Serious Managers Guide to AI Identity at Scale: OAuth, Tokens, and Governance

AI agents need identities and permissions just like employees, and getting them wrong can cause real damage. This guide shows managers how to govern AI identity at scale with OAuth, tokens, and clear accountability.

On a Tuesday morning, the product team at a mid-sized financial services firm received an alert they did not expect. Their newly deployed AI agent—designed to accelerate proposal generation—had spent the previous night sending draft emails to seventeen external clients. The agent had access to the CRM, the email platform, and a document library. No one had specified what it was authorized to do without review, who could stop it, or what would happen if the boundaries turned out to be wrong.

This book is for managers in that position: technically aware, organizationally savvy, accountable for outcomes, and tasked with turning agentic AI from a promising experiment into a reliable capability the business can trust and scale.

Serious Managers Guide to AI Identity at Scale covers the governance infrastructure that must be built before the pilot launches, not after the first incident. Across nine chapters, you will learn how agentic AI fundamentally changes the governance calculus—agents perceive, plan, execute, and adapt, calling APIs, writing files, sending messages, and triggering workflows with real-world consequences.

You will scope use cases and measure business value with structured evaluation frameworks. You will build governance architecture and policy design that define what agents may do, what requires human review, and what is prohibited. You will conduct risk assessment and threat modeling specific to autonomous systems. You will implement OAuth, token-based identity, and access controls that enforce governance at machine speed.

The book also covers safe development lifecycle and pre-production controls, human oversight roles and accountability structures, monitoring and incident response when agents exceed boundaries, and how to scale governance from first pilot through enterprise-wide deployment without creating bottlenecks.

The lesson is not that agentic AI is dangerous and should be avoided. The lesson is that governance infrastructure needs to be present, documented, and tested before agents reach production.

© 2026 PublishDrive (E-bog): 9781972752258

Udgivelsesdato

E-bog: 1. marts 2026