Agentic AI Security Services

AI agents are moving into critical business workflows. As they gain access to systems, data and decision-making capabilities, they introduce new machine-speed and -scale challenges that traditional cybersecurity programs weren’t designed to address. Gaps include visibility, accountability and governance.

Securely Adopt and Scale Agentic AI

GuidePoint Security helps organizations establish the security controls needed to safely adopt and scale agentic AI, from understanding the data, systems and software agents can access to managing how they operate over time. Our services help:

Prepare for Agentic AI Adoption

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Understand your organization's readiness to adopt AI securely, including the identity, access, trust and governance considerations required before agents are introduced at scale.

Gain Visibility Into AI Agents

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Know what AI agents and shadow AI exist across your environment, what they can access, who owns them and how they operate, so you can identify and address risk before it becomes a problem.

Establish Control and Governance

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Apply the right identity, access, guardrails, monitoring and lifecycle controls to AI agents, helping ensure they operate within defined boundaries and remain accountable as they evolve.

Identity as the Control Plane

It takes three control planes to govern agentic AI, but Identity is emerging as the foundation:

Data

What an agent may see, touch and extract. This includes classifications, entitlements and hard boundaries around sensitive information.

Runtime

What an agent is allowed to do while it’s running. And, what are the guardrails that constrain behavior, approval gates, real-time monitoring and containment to limit blast radius if something goes wrong.

Identity

What an agent may see, touch and extract. This includes classifications, entitlements and hard boundaries around sensitive information.

Governing these identities requires controls designed for how autonomous agents actually operate.

Why GuidePoint for Agentic AI

Agentic AI is creating new opportunities to transform how work gets done. But it also becomes an identity issue, a governance issue and a visibility or detection issue. AI agents can reason, plan, make decisions across enterprise environments and even spawn new agents, without human intervention. They need credentials, permissions and access like human users, but they operate at machine speed. In short: Every agent needs a named human sponsor and managed identity and access management lifecycle.

As a vendor-objective advisor and partner, GuidePoint Security provides full lifecycle support for secure AI adoption, use and defense.

GuidePoint works at the intersection of identity, security and AI to help organizations govern autonomous agents across all three control planes. We integrate agentic AI governance into your existing IAM and NHI programs, building on the controls and architecture you already have rather than creating another silo to manage.

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AI agents are the least-covered identity type.

Bots, RPA and AI agents are secured by only 41.5% of organizations, making them the least-covered non-human identity type in current management programs.

When Agentic AI Becomes a Strategic Priority

No matter where an organization is in its AI maturity journey, GuidePoint Security works with clients to tailor a security to your unique business priorities and risk tolerances. Common challenges we help address include:

AI Agents Operating Without Identity Governance

Autonomous agents are authenticating to production systems, accessing sensitive data and executing actions without provisioning standards, access reviews or deprovisioning. Every ungoverned agent is an identity your security team cannot see, scope or revoke.

No Trust Boundaries for Autonomous Decision-Making

AI agents are making decisions across systems without defined boundaries for what they are authorized to do. When an agent exceeds its intended scope, most organizations have no control framework to detect or constrain the behavior.

Shadow AI and Unauthorized Agent Deployment

Teams are deploying AI agents to solve operational problems without security review or governance oversight, creating downstream dependencies your identity team does not know about. Shadow AI is the new shadow IT and it moves faster.

Credential Sprawl From Agent Proliferation

Every AI agent deployment creates credentials, tokens and service connections that expand your credential surface. Without centralized management, revoking access becomes a cleanup exercise rather than a single governed action.

No Deprovisioning for Compromised or Rogue Agents

When monitoring detects anomalous behavior or scope violations, your team needs to revoke all agent access immediately. Most organizations cannot do this because agent access was never centralized or governed.

Regulatory Uncertainty Around AI Governance

AI governance frameworks are emerging rapidly. The EU AI Act, NIST AI RMF and sector-specific mandates are beginning to require organizations to require that AI systems are inventoried, governed and auditable. The organizations that build governance now will meet compliance requirements without scrambling when enforcement begins.

“This surge in conversations stems from the fact that every AI initiative and project currently underway involves either creating of integrating with AI agents.”

Security Architect, Enterprise IT

Source: IDC White Paper, sponsored by GuidePoint Security, Managing Agentic AI Through the Identity Control Plane: What Organizations Should Look for, #US54897326-WP, September 2026

Practical Governance for AI Systems

Governing agentic AI requires controls that span identity, data and runtime, adapted in recognition that they’re  identities that operate independently and at machine-scale.

