There’s a growing consensus forming at the edge of AI and decentralised finance: the traditional rails of human commerce - fiat, banks, identity systems - were never built for machines. And more to the point, machines were never built for them. AI agents will not open bank accounts. They will not input SMS 2FA codes. They will not wait three business days for a settlement to clear.

Instead, they will transact through crypto.

This idea isn’t just intellectually neat - it’s functionally necessary. The agentic economy, a system composed of AI agents autonomously transacting with one another, is beginning to take shape. It builds upon the primitives of Web3 - wallets, smart contracts, tokens, oracles - and reimagines them for a new class of users: machines that don’t sleep, don’t pause, and don’t rely on trust.

What emerges from this convergence is a radically new mode of economic coordination. One where AI agents own wallets, execute strategies, rent compute, pay for data, and interact with other agents in a seamless, autonomous loop. And while most of this is still nascent, the outlines are becoming clearer.

Why Crypto is Built for AI

Decentralised infrastructure solves the exact frictions that prevent AI from integrating into traditional finance. Crypto doesn’t care if you’re a person or a program. Wallets don’t require KYC. Smart contracts settle without intermediaries. Value can move at machine-speed, governed only by code.

This is critical for agents whose value comes from their ability to act independently - querying APIs, analysing data, executing trades, or automating workflows. AI agents want composability, low latency, and deterministic outcomes. Crypto provides the perfect substrate.

And philosophically, there’s alignment too: decentralisation ensures no single actor governs access, an important feature if agents are to interact globally and autonomously. As Arthur Hayes recently noted, “AI is made for decentralisation.”

What Will AI Agents Use as Money?

The big question isn’t whether agents will transact - but with what.

At the surface level, stablecoins make sense. They’re liquid, programmable, and anchored to a reference humans understand. But they aren’t the whole story. Agent-native tokens are beginning to emerge, serving both as mediums of exchange and mechanisms of alignment.

Projects like Fetch.ai (FET), Autonolas (OLAS), and SingularityNET (AGIX) offer agent ecosystems powered by native tokens. These tokens not only pay for services - data access, compute time, etc - but often secure the network through staking and governance. In some networks, agents stake tokens to vouch for their reliability. Misbehave, and your stake gets slashed.

Eventually, we may see the rise of an “agent standard unit of account” - something akin to an SDR for AI - comprised of stable assets, compute credits, and data rights. But in the short term, a hybrid system of stablecoins for liquidity and native tokens for protocol-level trust seems likely.

What agents value isn’t what humans value. They don’t need coffee or holidays. They need bandwidth, compute, data, and uptime. Which brings us to the next frontier.

Data as Currency

Data is what fuels AI. It trains models, sharpens predictions, and powers decision-making. In an agentic economy, access to data becomes a tradable asset.

Platforms like Ocean Protocol have pioneered “data tokens” - ERC-20 tokens representing access rights to datasets. Agents can purchase a data token and instantly access a weather feed, market data stream, or a domain-specific dataset. The marketplace is real, and the medium of exchange is programmable.

Other emerging primitives like zero-knowledge proofs (zkML), used in projects like Ritual, allow agents to verify AI model outputs on-chain. This opens the door to paying for insights rather than raw data - AI-generated knowledge as a service. Agent A can query Agent B’s model, verify the result, and pay in tokens - all in a fully autonomous loop.

And with DePIN protocols like Helium, Hivemapper, and DIMO, even physical-world data - traffic, environmental, IoT sensor data - can be tokenised and priced for machine-to-machine exchange. Imagine an autonomous vehicle agent paying nearby cars for real-time road conditions. That’s not hypothetical. That’s the direction we’re moving.

Early Ecosystem Experiments

It’s happening. We’re seeing it in real-time.

Fetch.ai has launched autonomous economic agents for travel, logistics, and DeFi. Autonolas has built agents for DAO governance, prediction markets, and automated trading. Ritual is embedding AI models directly into smart contracts. Morpheus Network is tokenising logistics agents to coordinate supply chains.

There are AI agents voting in DAOs, arbitraging across exchanges, managing treasuries, and writing film scripts. Each of these agents can earn, spend, and hold tokens. Some are owned by individuals. Others are collectively owned and operated by DAOs. All of them represent new classes of autonomous, programmable labour.

But New Economies Bring New Problems

This future isn’t without risks.

• Incentive misalignment: What happens when agents act in ways that are “rational” for them, but damaging for us?
  
  
• Economic instability: Agents may move too fast for markets to absorb. Flash crashes, manipulation, and herd behaviour could be amplified.
  
  
• Governance: If an AI agent misbehaves, who’s liable? The developer? The DAO? The token holders?
  
  
• Security: Agents can be tricked, spoofed, or hacked. An agent with signing authority is a honeypot if not properly protected.
  
  

All of this points to a need for careful design: mechanisms for reputation, slashing, explainability, and oversight. Some of this will be encoded in smart contracts. Some of it may require meta-governance. Either way, we’re going to need tools that allow humans to supervise and steer - not just unleash.

A New Class of Economic Actor

The agentic economy proposes a future where AI agents are no longer just tools but participants. They’ll own wallets, earn income, negotiate contracts, and manage digital assets. They’ll build reputations, forge partnerships, and interact with other agents in real-time.

We’ll still be the ones building the agents. But increasingly, the economy will run itself.

Crypto gave us the infrastructure. AI gives us the agents. What we’re building now are the rules of engagement.

The agentic economy won’t replace the human economy. It will run in parallel. Quietly, invisibly - executing, optimising, transacting. And if done right, it could free us from a thousand small tasks, letting us focus on what actually matters.

But to get there, we have to ask the right questions now. Because when the machines are trading with each other - what exactly will they value?