Why the Agentic Economy Needs a Trust Layer

AI researchers spend a lot of time thinking about reasoning, safety and scale. The people deploying AI agents have a more immediate problem. The basic plumbing still isn’t there. 

When an agent books something, pays for compute, or buys access to a dataset on someone else’s behalf, somebody has to make sure the payment clears, check the other side delivered what it promised, and give the person behind the transaction some recourse if it didn’t. None of that depends on how smart the model is. It depends on the legal, financial and technical infrastructure around it, and right now there’s not much of it.  

That’s becoming a much bigger issue as AI agents start handling real economic activity that touches everyday consumer or business activity. Gartner forecasts they’ll intermediate more than $15 trillion in B2B purchasing by 2028, with machine-to-machine negotiation and automated procurement becoming part of everyday enterprise commerce. 

What these agents need to be able to achieve this is a shared infrastructure for trust, provenance and settlement, exactly the role blockchain was built to play. 

From assistants to actors 

Over the last few years, AI as many understand it – Generative AI – mostly answered questions. Then it learned to draft documents, summarise meetings and write code. It still waited for someone to tell it what to do, and someone else signed off before anything actually happened. 

Agents are different. They can find a supplier, agree a price, make a payment and coordinate with other software to get the job done, all without waiting for a person to approve each step. Scale that across a business and you have dozens of agents making decisions and striking deals with systems they’ve never interacted with before, all day, every day. 

That’s already starting to happen. HUMAN Security’s 2026 Cyberthreat Report found autonomous agentic AI traffic across product discovery, account flows and checkout processes grew 7,851% year over year, a sign that AI is actively transacting on the web. 

Why a person can’t approve every step 

The obvious answer is to put a person in the loop, but that breaks down for the same reason it always has at scale. Reviewing every transaction is slow, expensive, and suffers from diseconomies of scale. This didn’t matter when transaction volumes or B2B payments were manageable,but it does when every agent is making dozens of small purchases an hour, paying for compute, buying data, or hiring another agent to do part of the job. 

At that point, trust has to move from the human reviewer into the infrastructure itself. Agents need a shared way to verify permissions, payments and outcomes without waiting for a person to approve every step, which is where blockchain becomes useful. 

People still have a role to play, but it’s a different one. They decide what an agent is allowed to do, review what happened afterwards, and step in when something goes wrong, instead of approving every payment or decision as it happens. 

The missing infrastructure for accountability 

Imagine a manufacturer’s agent detects that a key component is going to run short and starts looking for alternatives. It finds a supplier, checks its credentials, negotiates the terms, places the order and hands delivery to another logistics agent. If the supplier sends the wrong parts or the shipment disappears, the business needs a reliable record of who agreed what, who handled each step and where responsibility lies.  

But what can the first agent, or the person behind it, actually do? 

Right now, very little. There’s nowhere obvious to take the dispute, nothing to claim against because nobody has worked out how to insure it and no reliable record of the other agent’s past behaviour to check beforehand. 

In many cases, the person who set the whole thing in motion may never even know it failed, and that gap is already starting to show. Incode Technologies found agentic fraud accounted for 40% of attack attempts in early 2026, contributing to more than $20.9 billion in annual cyber-enabled financial losses. In short, we’ve built systems that can transact before we’ve built anywhere for those transactions to go when they break. The basic systems human commerce has always relied on simply don’t exist yet for machines.

Somewhere to settle disagreements

If two agents disagree over whether a job was done properly, someone needs a way to resolve it. Human commerce solved that a long time ago with contracts, dispute resolution, insurance, reputation and payment systems that support all of the above. AI agents will need the same foundations, yet almost none of them exist today. 

Most of the attention is going into payments because they’re the most visible part of the puzzle. But moving money is only useful if there’s a way to establish who was responsible, whether the agreed work was delivered, and what happens when it wasn’t. Without that, faster payments simply mean mistakes and fraud move faster too. 

Better models aren’t the constraint 

Better models will keep coming, but they probably won’t determine how quickly AI agents become part of everyday commerce. History tends to reward the technologies that build the right infrastructure around themselves. The internet needed standards and payments before businesses could rely on it. Cloud computing needs identity and access controls, and AI agents still need the equivalent layer for trust, accountability and transactions.  

That’s where blockchain becomes critical 

Blockchain’s real value isn’t decentralisation for its own sake, but providing a shared record that multiple parties can rely on without one of them being able to rewrite it later. Combined with verifiable identity and programmable contracts, it gives developers the foundations for reputation, dispute resolution and payments that can operate at machine speed. The winners in agentic commerce will build smarter agents and, just as importantly, the infrastructure that makes those agents trustworthy.