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

Who, what or how it is authorized to act. Both data permissions and runtime guardrails must bind to an identity. That makes identity the primary control plan on which the other two operate.

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

AI Strategic & Advisory Services

Help organizations assess AI readiness, plan, build and optimize AI-ready cybersecurity programs to support AI initiatives.

Data & AI Governance Services

Expertise to build and maintain a program to secure data & govern AI at scale & maintain security & compliance with AI adoption.

Architecture, Tooling and Evaluation

Structured comparison & proof-of-value testing for solutions against business & functional requirements, integration constraints and plans

AI Technical Services (Implement & Deploy)

Vendor-objective support to find, deploy and optimize right-fit AI solutions and align outcomes to your unique business priorities and risk tolerances.

AI Platform Security

Find shadow AI, SaaS tools, agents, identity workflows and MCPs. Secure MLOps and 3rd party model scans.

Identity and Access Management

Strategic and tactical services to secure AI agents/NHIs and support AI and Agentic AI program automation and governance.

Managed AI Security Services

Ongoing agent lifecycle management & monitoring, policy tuning and platform operations that evolve with your business, agent population and regulatory landscape.

Cloud Security for AI

Assess, design and build security into cloud native AI/ML platforms so organizations can scale AI securely and interconnect agents through cloud-hosted gateways.

Risk Management and TPRM

Risk management & mitigation from AI adoption and assess risk introduced by third-party agents, plugins, tools and model providers across your environment.

Application Security

Identify potential flaws, threats & vulnerabilities within AI apps, development practices and deployment pipelines and red team/ adversary testing.

Red Teaming & Adversarial Testing

Understand how adversaries will target agents with proactive, offensive testing of agent deployments targeting your unique attack surface introduced by agentic systems.

Incident Response and Forensics

Development & operationalization of AI-specific incident response capabilities and playbooks to include containment, forensic analysis, tools, evidence preservation.

Compliance and Regulatory Alignment

Ensure compliance with evolving regulatory frameworks (e.g., EU AI Act, NIST AI RMF, ISO 42001) and sector-specific 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.