Sandy Kaul, head of digital assets and innovation at Franklin Templeton, said the rise of an AI agent economy is likely to increase demand for blockchain protocols designed to handle machine-to-machine micropayments. She argued that traditional card networks are a poor fit for agent-based payments because of their fee structure and settlement delays. Kaul cited Aptos, Solana and BNB Chain as examples of networks better suited to this model, noting that transactions on those chains can settle within seconds, compared with Visa’s settlement window of one to three business days. A joint report from Visa and investment research platform Artemis reached a similar conclusion, saying legacy card systems built for relatively low-frequency human commerce are not enough for AI agents, which need near-zero fees and much faster settlement. The report also referenced Coinbase’s x402 payment protocol, which has recorded $15 million in adjusted transaction volume and more than 109 million adjusted transactions since its launch in May 2025.
Franklin Templeton’s head of digital assets and innovation, Sandy Kaul, said the emerging AI agent economy is set to drive greater demand for blockchain protocols that can support machine-to-machine micropayments.
Kaul said traditional card networks are not well suited to agent-based payments because of fees and settlement times. She named Aptos, Solana and BNB Chain as blockchain networks that fit the agent economy better, adding that transactions on those networks can settle within seconds, faster than Visa’s one- to three-business-day settlement timeline.
Visa and investment research platform Artemis made a similar point in a joint report, saying traditional card systems built for low-frequency human commercial activity are not enough to support AI agents, which require near-zero fees and faster settlement.
The report also said Coinbase’s x402 payment protocol has reached $15 million in adjusted transaction volume and more than 109 million adjusted transactions since its launch in May 2025.
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