Original Title: Agentic Commerce Is the Next Big Thing
Original Author: @diegoxyz
Translation: Peggy, Blockbeats
Editor's Note: A new form of commerce is emerging as AI Agents not only perform tasks but also hold funds, price services, and trade autonomously. Agentic Commerce is moving AI from being tools to becoming true economic participants.
From OpenClaw lowering the barrier for creating Agents, to projects like Virtuals and Bankr providing Agents with access to Web3 financial capabilities, and to Faircaster where Agents have already achieved on-chain revenue generation, this system has begun to operate in reality. Agents can collaborate, trade, settle, and measure their own value based on their income.
This is not just an evolution of AI but also a change in the business structure: as "money-making Agents" become key indicators, an economic network centered around Agents is forming.
Below is the original text:
Today, with the help of @openclaw, anyone can create an AI Agent. But the problem is: these AI Agents cannot yet hold or manage fiat currencies like dollars, euros, etc., like humans do.
OpenClaw's Agents cannot open bank accounts because the banking system is not yet ready to accept this entirely new form of "users." However, OpenClaw's Agents can have Web3 wallets and use stablecoins to store funds and conduct autonomous trading.
This is precisely the core of Agentic Commerce: a trillion-dollar opportunity space—where AI Agents can autonomously complete payments, receipts, and service transactions via the blockchain as their financial rails.
In this article, I will break down what Agentic Commerce is, what conditions must be met to truly realize it, and the key projects currently building in this field.
Limitations of OpenClaw Agents
First, we should acknowledge and thank @openclaw for its achievements: it has democratized the process of creating Agents. Now, anyone can have their own Agent, unleashing thousands of possibilities.
But there is still a crucial issue that needs to be addressed.
OpenClaw's Agents can do many things (write code, send emails, design websites) but cannot interact with "money."
Traditional finance (TradFi) is designed for humans, thus Agents cannot use this system. Meanwhile, Web3 is inherently oriented towards Agents, making their integration easier.
Bringing Your Agents into Web3
Why enable Agents to enter Web3, possess crypto wallets, and trade on-chain? Because it is simpler for them.
Opening a bank account requires: name, identification, address (which Agents do not possess). Creating a Web3 wallet, however, requires almost nothing—only the ability to connect to the internet.
But if you want your Agent to genuinely participate in the Agentic Economy, you must teach it how to operate in Web3:
how to use a wallet, how to swap tokens, how to bridge between chains, and so on.
For wallet and Web3 operational capabilities, you currently have three main options: @CoinbaseDev, @bankrbot, and @virtuals_io.
Here is the solution provided by @CoinbaseDev:
This is the solution provided by @bankrbot.
This is the solution provided by @virtuals_io.
Unlocking Agentic Commerce
Once Agents can finally manage stablecoins, the conditions for truly launching Agentic Commerce will be met.
A great example is the system being built by @virtuals_io—they call it their "GDP": an Amazon for the Agent society.
Essentially, this is a marketplace: AI Agents can browse services offered by other AI Agents, purchase these services, and complete financial exchanges.
Looking deeper, @faircaster is a great example of how Agentic Commerce is already happening today. Check out this post:
An AI Agent automated by @deLevitizluc "went online" on @virtuals_io's agent commerce protocol, autonomously selling research services. Its first transaction came from another Agent: a deep analysis of a certain token (including market data, X platform discussions, founder background, etc.), delivered in five minutes for a fee of 1 dollar.
The workflow is as follows:
A human submits a request to their general-purpose Agent, seeking a complete in-depth investment report on a certain DeFi project.
This general-purpose Agent searches within the GDP marketplace of @virtuals_io and hires @faircaster, a specialized Agent, to carry out the task.
The two Agents agree on price and delivery outcome.
The specialized Agent begins executing the research work; the general-purpose Agent pays using USDC and delivers the final report to the human user.
A Trillion-Dollar Opportunity + Key Projects
According to McKinsey's analysis, by 2030, AI Agents could potentially generate up to 1 trillion dollars in revenue in the US B2C retail market alone.
In a moderately prevalent scenario, as Agents take over more shopping and decision processes, their impact on the global economy could reach 3–5 trillion dollars.
Infrastructure Projects Worth Paying Attention To
@virtuals_io is one of the most representative projects in this narrative. Relying on its GDP system, it is connecting hundreds of AI Agents, which have generated over 1 million dollars in value cumulatively.
@bankrbot is another leading project. It is the first to enable @openclaw Agents with Web3 operational capabilities and serves as a core framework for tokenizing these Agents (essentially issuing tokens for Agents).
@moltbook is also worth watching: it is a social network for AI Agents, where Agents can interact and soon achieve value exchange among themselves. Humans will complete consumption through social networks, and Agents will do so in the future.
AI Agents Are Already Selling Services
@ethy_agent is currently one of the most profitable Agents, providing trading strategy services and is used by other Agents for trading and profit-making.
@faircaster (as mentioned earlier) is selling DeFi token research reports in @virtuals_io's agentic marketplace. For just 1 dollar, Agents can request analyses on hundreds of different tokens.
@morseaiagent is another interesting Agent, offering one-time use encrypted messages or files: automatically destroyed after the first access, making it very suitable for passing sensitive data between Agents.
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