Forget Nvidia (NVDA): The next big AI trade could be crypto and blockchain

Forget Nvidia (NVDA): The next big AI trade could be crypto and blockchain

Markets

Forget Nvidia: The next big AI trade could be crypto and blockchain

Franklin Templeton’s Sandy Kaul and Circle CEO Jeremy Allaire argue that as autonomous AI agents start spending money on their own, blockchain networks will power the next big AI trade.

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Helene Braun

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Edited by

Cheyenne Ligon

Jul 22, 2026, 1:32 p.m.

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Investors looking for the next AI trade should consider blockchain networks and crypto assets as autonomous AI agents begin transacting with one another, according to Franklin Templeton's Sandy Kaul.

Kaul said agentic AI will require low-cost, programmable payment rails for machine-to-machine micropayments, making blockchains better suited than traditional financial networks.

Her thesis aligns with Circle CEO Jeremy Allaire's view that AI agents and blockchain are converging into a single economic system where software can transact, coordinate and exchange value autonomously.

Artificial intelligence has fueled one of the market's biggest investment themes. Franklin Templeton's head of digital assets and innovation, Sandy Kaul, says investors may already need to think beyond AI chipmakers and cloud companies for the next place to put their money.

In a recent

post

, Kaul argued that the next wave of AI could benefit blockchain networks and crypto assets as autonomous AI agents begin transacting with one another. While institutional investors have poured money into semiconductor companies, hyperscale cloud providers and data centers, she said they're overlooking the infrastructure that could power machine-to-machine commerce.

Her thesis centers on agentic AI. Unlike generative AI, which creates text, images or code in response to prompts, agentic AI is built to complete tasks with little human input. An AI agent could book travel, compare prices, buy computing power, retrieve data or manage software workflows on a user's behalf.

That shift is already beginning. Robinhood launched AI-powered investing tools in May that let agents trade stocks and make purchases for users. CEO Vlad Tenev has said AI agents will eventually rival the capabilities of human traders, while OpenAI and Anthropic are racing to build increasingly autonomous systems that can navigate software and complete complex tasks on their own.

For Kaul, those agents introduce a problem that today's payment systems weren't built to solve.

Many transactions between AI agents could be worth only fractions of a cent, such as paying for an API call, a second of computing power or access to a dataset. Traditional payment networks become expensive when fees cost more than the transaction itself.

That's where Kaul believes blockchains come in.

She argued public blockchain networks are better suited to 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 one another directly over blockchain rails.

If that happens at scale, demand for blockchain networks could grow alongside AI adoption.

Since agents would need native cryptocurrencies to pay network fees, Kaul argued rising transaction volumes could increase demand for those tokens while generating more revenue for developer incentives, network security and decentralized applications.

Her argument echoes a broader vision put forward by Circle CEO Jeremy Allaire, who has argued that the rise of agentic AI and blockchain represents a single technological shift rather than two separate ones.

In a recent

paper

, Allaire said AI is driving the cost of knowledge work toward zero while blockchain and programmable digital money are doing the same for payments, settlement and coordination. As businesses rely more heavily on specialized AI agents, he argued those agents will become economic actors that buy services, hire other agents and exchange value autonomously. Blockchain networks, digital identities and programmable money would provide the infrastructure needed to support those interactions at internet scale.

That vision extends beyond payments. Allaire argued AI-native companies could increasingly operate on-chain, with tokens representing ownership and governance, while software pricing shifts from monthly subscriptions to pay-per-task models as AI agents become both the buyers and sellers of digital services.

For investors, Kaul said the implication is straightforward. AI portfolios have largely focused on public technology companies building models and infrastructure. If autonomous AI agents become a meaningful part of the economy, she argues, blockchain networks and the cryptocurrencies that power them could emerge as another way to gain exposure to AI's next stage of growth.

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