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

Franklin Templeton Identifies Agentic AI as Blockchain's Breakthrough Application

Sandy Kaul, Head of Digital Assets and Innovation at Franklin Templeton, has declared that agentic AI represents the killer use case for blockchain that could fundamentally reshape how investors approach the AI revolution 1

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. In a detailed paper published this week, Kaul argued that capturing the full economic value of autonomous AI agents requires investing in the underlying cryptocurrencies that power their transactions, not just shares in AI-aligned companies 1

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. The nearly $1.8 trillion asset manager stated that 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 breakthrough that drives blockchain adoption at scale 1

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Understanding Agentic AI and the Machine-to-Machine Economy

Unlike generative AI tools that simply respond to prompts, agentic AI operates as autonomous systems capable of perceiving their environment, devising plans, and executing multi-step tasks without constant human supervision 1

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. These autonomous AI agents can shop, book, and pay for things independently once given permissions by users, fundamentally transforming how software interacts with commerce 1

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. According to Bain & Company forecasts cited by Kaul, AI agents are expected to account for 15% to 25% of all U.S. e-commerce sales by 2030 1

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. McKinsey & Company projects that agentic commerce—AI systems transacting autonomously on behalf of humans, from buying cloud compute to booking flights—could reach $3 trillion to $5 trillion by 2030 1

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. By 2028, 33% of enterprise software could include agentic AI, while autonomous systems may handle as many as 15% of everyday business decisions 3

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Why Traditional Payment Systems Cannot Support AI-Driven Transactions

Traditional payment systems are fundamentally unsuitable for the machine-to-machine economy that autonomous AI agents will create 2

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. 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 3

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. Legacy card networks built for low-frequency human commerce cannot handle the infrastructure requirements for real-time micropayments that AI-driven commerce demands 2

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. In a joint report published last week, payments giant Visa and investment thesis platform Artemis argued that traditional cards are insufficient for AI agents, which need infrastructure with near-zero fees and faster settlement to make agentic micropayments commercially viable 2

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. The Visa network takes one-to-three business days for settlement, while AI agents executing thousands of transactions per hour require immediate finality 2

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Blockchain Networks Offer Speed and Settlement Advantages

Blockchain networks, as distributed ledgers that record and settle AI-driven transactions simultaneously without a bank intermediary, can handle the volume and speed requirements that agentic AI demands 1

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. While Bitcoin only processes approximately 7 transactions per second and Ethereum around 75 transactions, newer high-speed chains are recording maximum speeds ranging from 12,933 transactions per second on the Aptos chain, 6,284 TPS on Solana, and 3,252 TPS on BNB Chain 1

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. These transaction speeds match the Visa network that processes 1,700 to 10,000 transactions per second in normal operations 1

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. However, the comparison is misleading because blockchains both record and settle their transactions in that TPS window whereas the Visa network only records a transaction initially 1

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. Decentralized networks can process payments without the same minimum fee structure while supporting programmable transaction rules that let agents generate single-use payment tokens specifying merchant authorization, spending limits, and expiration times 3

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Emerging Protocols Connect AI Agents to Blockchain Rails

Coinbase already launched tools that let AI agents trade and pay autonomously, creating the x402 payment protocol that revives a forgotten HTTP status code from 1991 originally reserved for web payments that never materialized 1

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. The protocol lets software pay software directly over the internet, and Coinbase later transferred the intellectual property to the Linux Foundation 3

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. Google unveiled a payment protocol for agents in 2025, backed by the Ethereum Foundation 1

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. The x402 payment protocol processed $15 million in adjusted volume across over 109 million adjusted transactions since it launched in May 2025, according to Visa and Artemis' joint report 2

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. Credit card networks and technology companies, including Stripe, Shopify, Google, and Amazon Web Services, have reportedly supported the broader standard 3

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. Visa's crypto division and Stripe-backed Tempo both launched AI tools in March, with Visa's allowing AI agents to make same-day payments 2

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How Agentic AI Could Drive Cryptocurrency Demand

If autonomous AI agents use public blockchains, they will need to pay transaction fees in native tokens, creating direct demand for digital assets 3

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. An agent operating on Solana needs SOL to submit transactions, while Ethereum-based agents require ETH 3

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. 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" 1

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. Higher transaction volumes could produce more revenue for blockchain ecosystems, with foundations and decentralized organizations using those funds to finance development grants, security audits, validator incentives, and new applications 3

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. Kaul described a potential flywheel effect: more AI activity increases token demand and network revenue, which attracts developers and produces additional applications, users, and transactions 3

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