AI systems are breaking an internet that was designed at human-scale — by making it cheaper than ever to coordinate, transact, and generate voice, video, and text that are increasingly indistinguishable from human activity. We’re already beset with CAPTCHAs; now we’re starting to see agents interact and transact just like humans do (and as we’ve covered here).
The problem isn’t that AI exists — it’s that the internet does not have a native way to separate humans from machines while preserving privacy and usability.
This is where blockchains come in. The idea that crypto can help build better AI systems, and vice versa, can be nuanced; so here, we sum up a few reasons why AI needs blockchains now more than ever.
1. Raising the cost of AI impersonation
AI can fake voices, faces, writing styles, video, and entire social personas, and it can do this at scale: One actor can appear as thousands of accounts, opinions, customers, or voters – at increasingly lower cost.
These impersonation techniques aren’t new: Any enterprising fraudster has always been able to hire a voice actor, fake a phone call, or send a phishing text. What’s new is the price: It’s become increasingly affordable to carry out these attacks at a massive scale.
Meanwhile, most online services assume that one account corresponds to one person. When that assumption fails, everything downstream breaks. Detection-based approaches (like CAPTCHAs), inevitably lose, because AI improves faster than the tests designed to catch it.
So where do blockchains come in? Decentralized proof-of-human or proof-of-personhood systems make it easy to be one participant but persistently hard to be many. While it may be relatively easy and affordable to scan your iris and get a World ID for instance, it’s almost impossible to get a second one.
This makes it harder for AI to achieve impersonation at scale by limiting the supply of IDs and by increasing marginal costs for attackers.
AI can fake content, but crypto makes it a lot harder to cheaply fake human uniqueness. By restoring scarcity at the identity layer, blockchains raise the marginal cost of impersonation without raising friction for normal human behavior.
2. Creating systems for decentralized proof of personhood
One way to prove you’re human is through digital IDs, which encompass all of the things a person can use to verify their identity — usernames, PINs, passwords, and third-party attestations (e.g., citizenship or creditworthiness) and other credentials.
What does crypto add? Decentralization. Any identity system that sits at the center of the internet becomes a point of failure. As agents act on behalf of humans — transacting, communicating, and coordinating — whoever controls identity effectively controls participation. Issuers can revoke access, impose fees, or abet surveillance.
Decentralization flips this dynamic: Users, not platform gatekeepers, control their own identities, making them more secure and censorship-resistant.
Unlike traditional identity systems, decentralized proof of human mechanisms allow users to control and custody their own identities, and verify their humanity in a privacy-preserving and credibly neutral way.
3. Creating portable, universal “passports” for agents
AI agents don’t live in one place. A single agent can show up across chat apps, email threads, phone calls, browser sessions, and APIs. Yet there is no reliable way to know that interactions across these contexts refer to the same agent, with the same state, capabilities, and authorization provisioned by its “owners.”
Moreover, tying an agent’s identity to only one platform or marketplace makes it unusable within other products, and everywhere else that matters. This makes the experiences around agents fragmented and onerous to load in context
A blockchain-based identity layer allows agents to have portable, universal “passports.” These identities can carry references to capabilities, permissions, and payment endpoints, and can be resolved from anywhere, making agents much more difficult to spoof. This would also allow builders to create more useful agents and better user experiences: Agents could exist in multiple ecosystems without fear of being locked in to any particular platform.
4. Enabling payments at machine-scale
As AI agents increasingly transact on behalf of humans, existing payment systems become a bottleneck. Agentic payments at scale require new infrastructure — micropayment systems capable of handling tiny transactions across many sources.
Many existing blockchain-based tools — rollups and L2s, AI-native financial institutions, and financial infrastructure protocols — show potential to solve this problem, enabling near-zero-cost transactions and more finely-grained payment splits.
Crucially, these rails support machine-scale transactions — micropayments, frequent interactions, and agent-to-agent commerce — that traditional financial systems cannot handle.
- Nanopayments can be split across multiple data providers, allowing a single user interaction to trigger tiny payments to all contributing sources through automated smart contracts.
- Smart contracts allow for enforceable retroactive payments triggered by completed transactions, compensating information sources that contributed to a purchase decision after the transaction occurs with full transparency and traceability.
- Blockchains enable distribution of complex and programmable payment splits, ensuring that revenue is fairly allocated through code-enforced rules rather than centralized decisions, creating trustless financial relationships between autonomous agents.
5. Enforcing privacy across AI systems
There’s a paradox at the heart of many security systems: The more data they collect to protect users — from social graphs to biometric data — the easier it becomes for AI to impersonate them.
This is where privacy and security become the same problem. The challenge is making proof of personhood systems private by default and obscuring information at every turn to ensure that only humans can produce the information necessary to prove they are human.
Blockchain-based systems paired with zero-knowledge proofs allow users to prove specific facts — PINs, ID numbers, eligibility criteria (e.g., drinking age at a bar) — without revealing underlying data (e.g., your address on a driver’s license).
Applications get the assurance they need, AI systems are denied the raw material required for imitation. Privacy is no longer a feature layered on top; it is the core defense.
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AI makes scale cheap but difficult to trust. Blockchains restore trust, raising the cost of impersonation, preserving human-scale interaction, decentralizing identity, enforcing privacy by default, and giving agents native economic constraints.
If we want an internet where AI agents can operate without destroying trust, blockchains are not optional infrastructure: They are the missing layer that makes an AI-native internet work.
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