The Ethereum Foundation targets the role of trust in the AI ​​ecosystem

TLDR

The Ethereum Foundation plans to position Ethereum as a trust layer for AI systems. The organization focuses on coordination and validation rather than building AI models. David Crappis Ethereum can serve as a public authentication layer for autonomous agents. The Foundation supports ERC-8004 to standardize agent identity and trust. The strategy promotes privacy, local AI processing and stronger cryptographic data security.

The Ethereum Foundation has outlined a strategy to position Ethereum as a layer of trust for AI systems. The firm says it doesn't compete by building large AI models. Instead, it plans to verify identity, payments and autonomous agents.

The Ethereum Foundation outlines a coordination role for AI agents.

The Ethereum Foundation has said that raw AI focuses on coordination, not computation. David Krapis, head of AI at EF, presented the plan at NEARCON 2026. Ethereum can serve as a “public, non-administrative authentication layer for AI,” he said.

He explained that AI systems now handle business transactions, applications and software operations. However, centralized control can undermine decentralization and privacy. “If AI doesn't have the properties we care about and we use AI for everything, basically nobody has those properties anymore,” Crappis said.

He explained that Ethereum can help agents identify themselves and build trust. The network can route payments and handle cryptographic authentication. Heavy computation on traditional servers remains off-chain.

EF supports standards such as ERC-8004 for agent identity and trust. Developers outside of Ethereum have expressed interest in these standards. A decentralized evaluation network compared the system to toll rails.

He said that Ethereum can maintain clear stories for representatives. Those records help assess reputation and past performance. As a result, agents can conduct transactions without relying on central platforms.

Ethereum extends the core principles to AI security and privacy

The Ethereum Foundation aims to bring privacy and censorship resistance to AI systems. Crappis calls this effort “Props AI” within the organization. The program promotes privacy, openness and security in AI design.

He warned that centralized AI services could build detailed user profiles over time. Queries and usage patterns may reveal personal data. Therefore, EF supports more local AI processing on user devices.

“We want to create a world where consumers have as much data and power as possible,” Krapis said. “We don't just give it to operators,” he added. The approach seeks to limit unnecessary data transfer to large platforms.

Security forms another part of the movement. Crappis predicted that AI systems would automate cyberattacks and impersonation. “Maybe we'll see AI-engineered hacks,” he said.

It has been argued that traditional authentication models may fall under AI-based simulation. In response, he emphasized the importance of cryptographic keys. Controlling the private key provides mathematical proof of ownership.

“In a world where AI is out in the wild, we want Ethereum to be a place with a big lock,” Krapis said. “If I have the keys, I still have power,” he added. EF described its AI program as one of several ongoing priorities.