Web3 technologies and artificial intelligence (AI) are creating new ways to distribute revenue, own data, and pay for digital services, from micropayments to paid data collection and personalized ads.
The rapid development of generative AI is already changing the financial foundations of online services. Users increasingly access information directly through AI interfaces, bypassing websites, media outlets, and platforms. This leads to declining traffic, a rise in paywalls, and growing copyright disputes. In response to these challenges, blockchain technologies are being considered as a tool to redesign monetization models and redistribute value in the digital environment.
Analysts at a16z identify 11 key scenarios at the intersection of Web3 technologies and AI solutions. These scenarios build on existing developments and could form the basis of a more sustainable and transparent digital economy:
- Persistent context in AI interactions. User preferences, experience, and professional context can be stored as on-chain assets and used across different AI platforms, increasing the value of personalized services.
- Universal identity for AI agents. Decentralized identity systems allow AI agents to accept payments, verify reputation, and operate across ecosystems without being tied to a single platform.
- Proof of Personhood. On-chain IDs make it possible to distinguish humans from bots without revealing personal data, enabling fair access to services and content.
- Decentralized Physical Infrastructure (DePIN) for AI projects. Unused computing resources are pooled into open markets, reducing the cost of training and deploying AI models and lowering dependence on major cloud providers.
- Payment and regulatory infrastructure for AI agent interaction. Blockchain technologies enable AI agents to automatically order services from one another and settle payments without human involvement.
- Synchronization of AI apps. On-chain protocols ensure compatibility and updatability of applications created via AI platforms (vibe-coded), reducing maintenance and integration costs.
- Micropayments and revenue sharing. Smart contracts automatically distribute revenue among all data sources involved in AI decision-making, including payouts of less than $0.05.
- Intellectual property and content provenance registries. Registering copyrights in distributed ledgers simplifies data licensing for AI products and enables new monetization models for derivative content.
- Paid data collection by AI crawlers. Instead of blocking bots, websites can charge for data access, while real users retain free access.
- Privacy-preserving personalized ads. AI agents select ads based on user preferences, while Web3 solutions ensure payments to users for engagement without exposing personal data.
- User-controlled AI companions. Decentralized technologies make it possible to secure ownership and control of personal AI assistants to individuals rather than platforms.
According to a16z, around 50% of all internet traffic already comes from chatbots, and the share of top 10,000 websites blocking AI crawlers has grown from 9% to 37% in just one year. These figures show that traditional monetization models are no longer working.
Analysts believe that combining AI with blockchain offers an alternative — an economy in which value is distributed automatically, transparently, and directly among all participants, from content creators and developers to end users.
