Vitalik Buterin Proposes Human-Verified AI Wallets for Crypto Transactions

Buterin proposed AI-assisted wallets where algorithms suggest transaction plans but users must manually confirm large transfers.

Vitalik Buterin has outlined his perspective on how artificial intelligence (AI) could redefine the next generation of Web3 wallets.

He also proposed a model where humans remain directly involved in approving high-value transactions.

AI Will Shape Newer Crypto Wallets

The Ethereum co-founder shared his views on the decentralized social media platform Farcaster, noting that it is “pretty obvious” that the next iteration of wallets will heavily involve AI.

Despite this, Buterin added that he would not trust LLMs with multi-million-dollar transactions or control over large amounts of money. Instead, he gave an approach in which AI systems assist users while leaving the final decision in human hands.

He described an optimal workflow in high-value situations that would involve an AI system proposing a plan, after which a local light client simulates the transaction. The person would then review the intended action and the required outcome before manually confirming it.

However, Buterin warned that this approach must be implemented conservatively with a strong emphasis on security. He suggested that one way to achieve this is by removing decentralized application interfaces from the transaction process. By eliminating dApp user interfaces from the flow entirely, the system could reduce several attack vectors associated with theft and privacy risks.

The 32-year-old has previously discussed how cryptocurrency and AI could evolve together. He envisions blockchains and the technology working hand-in-hand, with crypto providing the trust, privacy, and economic infrastructure that it needs to operate safely and fairly.

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Proposed AI-Assisted Wallet Workflows

Other developers and community members responded to Buterin’s comments by describing potential implementations of the idea.

Ethereum developer Andrey Petrov suggested two additional scenarios. In the first, a user initiates a transaction as usual while AI analyzes the payload about to be signed. The technology would then attempt to guess their intended action and explain it in plain language, allowing them to confirm whether the transaction accurately reflects what they meant to do.

In the second case, the user either states their intended action directly or relies on the explanation generated in the first step. The AI then tries to reconstruct the transaction independently, without referencing the original amount, to determine whether it arrives at the same outcome. He explained that any differences between the two would show areas that require further review before the process is finalized.

Another Farcaster user, identified as fkaany, described a framework in which AI plans complex crypto strategies such as multi-hop swaps, yield optimization, and gas minimization.

This would involve a local light client simulating the outcome, which would allow individuals to review a clear summary and manually confirm the transaction, helping reduce risks from blind signing, phishing interfaces, and malicious dApp payloads.