Why AI Needs Governance Now
AI changes your risk picture in three ways:
- Data leaves through new channels. Employees paste customer records, contracts, source code, or controlled information into tools your company never approved. This unsanctioned use is often called shadow AI.
- Customers and auditors are asking. Security questionnaires now include AI sections: which AI tools you use, whether customer data trains models, and who approves new AI use. “We don’t have a policy” loses deals.
- Agents can act, not just answer. An AI agent with access to email, files, or business systems can be manipulated by the content it reads into taking actions nobody intended. Permissions and oversight matter more than the model itself.
Governance doesn’t mean slowing down. It means deciding — on purpose — which AI uses are approved, what data they may touch, and who is accountable.
What We Do
AI Use Inventory (Shadow AI Discovery)
We identify the AI tools and AI-enabled features in use across your organization — sanctioned and unsanctioned — using interviews, a short staff survey, and a review of your software inventory, SaaS settings, and identity provider. You get a register of AI use, the data each tool touches, and the vendor’s data retention and training terms.
AI Risk Assessment
A structured assessment of the risks your AI use creates: data exposure, regulatory and contractual obligations (including CUI and health information), vendor risk, accuracy and decision-making risk, and the security of AI applications you’ve built or deployed. Findings are prioritized and recorded in a risk register aligned with the NIST AI Risk Management Framework.
AI Acceptable Use Policy & Governance Model
A practical AI acceptable use policy your staff can follow, plus the governance around it: an approved-tools list, a lightweight intake process for new AI use cases, data handling rules by classification, roles and accountability, and how AI risk is reported to leadership.
Secure Design Review for LLM & Agentic Applications
Before you launch an AI assistant, retrieval-augmented chatbot, or AI agent, we review its architecture and design: data flows, identities and permissions, tool access, guardrails, logging, and human oversight. We assess the design against the OWASP Top 10 for LLM Applications and the OWASP Top 10 for Agentic Applications and give your developers specific, prioritized design recommendations.
NIST AI RMF & ISO/IEC 42001 Readiness
For organizations that need a recognized framework — often because a customer requires one — we map your current practices to the NIST AI RMF or ISO/IEC 42001, the international standard for AI management systems, identify gaps, and build the policies and processes to close them. For ISO/IEC 42001, we prepare you for audit; certification itself is issued by an independent, accredited certification body.
What We Review in AI and Agent Designs
Our design reviews focus on the risks the OWASP projects identify as most significant for AI applications, including:
| Risk area | What we look for |
|---|---|
| Prompt injection & goal hijacking | Can instructions hidden in documents, emails, web pages, or tool outputs redirect what the model or agent does? |
| Sensitive information disclosure | Can the system reveal data a user shouldn’t see — through retrieval, memory, logs, or the system prompt? |
| Excessive agency & tool misuse | Does the agent have more permissions, tools, or autonomy than its task requires? Are high-impact actions confirmed by a human? |
| Identity & privilege | Which identity does the agent act as? Are credentials scoped, short-lived, and auditable? |
| Supply chain | Which models, plugins, MCP servers, and data sources does the system depend on, and who controls them? |
| Memory & context poisoning | Can stored memory or retrieved content be manipulated to influence later decisions? |
| Output handling | Is model output treated as untrusted before it reaches code, queries, or other systems? |
| Oversight & logging | Can you reconstruct what the system did and why, and stop it if needed? |
How AI Governance Engagements Work
- Consultation (30 minutes, free). How your organization uses AI today, what your customers and contracts require, and what you’re planning to build or buy.
- Scoped proposal. Fixed scope, deliverables, and timeline — usually within one business day.
- Discover and assess. AI use inventory, stakeholder interviews, and review of existing policies, vendors, and AI application designs.
- Deliver. Risk register, prioritized recommendations, policy set, and design review findings, walked through with your leadership and technical team.
- Ongoing (optional). AI governance can be folded into a vCISO engagement so new AI tools and use cases are reviewed as they come up.
Who This Is For
- Growing companies fielding AI questions in customer security questionnaires.
- Defense contractors that must keep CUI out of AI tools not approved for it.
- Healthcare-adjacent and professional services firms handling sensitive client data.
- Teams building AI assistants or agents that want a security review before launch.
If you want help building AI tools or automation, see our Secure AI Solutions service.
Why USCIBER
- Security and compliance first. AI governance is an extension of the risk management, policy, and compliance work we already do for CMMC, ISO 27001, and compliance services clients — not a separate silo.
- Senior leadership. Engagements are led by security leadership holding CISSP, CISA, and CISM credentials.
- Framework-aligned. Findings map to the NIST AI RMF, ISO/IEC 42001, and OWASP guidance, so they hold up with customers and auditors. See all the frameworks we support.
- Practical for small teams. Policies and processes sized to how your organization actually works.
Frequently Asked Questions
What is AI governance?
AI governance is the set of policies, roles, and processes an organization uses to decide which AI uses are allowed, manage their risks, and stay accountable for outcomes. For most small and mid-sized organizations, it starts with an inventory of AI use, an acceptable use policy, and a simple approval process for new AI tools.
What is shadow AI?
Shadow AI is the use of AI tools or AI features that the organization hasn’t approved or doesn’t know about — for example, staff pasting customer data into a personal chatbot account. It creates data exposure and compliance risk because no one has reviewed the tool’s data handling.
Do we need an AI acceptable use policy?
If your employees use AI tools — and most do — yes. A policy tells staff which tools are approved, what data must never be entered, and when human review is required. It is also one of the first things customers ask about in security questionnaires.
What is agentic AI security?
Agentic AI security is protecting AI systems that can take actions — calling tools, sending messages, changing data — rather than only generating text. The main risks are attackers redirecting the agent through content it reads, agents holding more permissions than they need, and actions that no one reviews. The OWASP Top 10 for Agentic Applications catalogs these risks.
What’s the difference between the NIST AI RMF and ISO/IEC 42001?
The NIST AI Risk Management Framework is voluntary U.S. guidance organized around four functions — Govern, Map, Measure, and Manage. ISO/IEC 42001 is an international standard for an AI management system that organizations can be certified against by an accredited certification body. Many organizations use the NIST AI RMF to structure risk work and ISO/IEC 42001 when a customer requires certification.
Can you certify us to ISO/IEC 42001?
No. USCIBER helps you prepare — gap analysis, policies, risk processes, and audit readiness. Certification is issued by an independent, accredited certification body.
Can we use AI tools if we handle CUI?
Only tools and hosting environments that meet your contractual safeguarding requirements. Many consumer and standard business AI tools are not appropriate for CUI. We help you classify your data, set rules, and identify appropriate options.
Put Guardrails Around Your AI Use
Book a 30-minute consultation. We’ll discuss how your team uses AI today, what your customers expect, and the right first step — then send a scoped proposal.