow delegation.

You can assign your voting power to someone you trust — a more active community member or a recognized expert.

But Buterin believes delegation creates its own problems.

Once you hit that “delegate” button, your influence effectively ends.

Decision-making power consolidates among a small group of delegates, which undercuts the spirit of decentralization.

Instead of solving the attention problem, delegation can slowly reintroduce centralization — the very thing DAOs were built to avoid.

AI Assistants That Vote Based on Your Values

Here’s where AI enters the picture.

Buterin proposes that personal AI agents — powered by large language models (LLMs) — could act as governance assistants.

Rather than blindly delegating to another human, users could rely on an AI trained on their preferences.

Imagine an AI that reads your past posts, conversations, governance comments, and direct instructions.

Over time, it understands your values and policy leanings.

When a proposal appears, your AI reviews the documentation, evaluates the risks and trade-offs, and casts a vote aligned with your preferences.

If the issue is particularly important or unclear, the AI could flag it and ask you directly, presenting a summarized version of the relevant context so you can make an informed decision.

In other words, instead of disengaging from governance, you’d have a digital extension of yourself doing the heavy lifting.

Others Are Exploring Similar Ideas

Buterin isn’t alone in thinking this way.

Researchers like Lane Rettig at the Near Foundation have discussed similar concepts, including AI-powered “digital twins” that could vote on behalf of DAO members.

The goal isn’t to remove humans from governance, but to help them participate more effectively — even when they don’t have hours to spare each week reading technical proposals.

As DAOs expand into areas like decentralized finance, public goods funding, gaming ecosystems, and even city-level experiments, the complexity of decisions will only increase.

AI could become less of a luxury and more of a necessity.

The Privacy Dilemma in Decentralized Decisions

But governance challenges don’t stop at participation rates.

Some decisions require sensitive or confidential information — think internal disputes, negotiations, or funding allocations involving private data.

Traditionally, organizations solve this by granting significant authority to a few trusted individuals who can see that information.

But that reintroduces hierarchy and trust assumptions.

Buterin floated an alternative: users could submit their personal AI into a kind of secure “black box.”

The AI would access private information, process it, and output only a judgment — without revealing the underlying sensitive data to the broader group.

In this model, no one sees your private information.

No one sees inside your personal AI. They only see the decision it produces.

It’s a radical idea, but it aligns with crypto’s long-standing obsession with privacy-preserving computation — from zero-knowledge proofs to encrypted smart contracts.

More Information Means More Risk

There’s a catch.

If governance participants start feeding massive amounts of personal data into AI agents — writing samples, conversation logs, voting history — the privacy stakes rise dramatically.

Protecting that data becomes critical.

A compromised personal governance AI could reveal not just your voting preferences, but intimate details about your beliefs, strategies, or affiliations.

Ethereum itself has been steadily evolving, transitioning to proof-of-stake in 2022 and continuing to focus on scalability and decentralization improvements.

Governance discussions are increasingly important as the ecosystem matures and handles billions of dollars in value.

The way decisions are made today could shape the network’s resilience tomorrow.

AI in Crypto Is Growing Fast

This conversation also reflects a broader trend: AI and crypto are converging in unexpected ways.

From AI-powered trading bots to autonomous on-chain agents and prediction markets, projects are experimenting with machine intelligence embedded directly into blockchain systems.

Some communities are even exploring AI-managed treasuries and automated grant evaluation processes.

If governance can become more informed, less centralized, and more privacy-preserving through AI, it could address some of the structural weaknesses critics have pointed out for years.

But the risks are real. Poorly designed AI systems could be manipulated, biased, or hacked — introducing new forms of centralization rather than eliminating them.

What’s Next?

The big question isn’t whether AI will enter DAO governance — it’s how.

We’re likely to see early experiments: opt-in AI voting assistants, secure computation frameworks, and privacy-enhancing governance tools.

Some will fail. Others may quietly reshape how decentralized communities function.

The challenge will be balancing automation with accountability.

If your AI votes on your behalf, who’s responsible when something goes wrong — you or the algorithm?

For now, Buterin’s proposal adds fuel to an ongoing debate: decentralization isn’t just about removing middlemen.

It’s about designing systems that work at scale without sacrificing fairness, participation, or privacy.

AI might not be a perfect fix — but it could be a powerful tool in making decentralized governance actually live up to its promise.

Summary

Ethereum co-founder Vitalik Buterin believes artificial intelligence could help improve decentralized governance by addressing low voter participation and the limits of human attention.

He suggests personal AI assistants could analyze proposals and vote based on users’ inferred preferences, stepping in to ask for guidance on important issues.

He also proposes privacy-preserving AI models that can process sensitive information and output decisions without revealing private data.

While the approach could reduce centralization and governance attacks, it raises new concerns about data privacy and AI security as DAOs continue to evolve.