Description
AI agents do not fail only because the model is weak. They fail because organizations let them act inside environments that were never designed for non-human operators with broad permissions, weak boundaries, and unclear intervention rules. This playbook is about fixing that before deployment becomes incident response.
Enterprise AI Agent Deployment Playbook gives teams a practical control architecture for shipping AI agents into regulated environments. It is written for people who need to answer hard operational questions before an agent goes live: what the agent is allowed to do, how action is bounded, who reviews high-consequence behavior, what evidence must exist at each gate, and how to prove the system was governed before something broke.
Inside the book:
- A deployment framework for bounded action, traceability, release gates, and reviewer-verifiable accountability
- Control design grounded in EU AI Act, NIST AI RMF, GDPR, DORA, and related governance expectations
- Practical guidance for engineering, security, privacy, compliance, and operations teams working on real deployments
If you are moving from AI-agent experimentation to formal deployment, this is the manual for doing it with discipline.
