AI Agent Governance, Safety, and Compliance Tools cover the platforms and controls needed to deploy autonomous and semi‑autonomous AI agents responsibly across enterprises. As agentization expands—from conversational voice and chat agents in contact centers to autonomous SecOps and domain‑specific assistants—organizations must combine model infrastructure, runtime safety, observability, and policy enforcement to meet operational and regulatory obligations. Key categories include AI Governance Tools (policy engines, audit trails, provenance), AI Security Governance (threat detection, remediation agents, context lakes), and Regulatory Compliance Tools (data residency, consent, industry controls). Representative tools illustrate these roles: Observe.AI and Skit.ai focus on contact‑center automation with VoiceAI and real‑time agent assist plus compliance‑first integrations; Firsthand’s Brand Agent platform pairs real‑time personalized agents with a governance layer (Lakebed) to control behavior across web and partner surfaces; Simbian supplies autonomous SecOps agents and a unified Context Lake to accelerate detection and reduce missed alerts. Infrastructure and model layers—Vertex AI and Cohere—provide managed model training, deployment, private LLMs, and retrieval; Claude and Harvey represent conversational and domain‑specific assistants used within governed workflows. Current priorities (2026) include runtime safety controls, explainability and audit logs for decisioned actions, automated testing and pentesting of agent behaviors, provenance for data and model changes, and integration of governance into CI/CD for agents. Organizations should map tools to responsibilities—model providers, policy enforcement, monitoring, and domain controls—so agents operate within verifiable, auditable boundaries that satisfy both internal risk teams and evolving regulatory standards.