Enterprise / AI policy & control evaluation
Does your AI policy match what your systems allow?
A policy can prohibit an action while an integration still permits it. Compare written expectations with access, configuration and authorized application behavior before expanding AI use.
When to use this service
You have rules. You need to understand their effect.
Your organization has AI-use expectations, or is introducing them. People can already connect assistants to documents, customer records or business workflows. Different teams own the policy, information and integrations.
This evaluation connects AI security governance with control validation . In an agreed situation, does the technical path enforce the intended restriction?
A useful starting question
“Our policy restricts customer information. Can an assistant still retrieve it, send it to another provider, or act on it without the right approval?”
Explore the hypothetical scenario →Illustrative system / not a client architecture
Follow the expectation through the system.
- 01Intent
Policy + ownership
What information, users and actions should be restricted? Who approves exceptions?
- 02Configuration
Identity + permissions
What can the user and connector actually read or change?
- 03Behavior
Authorized scenarios
What happens when requests cross a system or provider boundary?
- 04Decision
Findings + improvements
Which gaps need action, who owns it and what requires follow-up?
Connections and decision points
- Policy → configuration: translate broad rules into specific expectations.
- Configuration → behavior: validate authorized scenarios rather than treating a setting as proof.
- Observation → improvement: record limitations and agree changes or retesting separately.
Assessment scope
Examine the gap between intent and enforcement.
- Policy and responsibility
- Review selected AI-use rules, sensitive-information categories, approvals and third-party obligations with their owners.
- Access and configuration
- Examine supported settings, connector identities , retrieval permissions and allowed tool actions.
- Authorized behavior
- Agree scenarios around restricted retrieval, external processing, prompt injection and approval boundaries. Use permitted targets and approved test information.
Findings and recommendations
Understand what needs attention, and why.
Outputs to agree
- Policy expectations and assessed paths.
- Observed gaps, evidence and testing limitations.
- Improvement priorities and accountable owners.
- Questions requiring further or specialist review.
Work that follows
Implementation and retesting are separately agreed. Findings may lead to narrower permissions, changed controls, revised policy or a decision not to expand a use.
Periodic reviews can revisit the path as providers and business needs change. They are not continuous monitoring.
Explore authorized control improvements →Evaluation process
Agree authority, information handling and test limits.
Approve the scope.
Name systems, owners, third-party permissions, allowed actions, evidence restrictions and stop conditions.
Examine the scenarios.
Compare documents, configurations and behavior. Record where access or coverage limits the conclusion.
Walk through the findings.
Discuss implications and ownership. Approve changes, follow-up testing and future review separately.
Methods and limitations
Technical depth without a certification claim.
NIST AI RMF and relevant OWASP guidance can inform questions. Specific framework mapping and coverage must be agreed; a reference does not establish compliance.
Is this the same as policy development?
No. Governance defines or improves expectations and responsibilities. Evaluation compares selected expectations with system configurations and behavior. Findings can inform policy revisions.
Is this a complete application security test?
No. Evaluation focuses on agreed policy and enforcement questions. Broader testing, source review, remediation and exhaustive coverage are not automatic inclusions.
Related pages
Continue the conversation.
Security policies & governance
Develop scoped security and AI-use policy guidance with named owners, review responsibilities, and practical implementation considerations.
Explore serviceAI access & workflow controls
Scope AI access restrictions and workflow hardening around supported platforms, data paths, tool permissions, and authorized configuration changes.
Explore serviceAI application testing
Evaluate agreed AI application and workflow scenarios, understand findings in context, and identify practical remediation priorities.
Explore Hypothetical use caseWhen AI policy meets connected systems
Explore a hypothetical internal AI assistant connecting customer records, documents, and an external provider, with conflicting policy and access boundaries.
ExploreDiscuss your needs
A useful next step starts with your environment.
Discuss the decision, systems, and boundaries that matter. We can establish what work is appropriate before making commitments.