Sandy Kaul of Franklin Templeton and Circle’s Jeremy Allaire suggest that with autonomous AI agents beginning to handle financial transactions independently, blockchain technology will lead the next significant AI investment opportunity.
By Helene Braun|Edited by Cheyenne Ligon Jul 22, 2026, 1:32 p.m. 3 min readMake preferred on ShareShare this articleCopy linkX (Twitter)LinkedInFacebookEmailMake preferred on (Getty Images)SummaryShow- According to Sandy Kaul from Franklin Templeton, investors should explore blockchain networks and cryptocurrencies as autonomous AI agents begin to interact financially.
- Kaul stated that agentic AI will necessitate affordable, programmable payment systems for machine-to-machine transactions, making blockchain technology more appropriate than conventional financial infrastructures.
- This perspective is shared by Jeremy Allaire of Circle, who believes that AI agents and blockchain are merging into a unified economic framework where software can autonomously transact and exchange value.
The surge in artificial intelligence has emerged as a leading investment trend in the market. Sandy Kaul, who oversees digital assets and innovation at Franklin Templeton, suggests that investors might need to look beyond traditional AI chip manufacturers and cloud service providers to find the next investment opportunity.
In a recent post, Kaul posited that the forthcoming phase of AI could significantly benefit from blockchain and cryptocurrency as autonomous AI agents commence financial transactions among themselves. While many institutional investors have directed capital toward semiconductor firms, large-scale cloud providers, and data centers, she argues they are neglecting the essential infrastructure that could enable machine-to-machine commerce.
Her theory revolves around the concept of agentic AI. Unlike generative AI, which produces text, images, or code based on prompts, agentic AI is designed to perform tasks with minimal human oversight. An AI agent could autonomously book travel, compare prices, acquire computing resources, retrieve information, or manage software workflows for users.
This transformation is already underway. In May, Robinhood introduced AI-driven investment tools that allow agents to trade stocks and make purchases on behalf of users. CEO Vlad Tenev has indicated that AI agents will eventually match human traders' capabilities, while companies like OpenAI and Anthropic are in a race to develop more autonomous systems that can navigate software and perform complex tasks independently.
Kaul believes these AI agents present a challenge that existing payment systems are not equipped to handle.
Many transactions between AI agents may involve very small amounts, often just fractions of a cent, such as payments for API calls, brief computing sessions, or access to datasets. Traditional payment systems can become costly when transaction fees exceed the value of the transaction itself.
This is where Kaul sees the advantages of blockchain technology.
She advocates that public blockchain networks are better suited for machine-to-machine payments due to their ability to facilitate programmable transactions, provide cryptographic identity, and enable near-instant settlements. Rather than depending on banks or card networks, AI agents could possess digital assets and transact directly via blockchain infrastructures.
If this scenario unfolds on a large scale, the demand for blockchain networks could rise alongside the adoption of AI technologies.
Since these agents would require native cryptocurrencies to cover network fees, Kaul suggests that increasing transaction volumes could lead to higher demand for these tokens, which in turn would support developer incentives, enhance network security, and foster decentralized applications.
Her views resonate with a broader perspective articulated by Circle's Jeremy Allaire, who contends that the emergence of agentic AI and blockchain signifies a unified technological evolution rather than two distinct trends.
In a recent paper, Allaire noted that AI is driving down the costs associated with knowledge work, while blockchain and programmable digital currencies are similarly reducing expenses for payments, settlements, and coordination. As businesses increasingly rely on specialized AI agents, he believes these agents will function as economic entities that purchase services, hire additional agents, and autonomously exchange value. Blockchain networks, digital identities, and programmable money would form the necessary infrastructure to facilitate these interactions on a global scale.
This vision extends beyond mere payments. Allaire suggests that companies rooted in AI could operate directly on-chain, with tokens signifying ownership and governance, while pricing models for software shift from monthly subscriptions to pay-per-task as AI agents take on roles as both buyers and sellers of digital services.
For investors, Kaul asserts that the message is clear. Current AI investment portfolios have mainly concentrated on established technology firms that are developing models and infrastructure. Should autonomous AI agents become a significant component of the economy, she posits that blockchain networks and the cryptocurrencies supporting them could present an additional avenue for investors to participate in the next phase of AI growth.
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TRON Network - Q2 2026
TRON Network - Q2 2026
In Q2; TRON's stablecoin dominance rose to 28.7%, USDT supply on TRON hit $89B ATH, $89M in protocol fees (2nd to Hyperliquid), TRX +3%, and deepening institutional & agentic reach.
By CoinDesk ResearchJul 21, 2026Commissioned byTronIn Q2; TRON's stablecoin dominance rose to 28.7%, USDT supply on TRON hit $89B ATH, $89M in protocol fees (2nd to Hyperliquid), TRX +3%, and deepening institutional & agentic reach.
Why it matters:
In Q2; TRON's stablecoin dominance rose to 28.7%, USDT supply on TRON hit $89B ATH, $89M in protocol fees (2nd to Hyperliquid), TRX +3%, and deepening institutional & agentic reach.
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