Ethereum co-founder Vitalik Buterin said the deepest divide among AI supporters is not about legislation or politics, but about a basic philosophical question: is superintelligence arriving soon, or is AI simply another step in the normal progression of software? That difference, he argued, reaches beyond AI policy and into capital allocation and system design across adjacent sectors, including blockchain.
According to Buterin, one camp expects superintelligent systems to emerge in the near term and sees major global risks that would require an unprecedented level of international coordination. The other camp treats AI as a tool whose capabilities are improving through a more familiar development cycle, with controls and safeguards added gradually. The gap between these views is wide. In his framing, they rest on incompatible assumptions about what AI actually becomes next.
Fast superintelligence would push blockchains toward proof and coordination layers
If AI advances rapidly toward superintelligence, Buterin said blockchain architecture would need to emphasize different building blocks. He highlighted the need for censorship-resistant hardware, on-chain proofs of model training, and decentralized agent networks. The purpose is clear: create infrastructure that can verify how AI systems are trained and how they coordinate, without relying entirely on centralized intermediaries.
He pointed to Ethereum and Bittensor as examples being considered for these roles. Ethereum could function as a foundational coordination and verification layer, while Bittensor represents an open-source blockchain project focused on decentralized machine learning and incentives for global contributors to supply models to a distributed network. Under the superintelligence scenario, systems like these would not be peripheral. They could become core infrastructure for trusted AI coordination.
Gradual AI progress would favor wallets, markets, and efficiency tools
The alternative path leads somewhere else. If AI develops at a steady and predictable pace, integration between crypto and AI would likely center on efficiency-oriented tools, decentralized wallets, and marketplaces for data and computation inside crypto ecosystems. That is a less dramatic architecture. It is also a very different one.
In that case, the focus would shift toward improving how data, compute, and settlement are handled in existing crypto networks, rather than building a heavy verification stack designed for an imminent jump to superintelligence. Both paths involve blockchains, but they ask for different priorities. One is built around resilience and verifiability; the other is geared toward practical throughput and resource exchange.
Buterin argues the industry should prepare for both outcomes
Buterin did not present a single preferred outcome. Instead, he urged the industry to be ready for both possibilities: a sharp leap to superintelligence or a more incremental rise in AI capability. The source article noted that 2026 is expected to bring faster adoption of blockchain-based app-chains and broader use of AI across financial processes, placing the debate in a more immediate context.
He also identified several milestones that could shape the next phase of crypto-AI integration: standards for verifying AI-driven claims on blockchains, fairer sharing of decentralized computational resources, and clearer regulatory guidance for autonomous agents. The end state for AI remains contested. The question of how blockchains can support and verify that evolution is already on the table.