Agentic AI revolutionizes business processes by enabling AI agents to access data, utilize tools, call APIs, and make decisions. This whitepaper explores the security risks associated with this growing autonomy and offers a practical way to understand and manage the security exposure of agentic AI.
What you’ll learn
- Why Agentic AI Changes Enterprise Exposure: Understand how AI autonomy, system access, and connected workflows expand security exposure.
- The Standards and Guidance Landscape: Explore the various security and risk management standards and guidelines relevant to agentic AI.
- Risk Anatomy of Agentic Systems: Examine risks such as over-privilege, data exposure, weak auditability, and insufficient containment.
- Best-Practice Assessment Model: Adopt a practical 5-step process for assessing and managing agentic-AI exposure.
- Control Themes That Matter Most: Identify the core controls needed across access, governance, monitoring, and containment.
- Incident Response Implications: Understand how AI changes detection, investigation, evidence collection, and containment.
- Representative Risk Scenarios: Explore practical scenarios involving data leakage, ransomware reconnaissance, and third-party AI exposure.
- Prioritized Remediation Roadmap: Build a phased approach to reduce exposure and strengthen long-term readiness.