The AI Security Guide

Read the full guide from Token Security, in collaboration with Descope and leading CISOs here: https://secureaiguide.com/?source=nhimg

The enterprise AI adoption wave is moving fast. with 82 percent of large-enterprise executives say they plan to bring AI agents into their operations within the next three years. At the same time, 81 percent of employees are already using AI, often without any approved policies in place. That speed brings risk. Agentic AI is capable of making decisions and taking action across systems which opens up a new, largely ungoverned attack surface powered by Non-Human Identities (NHIs) operating at scale across SaaS platforms, internal systems, and autonomous agents.

The AI Security Guide introduces a four-phase maturity model designed to help CISOs, IT leaders, and security practitioners embed security, governance, and risk mitigation into every stage of enterprise AI adoption. It maps the journey from shadow AI experimentation to fully governed, autonomous AI ecosystems—ensuring innovation does not outpace control.

Without this discipline, enterprises risk:

• Data exposure through uncontrolled AI access to sensitive sources

• Compliance failures due to unmonitored AI decision-making

• Identity sprawl from unmanaged NHIs with excessive privileges

• Opaque behaviors that make attribution and auditing nearly impossible

What the Guide Delivers

• Four-Phase Maturity Model - Progressing from shadow AI discovery to fully governed autonomous AI operations

• Cross-Functional Security Domains - Continuous oversight for IAM, data governance, model lifecycle security, and third-party AI risk

• NHI Governance - Treating every AI agent, copilot, and automation as a first-class identity with unique credentials, scoped permissions, and full auditability

• Practical, Actionable Controls - Just-in-time access, time-bound tokens, impersonation transparency, and secure model context protocols (MCPs)

Why It Matters

• Enterprise-Ready - Tailored for CISOs and security practitioners to align AI adoption with risk tolerance and regulatory obligations.

• Secure-by-Design - Ensures safeguards are integrated from pilot to production—not retrofitted later.

• Visibility and Accountability - Addresses NHI proliferation with identity governance, scoped access, and audit transparency.

• Business-Aligned Security - Allows security teams to safely accelerate AI innovation without compromising trust or control.

Bottom Line

The AI Security Guide offers a timely and comprehensive blueprint for securing Agentic AI. By guiding organizations from early experimentation to full-scale, governed AI deployments, it equips CISOs with strategy, governance, and maturity frameworks needed to safely harness the power of autonomous systems.