GuidePoint helps you build AI governance that is practical, enforceable and scalable:

Establish an AI Identity Inventory

Maintain a living record of all AI identities including which tools are approved, which systems each connects to, what permissions are inherited, what actions are authorized and which team owns each integration.

27%

of organizations have fully automated identity governance

n = 860 (all organizations); Source: IDC Worldwide IAM Security Survey, May 2026 (EU25120009-S), unweighted

Agentic AI Services Across the Lifecycle

650+

Vetted Solutions

400+

in Yearly Savings

95+

Reduction in Security Spend

Strategy and Assessment

Evaluate your organization’s readiness for autonomous AI agent adoption spanning identity governance, trust boundaries, NHI, access controls and operational risk.

Identity and Governance Deployment

Deploy identity and lifecycle controls for AI agents including discovery, classification, provisioning, access governance and deprovisioning. Controls are integrated into your existing IAM and NHI architecture so AI identity governance operates within your current infrastructure rather than alongside it.

Managed Lifecycle Services

Ongoing monitoring, policy management and lifecycle support to help ensure agent identities remain visible, governed and aligned with evolving business and regulatory requirements.

Outcomes

Gain Visibility Into AI Agents

Know exactly what autonomous agents operate in your environment, what they access, what decisions they make and who owns them.

Establish AI Governance

Apply provisioning, least privilege, access reviews and deprovisioning to AI agents with the same rigor you apply to any identity in your environment.

Define and Enforce Trust Boundaries

Ensure every agent operates within a defined scope with detection and enforcement mechanisms for when behavior exceeds authorization.

Enable Immediate Shutdown

Revoke all agent access in a single action, including sessions, credentials and downstream connections, when monitoring detects compromise or scope violations.

Meet Emerging Compliance Requirements

Demonstrate to auditors and regulators that AI agents are inventoried, governed and auditable against emerging frameworks including the EU AI Act and NIST AI RMF.

Scale AI Adoption with Confidence

Grow your AI agent population knowing that governance scales with it rather than creating more ungoverned access with every new deployment.

Your Elite Highly Trained Team

Working with GuidePoint, your organization will be backed by our elite team of highly trained cybersecurity engineers, architects and consultants who come from organizations of all sizes, including Fortune 100 companies, the Department of War and U.S. Intelligence Community.

Why GuidePoint Security?
CISSP
CCSP

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Talk to an AI Security Expert

Whether you are deploying your first AI agents or scaling an existing agent population, our team is ready to help you build governance that keeps pace with adoption.

“GuidePoint Security is basically family. They’re always there when I need them. At the end of the day GuidePoint is always there to help and that’s how they add value.”

Mark Gilman

Security Manager

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Frequently Asked Questions (FAQ)

Other non-human identities execute predefined tasks. AI agents reason, make decisions and take actions autonomously. Governance must account for trust boundaries, scope violations and the ability to shut down an agent that exceeds its authorization. The controls are fundamentally different.

Governance is easier to build before agent populations scale than after. The organizations that establish identity lifecycle controls, trust boundaries and monitoring at the beginning avoid the technical debt and security exposure that come from retrofitting governance onto an ungoverned agent population.

Yes. Our approach integrates AI agent governance into your existing IAM and NHI architecture rather than creating a parallel program. Agent identities are managed through the same lifecycle controls, access policies and monitoring capabilities you apply to every other identity.

Your current state across eight domains including agent discovery, identity lifecycle, trust boundaries, access controls, credential management, monitoring, shutdown capability and regulatory alignment. You receive scored findings and a prioritized roadmap.

A trust boundary defines what an agent is authorized to access, decide and do. Without one, an agent that exceeds its intended scope has no control to detect or constrain the behavior. Trust boundaries are the governance layer between an agent doing its job and an agent becoming a risk.

Your governance program should enable immediate revocation of all agent access in a single action. Sessions, credentials and downstream connections. Our assessment evaluates whether this capability exists and our deployment services build it if it does not.

The EU AI Act, NIST AI RMF and sector-specific frameworks are beginning to require organizations to demonstrate that AI systems are inventoried, governed and auditable. Building governance now positions you ahead of enforcement timelines rather than responding after the fact.