That shift is already beginning. Robinhood launched AI-powered investment tools in May that let agents trade stocks and make purchases for users. CEO Vlad Tenev has said that AI agents will eventually rival the abilities of human traders, as OpenAI and Anthropic race to build increasingly autonomous systems that can navigate software and complete complex tasks on their own.
For Kaul, these agents introduce a problem that today’s payment systems are not built to solve.
Many transactions between AI agents can be worth only fractions of a cent, such as payment 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.
This is where Kaul believes blockchains come in.
She 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 over blockchain rails.
If it happens at scale, the demand for blockchain networks could grow along with AI adoption.
Since agents would need native cryptocurrencies to pay network fees, Kaul argued that increasing transaction volumes could increase demand for these tokens while generating more revenue for developer incentives, network security and decentralized applications.
