Franklin Templeton: Agentic AI Is Blockchain's Killer Use Case, Driving Crypto Demand

Franklin Templeton Says Agentic AI Is Crypto's 'Killer Use Case'

Sandy Kaul contends that capturing the full economic value of the AI revolution requires investing in the underlying cryptocurrencies like Solana and Ethereum. Sandy Kaul, Head of Digital Assets and Innovation at Franklin Templeton, has a message for anyone who thinks buying Nvidia stock covers their AI exposure: It doesn't. Kaul published a paper Tuesday arguing that agentic AI -- software that acts, pays, and decides on your behalf without checking with you at every step -- will run on crypto rails, not Wall Street ones. Franklin Templeton manages nearly $1.8 trillion in assets. "Blockchain will be pivotal in allowing agentic AI to realize its potential for consumer transactions, and the growth of agentic AI is likely to become the 'killer' use case that drives blockchain adoption," the asset manager said in its post. The case turns on what AI agents actually do, Franking Templeton argues. AI agents go beyond what a simple chatbot can do -- agents can shop, book, and pay for things autonomously, once given permissions by the user. A report by the AI advisory firm Capgemini cited in the paper describes the shift as moving AI "from a reactive, conversational chatbot to an autonomous system that can perceive its environment, devise a plan, and execute multi-step tasks to achieve high-level goals without constant human supervision." That's what agentic AI does. Execute things autonomously instead of just spitting out information. Per a Bain & Company forecast, also cited by Kaul, "AI agents are expected to account for 15% to 25% of all U.S. e-commerce sales by 2030." Traditional payment networks -- built for human-scale, human-speed commerce -- can't handle the math required to power a world in which agentic AI becomes a social phenomenon. There would be too many transactions for banks to process on time. Blockchain networks, being distributed ledgers that record and settle transactions simultaneously without a bank in the middle, can. "While bitcoin only processes ~7 transactions per second and Ethereum ~75 transactions, newer high-speed chains are recording maximum speeds ranging from 12,933 transactions per second (TPS) on the Aptos chain, 6,284 TPS on Solana and 3,252 TPS on BNB Chain," the post reads. "These transaction speeds are on par with the Visa network that processes 1,700 to 10,000 transactions per second in normal operations." "Yet, even this comparison is misleading. Blockchains both record and settle their transactions in that TPS window whereas the Visa network only records a transaction. Settlement on the Visa network takes 1-3 business days." That speed gap matters when your software is making thousands of micropayments per hour. Coinbase already launched tools that let AI agents trade and pay autonomously. Google unveiled a payment protocol for agents in 2025, backed by the Ethereum Foundation. The x402 Foundation -- 40 organizations including Visa, Mastercard, and AWS building open payment rails for AI -- launched formally on July 14. The protocol revives a forgotten HTTP status code from 1991, originally reserved for web payments that never materialized, and puts it to work letting software pay software directly over the internet. If each agent buys data, compute, and API access using a blockchain's native token (the cryptocurrency that powers transactions on that specific network), demand for coins like Solana and Ethereum could follow volume. Kaul's conclusion is direct: "I believe what will become increasingly clear in coming years is that in order to capture the value of decentralized networks and businesses, investors will need to buy the cryptocurrencies and alt coins being issued by those entities." Agentic commerce -- AI systems transacting autonomously on behalf of humans, from buying cloud compute to booking flights -- is projected at $3 trillion to $5 trillion by 2030, according to a report by McKinsey & Company.

Agentic AI is Next 'Killer' Use Case for Blockchain: Franklin Templeton

Franklin Templeton's digital assets lead said that the autonomous AI agent economy will increase demand for blockchain protocols hosting machine-to-machine micropayments. Artificial intelligence (AI) agents are the next "killer" use case for blockchain and cryptocurrency, according to investment management giant Franklin Templeton's head of digital assets and innovation. Sandy Kaul said in a X post on Wednesday that the AI agent economy will grow demand for blockchain protocols hosting machine-to-machine micropayments, as legacy card networks are unsuitable for agentic payments due to high fees and settlement times. "To capture the AI growth opportunity today, most investors buy shares of AI-aligned companies and related verticals. But will the same playbook work for agentic AI," Kaul said in the introduction to his more-than-1,800 word post. He said blockchain networks such as Aptos, Solana and the BNB Chain are more suited for the agentic economy, as they settle transactions in seconds, which is faster than the one-to-three business-day settlement time of the Visa network. In a joint report published last Wednesday, payments giant Visa and investment thesis platform Artemis argued that traditional cards built for low-frequency human commerce are insufficient for AI agents, which need infrastructure with near-zero fees and faster settlement to make agentic micropayments commercially viable. Visa's crypto division and Stripe-backed Tempo both launched AI tools in March. Visa's allows AI agents to make same-day payments. Some machine payment protocols are boasting signs of adoption. The x402 payment protocol developed by Coinbase processed $15 million in adjusted volume across over 109 million adjusted transactions since it was launched in May 2025, according to Visa and Artemis' joint report.

