Ethereum Foundation Positions Blockchain as Trust Layer for the Age of AI

The Ethereum Foundation has outlined plans to position Ethereum as a decentralised infrastructure layer supporting artificial intelligence (AI) systems, focusing on coordination, verification and trust rather than building AI models itself. The strategy centres on enabling autonomous software agents to identify themselves, exchange payments and verify interactions using blockchain technology.

According to the foundation’s AI lead Davide Crapis, Ethereum was never designed to run large-scale AI computations, meaning the heavy processing required by neural networks will remain on traditional servers outside the blockchain. Instead, Ethereum can act as a neutral environment where AI agents interact using transparent records and cryptographic verification.

Crapis said the approach is intended to address concerns that artificial intelligence could accelerate the re-centralisation of digital infrastructure if powerful systems remain under the control of a small number of companies. The Ethereum Foundation argues that maintaining decentralisation, privacy and censorship resistance will become increasingly important as AI systems take on more tasks across the internet.

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Standards and Infrastructure

Within this framework, Ethereum could provide a public registry that allows agents to discover one another, maintain verifiable reputations and route payments without relying on centralised platforms. The system has been compared to a decentralised review network combined with built-in payment capabilities.

To help formalise the ecosystem, developers are working on ERC-8004, a protocol designed to establish identity and trust standards for AI agents, which Crapis said has already begun attracting attention outside the Ethereum community.

The foundation is also exploring ways to extend blockchain principles such as privacy and security into the AI environment. This includes encouraging local processing of user data and relying on cryptographic keys as a mathematically verifiable form of authentication in response to the potential rise of AI-driven impersonation and automated cyberattacks.
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