AI Use
Tools, models, applications, APIs, and agents in use across the organization.
AI Governance & Security Assessment
Understand your AI environment before it becomes your blind spot.
Establish what AI is in use, what information it touches, who owns it, where material gaps exist, and what leadership should address first.
What we evaluate
A cross-functional view of the environment.
Data
The company, customer, regulated, and sensitive information processed by AI systems.
Access
Systems, permissions, integrations, identities, and actions available to AI applications.
Governance
Who approves, owns, reviews, documents, and oversees AI use.
Vendors
Third parties, embedded capabilities, and upstream dependencies that introduce AI risk.
Security
Architecture, application, data, model, and control gaps that affect the environment.
Workforce
How employees use public and internal AI tools in day-to-day work.
Readiness
Whether the organization can identify, escalate, and respond to an AI-related incident.
Assessment process
Focused, evidence-led, practical.
Discovery
Align on scope and establish a baseline of known AI use, policies, vendors, and evidence.
Stakeholder Interviews
Understand adoption, ownership, workflows, concerns, and control practices across functions.
Environment Review
Examine relevant systems, data flows, access paths, vendor relationships, and governance processes.
Risk Analysis
Evaluate material exposure, control maturity, and priorities in business context.
Executive Roadmap
Deliver findings, a prioritized remediation plan, and an executive working session.
Outputs leaders can act on.
Deliverables are tailored to scope and maturity, with clear distinctions between observations, risk judgments, and recommendations.
- AI inventory
- Use-case classification
- AI risk register
- Vendor findings
- Policy findings
- Security observations
- Governance maturity findings
- Prioritized recommendations
- Executive report