Franklin Templeton says AI agents will drive a micropayment economy on blockchains. The firm invested in Cambrian and sees networks like Aptos and Solana as key infrastructure.
Alpha Score of 31 reflects weak overall profile with moderate momentum, poor value, weak quality. Based on 3 of 4 signals – score is capped at 90 until remaining data ingests.
Franklin Templeton sees autonomous AI programs – what it calls agentic AI – reshaping the way payments work on blockchain networks. The asset manager expects these systems to push micropayments into the mainstream, creating an economy where machines transact with machines.
Sandy Kaul, head of digital assets at Franklin Templeton, said the shift is already visible. “The blockchain infrastructure is being designed for machine-driven micropayments,” she said. The logic is straightforward. Credit card fees of 2-3% can eat up a micropayment entirely. Blockchains, with their low transaction costs, fit the use case better.
Circle CEO Jeremy Allaire echoed the view. He said improved blockchain environments could fuel an “agentic economy” where AI autonomously pays for API calls, data streams, and global transfers. The result, he argued, is a move from speculation to utility.
Franklin Templeton is not just talking. The firm participated in a $6 million seed round for Cambrian, a startup building blockchain data infrastructure. The investment aligns with a broader push into digital assets, Kaul said.
Robinhood’s recent deployment of AI trading tools, she added, shows the trend is spreading beyond crypto-native firms.
Blockchain networks differ in their ability to handle the volume. Aptos processes roughly 12,933 transactions per second, according to public data. Solana runs at about 6,284 TPS. BNB Chain does around 3,252 TPS. Visa settles in 1-3 days. The gap is wide.
Projections from Franklin Templeton peg the potential agentic economy at $3 trillion to $5 trillion by 2030. That would make high-speed blockchains essential infrastructure, driving demand for their native tokens as fee currencies.
For investors, the message is concrete: monitor the chains that can handle the load and the AI platforms that connect to them. The thesis is not hypothetical – the money is already moving.
Drafted by a large language model from the source reporting linked above, then screened by automated publishing checks. It is not read by a journalist before publication. Some articles cite our Alpha Score. Verify prices and figures against the original source. Educational coverage, not personalized advice.