Shadow AI Has No Owner
AI tools, extensions, copilots, CLIs, and workflows are spreading without visibility.
Buyer fear
We do not know where AI is being used, what data goes into it, or who owns the risk.
Primary service
AI Security Maturity Benchmark
Supporting services
Best for
Why This Matters
The business and security pressure.
Unowned AI usage becomes a policy, privacy, and incident-response problem fast. Inventory is the first control.
Review Surfaces
Systems and surfaces in scope.
Listed surfaces are common review targets, not partnership, certification, or endorsement claims. Marketplace readiness support does not replace official review.
Common Failure Modes
What usually breaks.
AI is embedded in extensions or scripts nobody owns
Vendor lists are incomplete
Logs do not show what data went where
Policy is written but no one can enforce it
What We Do
The work mapped to the service path.
Inventory AI surfaces, model calls, vendors, agents, RAG paths, and data flows
Find unowned or undocumented AI usage
Map policy gaps to owners and controls
Create a 30/60/90 risk roadmap
Workbench Instruments
Products used to deliver or demonstrate the work.
Deliverables Produced
Artifacts buyers can inspect.
AI Surface Inventory
Shadow AI Register
Model / Vendor Usage Map
Control Coverage Snapshot
30/60/90 Risk Roadmap
What Good Looks Like
Concrete outcomes.
Every surface has an owner
Data paths are visible
Control gaps are ranked
The next remediation step is clear
Related services
Related research
Caveat
Based on analyzed job-description signals and scoped engagement evidence, not proof of any individual company's internal security maturity.
Turn this brief into scoped work.
The CTA follows the primary service path so the next step is commercially clear.