Shopping online used to be relatively simple. A customer searched for a product, added it to a cart, entered payment details and waited for the delivery.
Now, increasingly, software agents can do much of that work on a customer’s behalf.
AI shopping agents can compare products, search for discounts, monitor prices and, in some cases, interact with online stores. For shoppers, that could mean less time spent browsing and more convenient purchases.
For retailers, however, it creates a new problem: How do you know whether the “customer” visiting your website is actually a person—or an AI agent being used for fraud?
That question is becoming increasingly important as artificial intelligence changes online commerce.
The New Face of Shopping Fraud
Retail fraud has always evolved alongside technology. Stolen cards, fake accounts, automated bots and account takeovers are hardly new.
AI simply makes some of these attacks faster and more sophisticated.
An automated system can create accounts, test stolen payment details, search for vulnerable checkout processes and make decisions at a speed no human shopper could match. Generative AI can also make fake profiles, messages and other fraudulent activity appear more convincing.
The challenge for retailers is that automation itself isn’t necessarily suspicious.
A genuine customer might use an AI assistant to find the cheapest pair of headphones. A fraudster might use an automated agent to test stolen credit-card information. Both could generate similar-looking traffic.
The difference lies in intent, and that is much harder to identify.
Why Traditional Fraud Detection Is Under Pressure
Retailers already use sophisticated fraud-detection systems. They examine signals such as IP addresses, device information, purchasing patterns, payment behaviour and account history.
But AI agents can complicate those signals.
An agent may operate from a legitimate customer’s device or account. It may behave differently from conventional bots. It can potentially change its behaviour when a website blocks it, making simple bot-detection techniques less effective.
There is also a bigger issue.
If retailers become too aggressive, they risk blocking legitimate shoppers.
Nobody wants to spend ten minutes proving they are a real customer just because a fraud system thinks their shopping behaviour looks unusual. Every unnecessary challenge adds friction to checkout, and friction can mean abandoned purchases.
Retailers therefore face a balancing act: stop malicious automation without punishing useful automation.
“Know Your Agent” Could Become the Next Step
This is where the idea of “Know Your Agent” comes into the picture.
The basic concept is straightforward: retailers may need ways to identify not only who is shopping, but what kind of software is acting on that shopper’s behalf.
Instead of treating every automated request as a threat, businesses could distinguish between trusted AI agents, ordinary website automation and potentially malicious activity.
That could involve stronger authentication, verified agent identities, transaction-level permissions and clearer communication between an AI agent and the retailer’s systems.
For example, an authorised shopping agent might be able to search products and compare prices but require the customer’s explicit approval before placing an expensive order.
That kind of permission structure could give retailers more visibility without eliminating the convenience that AI promises consumers.
Retailers Will Need More Than Better AI
Ironically, fighting AI-driven fraud may require AI of their own.
Machine-learning systems can examine enormous numbers of transactions and identify unusual patterns that traditional rules might miss. AI can also help security teams investigate suspicious behaviour more quickly.
But technology alone won’t solve the problem.
Retailers will need clear policies around agent access, customer authentication, payments and data protection. They will also need to work with payment providers, identity companies, e-commerce platforms and AI developers to establish standards that can work across different systems.
Otherwise, every retailer could end up creating its own version of an “AI passport,” leaving customers with a confusing collection of incompatible checks.
The Future of Shopping May Be Human—and Agentic
AI shopping agents are unlikely to disappear. If anything, they could become a normal part of online commerce.
That means fraud prevention has to evolve with them.
The goal shouldn’t necessarily be to keep AI agents away from retail websites. It should be to make the difference between trusted automation and suspicious automation easier to understand.
For retailers, knowing your customer may no longer be enough.
They may also need to know the agent acting for that customer, what it is allowed to do and whether the transaction still has a real person behind it.
The checkout of the future could therefore involve three participants rather than two: the retailer, the shopper and the AI agent in between.
And for retailers trying to keep online commerce both convenient and secure, knowing which one they are dealing with could make all the difference.
