You were trained to block bots, but now some bots are your customers' personal shoppers. For years, we've treated bots as threats; non-human actors whose very presence suggested risk. If the device was unfamiliar, the behavior irregular, or the user agent suspicious, we flagged it, blocked it, and moved on.
But earlier this year, something shifted. Early adopters are asking AI agents like ChatGPT or Perplexity to assist with real-world tasks: finding products, filling out forms, even navigating checkout flows. These agents don't spoof human behavior; they skip it entirely. Which means your fraud system, trained to detect non-human patterns, will do exactly what it was designed to do: end the session. Not because it was risky, but because it "wasn't human enough".
The real shift isn't automation, but rather, continuity. The identity behind every transaction has become the only stable signal of trust. Devices change, agents act, journeys fragment. But the individual behind them remains the anchor point that connects behavior over time. Continuity only matters, though, if the identity is genuine; preserving the thread means confirming it hasn't been hijacked along the way. The question is no longer what device initiated the action, but whether the identity it represents is real.
Welcome to the new world of agentic commerce.
The world’s largest networks and platforms are already legitimizing agent-based transactions:
While these programs are still in early stages, their existence signals that agentic commerce is not a hypothetical; the largest networks are already prototyping and preparing for it. Each initiative legitimizes agents as potential participants in commerce, but legitimacy at the protocol level doesn’t guarantee trust at the identity level.
Protocols don’t make decisions. Your system still has to answer the question: “Is this agent trusted enough to act for this user right now?” And increasingly, the harder question follows: “Or is it acting for someone pretending to be the user?”
Agentic commerce introduces both promise and peril. On one hand, it’s allowing users to delegate real actions to digital assistants. On the other hand, it’s giving fraudsters scalable new tools to mimic legitimate behavior with alarming precision. The agent itself isn’t inherently good or bad; it’s only a proxy. What matters is the authenticity of the identity controlling it. Recognition alone isn’t protection; only verified identity continuity can tell the difference.
In an automated world, the device is no longer the constant; the individual is. A growing share of digital interactions now originate from bots or delegated systems, which means device signals alone can’t tell you whether an interaction is trustworthy. What matters is the authenticity and continuity of the identity the agent represents.
That’s where most fraud and identity systems fall short. They were built to score discrete events, not recognize persistent identities across changing devices, agents, and contexts. They can detect that an agent is present, but they can’t confirm whether it’s acting on behalf of a trustworthy individual. When that continuity breaks—when your system can’t connect who it sees to who it knows— fraud signals misfire, legitimate activity stalls, and synthetic identities slip through.
Even if protocols authenticate agents, your models may still misclassify them as automated risk. Without continuously refreshed identity signals, retraining lags behind behavior, leaving systems brittle against new patterns.
Here’s how agentic commerce shows up today, not in volume, but in visibility gaps:
An AI agent attempts to complete a customer’s repeat transaction but fails device fingerprinting and triggers a block for automation, even though it was acting on behalf of a verified user. The session ends, but the user never knows why. You didn’t stop fraud; you broke the chain of trust.
The same technologies that let trusted customers delegate tasks also let fraudsters automate them. Without identity continuity, both can look identical to your system. No fraud score, no obvious error. Just another “suspicious” signal that got filtered out. A clean dashboard masking both lost customers and unseen attacks.
Yes, users have delegated before. Autofill, browser extensions, password managers; they’ve long acted on a user’s behalf in small ways. But agentic commerce marks a turning point.
These agents aren’t just storing credentials; they’re reasoning, deciding, and initiating actions. They don’t behave like humans or carry the contextual breadcrumbs like cookies, scrolling, or behavioral patterns that your system depends on.
But it’s not enough to recognize the behavior as agentic; you have to know the identity behind the behavior is real. That’s the shift from pattern recognition to identity verification; the difference between knowing something happened and knowing who made it happen.
Delegated behavior was passive; agentic behavior is active. A password manager fills in a field, but an agent decides what goes in it. And active autonomy breaks your heuristics. If your system still requires every interaction to look human, you’re not just scoring risk; you’re losing sight of identity continuity.
Elephant Trust is the first and only identity intelligence platform built to connect and verify identities across every transaction: human, device, or agentic. Our signals detect and classify known AI agents and verify the identity context behind their actions, so your system can differentiate authorized automation from synthetic fraud.
This dual lens—seeing both the agent and the identity behind it—is what distinguishes Elephant. It’s how organizations can safely embrace agentic commerce without inviting agentic fraud.
We monitor and update signal layers daily for emerging agent behavior, including:
IP range, user agent, and browser settings for:
Trust signals surfaced in:
Agentic commerce may change how transactions happen, but not who they’re tied to. Elephant keeps every action anchored to verified identity, the foundation of trust in an automated world.
Agentic commerce rarely announces itself. Instead, it will show up as lower conversion rates, higher form abandonment, “unusual” click paths that never complete, and clean fraud dashboards with unexplained revenue dips.
Most teams won’t notice right away, not because it’s invisible, but because their systems were never designed to connect activity back to verified identity. And that’s the hidden risk of agentic commerce: it doesn’t always look like fraud. It quietly erodes trust and revenue in ways that only identity-aware systems can detect.
You built your system to recognize users, but your users are beginning to send proxies. And your system, without realizing it, may already be losing track of who’s behind the interaction.
Agentic commerce is the next evolution of digital interaction and the next frontier of fraud. The only safeguard is trust intelligence that ties every action—human or agentic—back to a verified identity. Elephant is the first and only identity intelligence platform built to ensure that you always know the difference between trusted automation and identity manipulation.