Shadow AI Problem Awareness
The Shadow AI Crisis in Healthcare
Unauthorized AI usage is happening right now in your organization; creating PHI exposure, compliance risk, and audit failure
What Is Shadow AI?
Unauthorized AI tools being used by staff without IT knowledge, security review, or governance oversight
Clinical Staff Using ChatGPT
Doctors and nurses pasting patient notes into ChatGPT to summarize discharge instructions or generate documentation
Risk: PHI sent to OpenAI servers
Admin Using AI Scribes
Administrative staff uses free AI transcription tools (Otter.ai, Rev.ai) to document patient phone calls, insurance discussions, and appointment scheduling
Risk: PHI sent to OpenAI servers
Revenue Cycle Using Claude
Billing staff uses Anthropic Claude to draft insurance appeal letters, analyze denial patterns, or generate claim documentation
Risk: No BAA, no audit trail
78%
Healthcare workers use AI tools without IT approval
0%
Organizations with visibility into shadow AI usage
100%
Unmanaged PHI exposure risk
Shadow AI Resources
Everything you need to understand, discover, and address shadow AI in healthcare
Problem Definition
What Is Shadow AI?
Complete definition, real examples from healthcare, and why it’s a governance crisis not just an IT problem
Tactical Guide
How to Discover Shadow AI
Practical methods to inventory unauthorized AI usage across your organization
Research & Data
Shadow AI Statistics
Data on adoption rates, PHI exposure, and compliance risks in healthcare
Case Study
The Samsung ChatGPT Incident
Case study: How Samsung’s employees exposed sensitive data and what healthcare can learn
The Governance Gap
What Doesn’t Work
Staff using 5-10 different AI tools without approval
No written policies on AI usage
No logging or audit trail of what’s being sent to AI
IT and security teams completely blind to usage
No BAAs with AI vendors
PHI flowing freely to external models
Consequences
PHI Exposure
Patient data sent to unauthorized third parties with no BAA, no encryption standards, no data residency controls
HIPAA Violations
OCR enforcement actions, multi-million dollar fines, mandatory corrective action plans
Reputational Damage
Loss of patient trust, media coverage, board-level crisis, competitive disadvantage
Audit Failure
Cannot demonstrate to auditors that you know where PHI is going or how AI is being used
Your Governance Partner
Our Governance Framework
Four pillars that eliminate shadow AI risk while enabling safe AI use
Visibility
Complete inventory of who’s using AI, what tools, for what purposes, and what data is being shared
PHI Protection
Automatic detection and cleansing of all 18 HIPAA identifiers before data reaches external AI models
Guardrails
Written policies, approved tool lists, role-based access controls, and acceptable use standards
Monitoring
Written policies, approved tool lists, role-based access controls, and acceptable use standards
From Risk to Governance in 3 Phases
A proven approach from risk assessment to full governance
Phase 1
60 minutes
Shadow AI Risk Check
Structured discovery call to map your shadow AI exposure, identify top risks, and build a governance roadmap
Deliverable: Risk assessment summary + prioritized action plan
Phase 2
6 weeks
6-Week Governance Pilot
Hands-on implementation: inventory your AI usage, deploy PHI protection, establish policies, and create a governed AI workspace
Deliverable: Governance baseline, safe AI access, executive summary, scale roadmap
Phase 3
Continuous
Ongoing Governance-as-a-Service
Ongoing monitoring, policy updates, new tool evaluations, compliance reporting, and enablement support as you scale
Deliverable: Monthly reports, quarterly reviews, continuous compliance
Ready to Eliminate Shadow AI Risk?
Start with a free Shadow AI Risk Check—understand your exposure and get a clear governance roadmap.