Sinch

Why AI Agents Are Not Digital Employees: Control Mechanisms and Organizational Risks Explained

Alexey Lapunov from TECHNONIKOL Digital's information security department explains why AI agents require extensive surrounding governance structures to function as reliable digital workers. Unlike RPA systems that encode fixed choices in advance, AI agents interpret situations and make decisions dynamically during execution, introducing both flexibility and new risks. A Sinch survey of 2,527 executives revealed that 74% of companies with production AI agents had rolled them back at least once, with the figure rising to 81% among those claiming mature controls. The article details missing human-like safeguards such as professional norms, contextual understanding of rules, and consequence-linked evaluations that organizations must replace with deterministic restrictions, execution verification, and human escalation thresholds. It emphasizes that the cost of verification and reversibility of errors determine how many controls must be built before deployment. Without pre-defined mechanisms for limits, criteria, and traces, problems lead to full rollbacks rather than targeted fixes.