a16z maps 11 paths where Crypto meets AI

The company argued that crypto can counter the centralization of AI by giving users control over identity, data ownership and payments.

Andreessen Horowitz’s crypto team this week outlined 11 areas where blockchain networks could intersect with artificial intelligence, explaining how crypto tools could impact identity, payments and ownership as AI systems spread across the internet.

The company framed crypto less as a speculative asset class and more as infrastructure that could counter growing centralization in AI by giving users control over data, identity and economic participation.

a16z presents use cases while concentrating AI power

In a January 20 post on X, a16z crypto argued that the web is moving toward interfaces dominated by AI prompts, raising questions about who controls data, distribution, and revenue as traditional websites lose traffic.

The company said blockchains can provide a neutral foundation layer for AI systems by supporting persistent user context, wearable identities for AI agents, and on-chain payments that work without platform gatekeepers.

Several of the ideas focused on identity and trust, with one example being decentralized proof of personhood, which aims to help platforms distinguish humans from bots without relying on centralized ID providers.

The post pointed to existing projects like World’s Proof of Human and newer systems like the Solana Attestation Service, which allow users to link off-chain credentials to wallets while keeping the data private.

Payments were another recurring theme. a16z described how blockchains could support micropayments between AI agents, content creators, and end users. That includes revenue sharing when AI tools rely on third-party content, as well as systems where web crawlers pay sites directly for access to data.

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The company noted that nearly half of internet traffic now comes from automated sources, while more website operators are blocking AI scrapers, a tension that has driven companies like Cloudflare to sell blocking tools.

The post also highlighted decentralized physical infrastructure networks, or DePIN, as a way to pool unused compute and energy resources for AI training and inference. By merging hardware from gaming PCs and data centers, these networks aim to reduce dependence on major cloud providers.

Why identity, payments and ownership keep popping up

Many of the ideas reflected concerns expressed elsewhere in the crypto industry. For example, Ethereum co-founder Vitalik Buterin recently said he plans to leave centralized social media behind in favor of decentralized platforms, arguing that shared data layers enable competition without locking users into a single interface. His comments reflected a broader push to separate identity and content from platform control.

The Ethereum Foundation has also moved in this direction. Last year it launched a new AI team focused on agentic payments and coordination, with the aim of turning Ethereum into a settlement layer for AI agents and machine-to-machine transactions. Foundation developer Davide Crapis said at the time that AI systems need a neutral infrastructure for value transfer and reputation, rather than relying on a few big tech companies.

The a16z map does not claim that these systems are close to mass adoption. Several use cases, including user-owned AI companions or fully open agent-to-agent markets, are described as longer-term ideas. Still, the company’s sketches show where investors and builders think crypto could fit as AI systems evolve from isolated tools to always-on intermediaries between people, data and money.