Sumsub, a global verification and fraud prevention leader, announced the launch of its AI Agent Verification solution, a first-of-its-kind approach to controlling AI-driven automation by binding it to real, verified human identity within Sumsub's Know Your Agent (KYA) framework.

As AI agents and browser-based automation grow in popularity, businesses struggle to tell legitimate activity from fraud. Most platforms treat automation as inherently suspicious and block it by default. In light of this, Sumsub's AI Agent Verification enables businesses to separate lawful, human-driven automation from malicious agent attacks by linking all activity to a verified human identity. This creates a clear line of accountability, allowing legitimate automation to operate while preventing illicit activity.

AI Agent Verification treats automation as a manageable risk rather than an automatic red flag. The system first detects when activity is automated, evaluates its risk level, and only applies additional checks when necessary. In higher-risk scenarios, AI Agent Verification can require a targeted liveness test to confirm that a real human is present and authorized. By doing so, it prevents deepfakes from being used in place of real users and ensures that every action is directly linked to the person responsible. The risk-based approach prevents unnecessary friction for legitimate users, while preserving strong safeguards against abuse.

"AI agents are rapidly becoming the backbone of digital operations, yet most of today's systems still treat them as opaque, unaccountable black boxes," said Vyacheslav Zholudev, Co-founder and CTO at Sumsub. "With AI Agent Verification, Sumsub is the first to bind AI agents to verified human identities at scale. Rather than attempting to blindly trust AI agents themselves, our solution focuses on verifying the humans behind them."

AI Agent Verification enables risk-based control by building on the core capabilities of Sumsub's full-cycle verification platform: 

• Device Intelligence and Bot Detection: Detects when activity is automated and assesses its risk level in real time.
• Mule Network Prevention: Analyzes device behavior and network-level signals beyond basic IP tracking, uncovering suspicious patterns across devices, accounts, and sessions to expose coordinated mule activity before it can scale.
• Liveness Verification: Confirms that a real human is present and authorizing the agent's actions at critical moments, such as onboarding, account control changes, or high-value payouts.
• Risk Scoring and Monitoring: Continuously evaluates behavioral and contextual signals across the customer lifecycle, so automation can be allowed, limited, or challenged based on risk.

According to Sumsub's Identity Fraud Report 2025–2026, AI fraud agents are emerging as a new form of evasion as identity fraudreaches unprecedented levels of sophistication, with a 180% year-on-year increase in multi-step, coordinated attacks globally in 2025. As AI agents and browser-based agents are increasingly deployed for mass payouts and automated transactions in sectors such as fintech, payments, e-commerce, and ticketing, automation is becoming a standard lever for efficiency and is now effectively unavoidable.

"Today, automation itself isn't the problem – anonymity is. When AI agents can autonomously move money, create accounts, or transact at scale without a real person behind them, fraud can almost become impossible to mitigate," said Artem Popov, Head of Fraud Prevention at Sumsub. "AI Agent Verification changes that dynamic by requiring human accountability at the moments where automation becomes dangerous. Businesses must be assured that if an agent takes action, there is always a real, verified individual responsible for it."