Agentic AI Could Become Crypto's Killer App and Send Altcoin Demand Soaring

Agentic artificial intelligence could become the breakthrough application that takes blockchain payments mainstream and creates a new source of demand for cryptocurrencies, according to Franklin Templeton. Sandy Kaul, the asset manager's head of Digital Assets and Innovation, argued that investors buying shares in chipmakers, data centers, and other AI-aligned companies may be overlooking how autonomous agents will conduct transactions. Unlike generative AI tools that respond to human prompts, agentic systems can independently develop plans, interact with software, and execute multi-step tasks. That development could produce trillions of dollars in machine-led commerce, and require payment infrastructure capable of processing tiny transactions without constant human approval. Kaul believes blockchains are better suited to that role than legacy financial rails, potentially transforming crypto networks into the settlement layer for an economy where "software can pay software." Agentic Commerce Could Reach $5 Trillion Institutional investors have already concentrated heavily on conventional AI exposure. The 10 largest S&P 500 companies, all aligned with the AI theme, now represent almost 40% of the index's total market capitalization, according to Franklin Templeton. However, agentic AI could shift value away from the companies building models and infrastructure toward the networks used by autonomous systems. Estimates cited by Kaul place agentic commerce between $3 trillion and $5 trillion by 2030. By 2028, 33% of enterprise software could include agentic AI, while autonomous systems may handle as many as 15% of everyday business decisions. Such agents could purchase computing power, make API calls, license data, and pay for digital services in real time. Each transaction may cost only a fraction of a cent, creating a machine-to-machine economy based on continuous micropayments. Protocols are already emerging to support these transactions. Coinbase created x402, reviving the internet's long-dormant "402 Payment Required" status code to let software request and complete payments automatically. Coinbase later transferred the protocol's intellectual property to the Linux Foundation. Credit card networks and technology companies, including Stripe, Shopify, Google, and Amazon Web Services, have reportedly supported the broader standard. AI agents could also reshape retail spending. Franklin Templeton cited projections suggesting they may influence between 15% and 25% of US e-commerce sales by 2030. Why AI Agents May Need Blockchains Traditional payment systems are poorly designed for transactions worth fractions of a cent. Credit card payments typically carry fees of 2%-3% plus a fixed charge of around $0.30, making them impractical when an AI agent pays $0.001 for a second of computing power or a single data query. Blockchains can process payments without the same minimum fee structure while supporting programmable transaction rules. An agent could generate a single-use payment token specifying which merchant can accept it, the amount that can be spent, and when the authorization expires. A blockchain could verify those conditions and invalidate the token after the purchase. Cryptographic identities could also help distinguish legitimate agents from unauthorized software. Each agent could receive credentials allowing it to sign transactions, while the network records an auditable history of its payments and decisions. That transparency could prove particularly important when autonomous systems operate without real-time human supervision. Companies would need to understand what an agent purchased, which rules it followed, and who authorized its activity. Newer blockchains may also provide the throughput required for machine commerce. Kaul cited maximum transaction rates of 12,933 per second for Aptos, 6,284 for Solana, and 3,252 for BNB Chain. Unlike card networks, which initially authorize payments before completing settlement later, blockchains can record and settle transfers in a single process. However, real-world performance, fees, and network reliability may differ substantially from advertised maximum throughput. AI Payments Could Fuel Altcoin Demand If AI agents use public blockchains, they will need to pay transaction fees in native tokens. An agent operating on Solana, for example, needs SOL to submit transactions. Franklin Templeton expects this mechanism to create demand for the cryptocurrencies underlying the networks that capture agentic activity. Higher transaction volumes could also produce more revenue for blockchain ecosystems. Foundations and decentralized organizations could use those funds to finance development grants, security audits, validator incentives and new applications. Kaul described a potential flywheel: more AI activity increases token demand and network revenue, which attracts developers and produces additional applications, users and transactions. Autonomous agents could simultaneously remove one of Web3's largest barriers by managing wallets, token conversions, and payments in the background. Consumers could use decentralized applications without having to buy crypto or understand blockchain infrastructure. Still, greater network usage does not guarantee that every associated altcoin will appreciate. Token supply, fee-burning mechanisms, value distribution, and competition between blockchains will determine whether activity benefits holders. Franklin Templeton nevertheless believes investors may eventually need crypto exposure to capture the value created by decentralized AI commerce. The next stage of the AI investment cycle, Kaul argued, may not belong only to semiconductor companies and cloud providers. It could also reward the blockchain networks that allow autonomous agents to transact.