AI agents are increasingly deployed in enterprise environments to automate workflows, access data, schedule meetings, write code, and perform actions autonomously. Unlike traditional users or service accounts, AI agents operate with delegated authority that often spans multiple systems and users, making their access persistent, broad, and difficult to govern. This creates a fundamental challenge to existing Identity and Access Management (IAM) models, which rely on clear ownership, defined roles, and periodic reviews tied to human behavior. AI agents can accumulate permissions over time (access drift), acting as intermediaries that enable users to perform actions indirectly that they are not authorized to do directly, a phenomenon termed agentic authorization bypass. The risk is categorized into three types: personal agents (user-owned with limited scope), third-party vendor-owned agents (governed by vendors), and organizational agents (shared, often ownerless, with broad permissions). Organizational agents pose the greatest risk due to lack of clear ownership, accountability, and lifecycle management, leading to large blast radii and potential systemic security failures. The article emphasizes the need to rethink risk management by treating AI agents as distinct entities with their own identities and permissions, requiring explicit ownership, continuous access reviews, and mapping of user-agent interactions to prevent unauthorized actions and detect misuse. Without these measures, AI agents can silently create authorization bypass paths, undermining enterprise security and compliance.

For European organizations, the threat posed by AI agents is significant due to the increasing adoption of AI-driven automation and digital transformation initiatives. The uncontrolled expansion of AI agent permissions can lead to unauthorized data access, exposure of sensitive information, and execution of unintended or malicious actions without direct user involvement. This can result in breaches of data protection regulations such as GDPR, causing legal and financial repercussions. Operationally, AI agents with broad access can disrupt workflows, corrupt data, or trigger unintended system changes, impacting business continuity. The lack of clear ownership and accountability complicates incident response and forensic investigations, increasing the time and cost to remediate incidents. Additionally, the agentic authorization bypass undermines traditional security controls, potentially allowing insider threat scenarios or supply chain risks to escalate unnoticed. European enterprises with complex, multi-system environments and stringent compliance requirements are particularly vulnerable to these risks if AI agent governance is not properly implemented.

1. Establish explicit ownership and accountability for every AI agent, especially organizational agents, with clear approval and review processes. 2. Integrate AI agents into IAM frameworks as distinct identities with tailored permission sets, avoiding overprivileged access. 3. Implement continuous monitoring and auditing of AI agent activities, including detailed logging of user-agent interactions and actions performed. 4. Map and document the full lifecycle of AI agents, including creation, deployment, permission changes, and decommissioning, to prevent access drift. 5. Enforce strict segregation of duties and least privilege principles specifically for AI agents, limiting their scope to necessary functions only. 6. Use automated tools to detect anomalous agent behavior and unauthorized access patterns indicative of agentic authorization bypass. 7. Incorporate AI agent risk assessments into enterprise risk management and compliance programs, ensuring alignment with GDPR and other regulations. 8. Educate security teams and stakeholders on the unique risks posed by AI agents and update incident response plans to address agent-related incidents. 9. Collaborate with AI platform vendors to understand embedded third-party agents’ security controls and supply chain risks. 10. Regularly review and update policies governing AI agent deployment and use, adapting to evolving threat landscapes and organizational changes.