AI Agents Need Security Training – Just Like Your Employees
AI Agents Need Security Training – Just Like Your Employees
https://www.infosecurity-magazine.com/news-features/ai-agents-need-security-training/
Publish Date: 2026-04-02 02:51:25
Source Domain: www.infosecurity-magazine.com
Summary of the Article
The growing surge in enterprise AI adoption has introduced unique challenges for security leaders, with AI agents now possessing insider status due to their access to sensitive data and organizational systems. Yet many companies still fail to treat these AI agents as high-risk entities requiring robust security controls. Meghan Maneval from Safe Security, discusses the necessity of extending mandatory security awareness training to AI agents similar to human employees. Maneval outlines best practices for AI auditing during a session at ISACA Europe 2025, emphasizing the need for extensive documentation, deep dives into the AI’s inner workings, and thorough risk management. She advocates that AI tools should be monitored using system logs, behavioral analysis, and detecting AI drift. For a complete audit, it’s crucial to review underlying algorithms, training data, outputs, and the surrounding controls to ensure both fairness and protection of sensitive data. Overall, Maneval emphasizes the importance of treating AI agents with the same care and oversight accorded to human insiders.
Key Points:
- AI as Insiders: AI agents have the same access as human employees and should thus be treated as high-risk insiders.
- Comprehensive Inventory: Conducting a thorough inventory of AI tools, usage, and third-party applications is crucial to understand the full scope of AI operations within an organization.
- In-Depth Auditing: Detailed examination of AI components, including algorithms, training data, and decision-making processes, is essential to uncover biases and risks.
- Security Controls: AI agents should be subjected to the same security controls as human employees, including role-based access controls and secondary approvals.
- Monitoring Techniques: Utilize a combination of system log analysis, behavioral analysis, AI drift detection, and anomaly detection to ensure AI systems operate correctly and safely.
