AI agents are moving beyond chatbot duties and taking on a larger role across the internet. As software begins to research, buy, adjust, and complete tasks with limited supervision, new questions arise. How do non-human users pay, prove their identity, and operate within clear rules?
This question opens up unexpected paths for cryptocurrencies, especially in stablecoins, digital wallets, and machine-friendly identity systems.
For years, cryptocurrencies have sought a role native to the internet. Trading attracted attention and speculation brought traffic. But it felt incomplete, as if its deep promise pointed elsewhere: a financial system designed for digital life from the beginning.
AI agents could further enhance that promise.
This term can seem vague because it’s used for almost everything in AI. An AI agent is software that can set a goal, break it down into steps, use tools, gather information, and perform actions with some degree of autonomy.
This change essentially changes how the Internet works. Chatbots provide answers to questions, while agents can compare vendors, renew subscriptions, book services, monitor budgets, send instructions to other software, and complete tasks from start to finish.
But how does software participate in the economy once it starts acting like a user?
The Internet is home to a new breed of users: AI agents
Imagine a company that uses AI agents to handle some of its daily tasks. The system notices the increase in demand, buys additional computing, pays for data services, updates software tools, and logs each step for review.
At that point, the question is no longer whether the software has the ability to reason about the task. The biggest question now is whether the Internet has a financial system built for software that runs on its own.
That’s where cryptocurrencies have the potential to separate from the hype surrounding “AI tokens.”
Novelty coins attached to vague promises from AI projects are not the best use case for cryptocurrencies. Agents need wallets, credentials, payment systems, and clear operating rules. They must also hold value, spend within predetermined limits, prove who they represent, and leave records that can be reviewed later.
Traditional (statutory) payments can handle some of that. However, they are built around individuals and businesses, with cardholders, bank accounts, and well-known liability rules at their core.
But AI agents require a different design. They may need to perform many small transactions, interact between services, follow preset budgets, and operate within strictly defined permissions, which requires a more programmable setup.
Fortunately, cryptocurrencies have spent years building products and infrastructure that meet these needs.
Wallets are a prime example. With cryptocurrencies, spending limits, whitelists, approval requirements, and delegated access can all be included within their design, allowing wallets to be more than just storage tools.
This makes it easy to pay approved vendors, stay within budget, and create AI agents with narrow privileges that can only act within specific tasks.
Identity is also very important. As agents become more prevalent, platforms will need better ways to answer basic questions such as: What is this agent? Who gave it authority? What can it do?
a16z now calls this shift “Know Your Agent,” arguing that the bottleneck of the agent economy is shifting from intelligence to identity. According to the company’s own estimates, non-human identities in financial services already outnumber human employees by 96 to 1.
However, cryptographic identity systems are not ready to completely dominate. However, they match the shape of the challenge. Encrypted credentials and portable certificates allow software to prove origin, authority, and authority in a format that other systems can verify.
Payments are the third part, and probably the one that the market will understand the quickest.
When agents start their economic activities online, they need a way to move money that looks and feels native to the web.
This is where stablecoins stand out above most others in cryptocurrencies. These are dollar-pegged digital assets that can be moved 24 hours a day around the world and have a level of programmability that makes them particularly suitable for software-driven activities. Even BIS noted that stablecoins are becoming increasingly attractive for cross-border payments and trade settlements, despite warnings about their limitations and policy risks.
Why can cryptocurrencies be more profitable than “AI coins”?
All of this has led major payment companies to lean towards cryptocurrencies.
Visa has publicly described secure agent-driven transactions, saying agent commerce introduces new complexities and new forms of risk as agents enter the payment flow. Stripe has launched a product targeting stablecoins and what the company calls “agent commerce.” Mastercard said agent commerce is expanding and has launched a new crypto partner program built around programmability and the use of real-world digital assets.
This mainstream validation is helpful because the broader AI trend is already a reality. According to OECD data, the adoption rate of AI among companies will increase from 8.7% in 2023 to 14.2% in 2024 and 20.2% in 2025. These numbers do not represent overnight adoption, but they do point to a growing wave of software systems filling narrow but meaningful jobs within the economy.
If you look at it from that angle, the obvious opportunities for cryptocurrencies in AI are pretty boring. Cryptocurrencies are permeated with AI through stablecoin infrastructure, wallets, identity and credential layers, and software-initiated economic activity auditing and settlement systems.
This is also one of the reasons why so many AI-branded crypto tokens have a hard time retaining their value. AI stories may garner short-term attention, but lasting value usually comes from the layers that people actually use. In this case, it refers far more to digital dollars, machine wallets, and verifiable credentials than to speculative “agent coins.”
Bitcoin fits into this story a little more indirectly. The company could still benefit from a strengthening digital asset environment and widespread acceptance of internet-native finance. But if an AI agent is paying for software, data, or cloud services, the most obvious fit is definitely not Bitcoin, but a stable, programmable unit of value.
There are still real obstacles here. Trust, security, fraud, and liability are not immediately resolved when an agent obtains a wallet. Businesses will demand tighter oversight, platforms will demand stronger authentication, and regulators will demand accountability under pressure.
The more autonomous software becomes, the greater the demand for systems that can express identities, permissions, budgets, and validation in clear digital form. Crypto has been building these pieces over the years, often without a clear mainstream destination.
AI agents may finally give it to them.
For a long time, the biggest problem with cryptocurrencies was that many could not understand why ordinary users would need a separate financial system online.
The answer may come from another direction, as it turns out that the perfect user of programmable money is actually software. The most powerful use case for machine-friendly IDs may be from non-human users. And the most attractive role for cryptocurrencies may emerge when agents need to buy, adjust, and trade on their own over the Internet.
If that happens, the long quest for product-market fit for cryptocurrencies could end in an unexpected place: the financial layer where the software works.
