AI Agent Security, Governance, and Risk Management

AI AGENTS FOR BUSINESS RESOURCE CENTER

AI agents combine model uncertainty with access to business systems. Security must govern identity, data, tools, decisions, and operations.

Reviewed and updated July 2026.

Threat model

Relevant risks include prompt injection, malicious retrieved content, excessive agency, data leakage, insecure tool calls, credential exposure, hallucinated actions, duplicate transactions, compromised integrations, inadequate logs, and overreliance by employees.

Identity and access

Give each agent a dedicated nonhuman identity. Apply least privilege, short-lived credentials where possible, scoped API tokens, network boundaries, separation of duties, and periodic access review. Never embed secrets in prompts or source content.

Tool and action controls

Allowlist tools and parameters. Validate inputs and outputs outside the model. Use transaction limits, idempotency, rate limits, confirmation for destructive changes, and human approval for consequential actions.

Data protection

Classify data, minimize collection, restrict retrieval by user and tenant, encrypt in transit and at rest, define retention, support deletion, redact sensitive logs, and document where providers process information.

Human oversight

Define which actions are automatic, which require approval, and which are prohibited. Make escalation fast and preserve enough context for a person to take over. Human review must be meaningful, not a rubber stamp.

Testing and monitoring

Evaluate quality and security before release. Red-team malicious instructions and data exfiltration attempts. Monitor tool errors, unusual access, policy violations, drift, cost anomalies, corrections, and user complaints.

Incident response

Maintain the ability to disable an agent, revoke credentials, isolate integrations, preserve evidence, notify owners, correct affected records, communicate with customers, and conduct a post-incident review.

Governance checklist

• Named business and technical owners
• Inventory of agents, models, tools, and data
• Risk tier and permitted autonomy
• Documented approvals and prohibited actions
• Evaluation and release criteria
• Audit, monitoring, and review schedule
• Vendor and data-processing assessment
• Incident response and shutdown procedure

Continue learning

• Complete guide to AI agents for business
• AI agent use cases by function and industry
• AI agent implementation framework
• Security and governance
• Cost and ROI planning
• Platform buyer’s guide
• AI agent glossary