A Shadow AI Audit finds where employees use AI tools without clear approval, policy, or oversight. The goal is visibility: approved versus unapproved tools, data sensitivity, department risk, and a practical action plan.
Readiness scope
Shadow AI is unmanaged AI usage inside the company. It can be well-intentioned: employees use ChatGPT, Copilot, Gemini, Claude, AI writing tools, browser extensions, automation platforms, or personal accounts to move faster. The risk is that sensitive data and business decisions may move outside controlled systems.
You receive a shadow AI heat map, risk register, data sensitivity view, approved/unapproved tools list, immediate control actions, and an AI usage action plan that can feed into broader AI policy and NIS2 readiness work.
Shadow AI heat map
Department risk map
AI tool inventory
Data sensitivity scoring
Risk register
Approved tool recommendations
Action plan
These external resources are included so buyers can validate the regulatory and AI-risk basis directly. They do not imply endorsement or certification.
Shadow AI is AI tool usage that happens without clear approval, governance, security review, or visibility.
It can expose client data, personal data, confidential business information, code, contracts, and decisions to tools or accounts that were not reviewed.
We combine intake, staff survey, stakeholder interviews, tool inventory, workflow review, and evidence checks.
Yes, when included in scope. Interviews help distinguish useful AI adoption from risky behavior.
It can be designed to use anonymous survey inputs where that improves honesty and organizational trust. Final reporting focuses on risk patterns, not blame.
A heat map, risk register, department-level findings, approved/unapproved tool view, and action plan.
Start with a scope review. We will identify the highest-risk systems, AI workflows, evidence gaps, and the fastest practical path to a useful readiness report.