That change is already beginning. Robinhood launched AI-powered investing tools in May that allow agents to trade stocks and make purchases for users. CEO Vlad Tenev has said AI agents will eventually rival the capabilities of human traders, while OpenAI and Anthropic are racing to build increasingly autonomous systems that can navigate software and complete complex tasks on their own.
For Kaul, these agents introduce a problem that current payment systems were not created to address.
Many transactions between AI agents could be worth only fractions of a cent, such as paying for an API call, a second of computing power, or access to a data set. Traditional payment networks become expensive when fees cost more than the transaction itself.
That’s where Kaul believes blockchains come in.
He argued that public blockchain networks are better suited for machine-to-machine payments because they offer programmable transactions, cryptographic identity, and near-instant settlement. Instead of relying on banks or card networks, AI agents could hold digital assets and pay each other directly through blockchain rails.
If that happens at scale, demand for blockchain networks could grow alongside AI adoption.
Since brokers would need native cryptocurrencies to pay network fees, Kaul argued that rising transaction volumes could increase demand for those tokens while generating more revenue for developer incentives, network security, and decentralized applications.
