Andreessen Horowitz’s crypto team over the week outlined 11 areas where blockchain networks could intersect with artificial intelligence, laying out how crypto tools might shape identity, payments, and ownership as AI systems spread across the internet. The firm 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 Lays Out Use Cases as AI Power Concentrates 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 firm said blockchains can provide a neutral base layer for AI systems by supporting persistent user context, portable 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 such as World’s Proof of Human and newer systems like the Solana Attestation Service, which lets users link off-chain credentials to wallets while keeping 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. The firm noted that nearly half of internet traffic now comes from automated sources, while more website operators are blocking AI scrapers, a tension that has pushed 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 aggregating hardware from gaming PCs and data centers, these networks aim to reduce reliance on large cloud providers. Why Identity, Payments, and Ownership Keep Resurfacing Many of the ideas echoed concerns raised elsewhere in the crypto industry. For example, Ethereum co-founder Vitalik Buterin recently said that he plans to leave centralized social media behind in favor of decentralized platforms, arguing that shared data layers allow 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 stated goal of making Ethereum a settlement layer for AI agents and machine-to-machine transactions. Foundation developer Davide Crapis said at the time that AI systems need neutral infrastructure for value transfer and reputation, rather than relying on a few large technology firms. a16z’s map does not claim these systems are close to mass adoption. Several use cases, including AI companions owned by users or fully open agent-to-agent markets, are described as longer-term ideas. Still, the firm’s outline shows where investors and builders think crypto could fit as AI systems move from isolated tools into always-on intermediaries between people, data, and money. The post a16z Maps 11 Paths Where Crypto Meets AI appeared first on CryptoPotato .
