Problem Definition
What Is Shadow AI?
The complete definition, why it’s a governance crisis, and why it’s happening right now in your organization
The Definition
Shadow AI is the use of AI tools and services by employees without formal approval, security review, or IT oversight.
It’s called “shadow” because it happens invisibly—outside of procurement processes, vendor management, and governance frameworks. Leadership, IT, compliance, and security teams have no visibility into what AI tools are being used, by whom, for what purposes, or what data is being shared.
Real Examples from Healthcare
Shadow AI isn’t theoretical—it’s happening right now across clinical, administrative, and revenue cycle teams
CLINICAL DOCUMENTATION
Physician using ChatGPT
What they do:
Doctor copies patient notes into ChatGPT to generate discharge summaries, simplify medical jargon for patient education materials, or draft clinical documentation
The Problem:
Patient PHI (names, dates, diagnoses, treatments) sent directly to OpenAI servers
The Risk:
HIPAA violation, no BAA, no audit trail, no control over data use or retention
PATIENT COMMUNICATION
Admin using AI transcription
What they do:
Administrative staff uses free AI transcription tools (Otter.ai, Rev.ai) to document patient phone calls, insurance discussions, and appointment scheduling
The Problem:
Unencrypted PHI stored in third-party cloud services
The Risk:
Data breach exposure, compliance violation, no vendor oversight
REVENUE CYCLE MANAGEMENT
Billing team using AI
What they do:
Billing staff uses Anthropic Claude to draft insurance appeal letters, analyze denial patterns, or generate claim documentation
The Problem:
Patient diagnosis codes, treatment details, and claim information shared with AI model
The Risk:
No BAA, no logging, no ability to demonstrate compliance if audited
Real Examples from Healthcare
Shadow AI isn’t theoretical—it’s happening right now across clinical, administrative, and revenue cycle teams
REVENUE CYCLE MANAGEMENT
Physician using ChatGPT
What they do:
Doctor copies patient notes into ChatGPT to generate discharge summaries, simplify medical jargon for patient education materials, or draft clinical documentation
REVENUE CYCLE MANAGEMENT
Admin using AI transcription
What they do:
Administrative staff uses free AI transcription tools (Otter.ai, Rev.ai) to document patient phone calls, insurance discussions, and appointment scheduling
REVENUE CYCLE MANAGEMENT
Billing team using AI
What they do:
Billing staff uses Anthropic Claude to draft insurance appeal letters, analyze denial patterns, or generate claim documentation
The Problem:
Patient PHI (names, dates, diagnoses, treatments) sent directly to OpenAI servers
The Risk:
HIPAA violation, no BAA, no audit trail, no control over data use or retention
The Problem:
Unencrypted PHI stored in third-party cloud services
The Risk:
Data breach exposure, compliance violation, no vendor oversight
The Problem:
Patient diagnosis codes, treatment details, and claim information shared with AI model
The Risk:
No BAA, no logging, no ability to demonstrate compliance if audited
Why Shadow AI Is Happening
It’s not because staff are reckless. It’s because they’re trying to get work done
AI Tools Are Incredibly Useful
ChatGPT, Claude, and other AI tools genuinely save time and improve work quality. Staff discover them, see immediate value, and start using them—without thinking about compliance.
No Official Alternative Exists
Organizations haven’t provided approved, governed AI tools. Staff need AI to keep up with productivity expectations, so they use what’s available.
Approval Processes Are Too Slow
Organizations haven’t provided approved, governed AI tools. Staff need AI to keep up with productivity expectations, so they use what’s available.
IT Doesn’t Know It’s Happening
These are web-based SaaS tools accessed through personal accounts. They don’t show up in network logs, procurement systems, or vendor management processes.
No Official Alternative Exists
Most employees genuinely don’t realize that pasting patient information into ChatGPT is a HIPAA violation. They see it as using a productivity tool, not exposing PHI.
Why This Is a Governance Crisis
Not just a compliance issue. This is an existential risk for all organizations
You Can’t Govern What You Can’t See
Without visibility into what AI tools are being used, you have no ability to assess risk, enforce policies, or implement controls. You’re flying blind.
Impact: Zero governance posture
PHI Is Already Exposed
Every time staff paste patient information into ChatGPT or Claude, PHI leaves your organization. This has already happened thousands of times.
Impact: Ongoing HIPAA violations
No Audit Trail Exists
If OCR or a state attorney general asks ‘where has patient data been sent?’, you have no answer. You cannot demonstrate compliance or respond to breach investigations.
Impact: Audit failure, regulatory action
Banning AI Doesn’t Work
Organizations that ban AI tools see zero reduction in shadow AI usage. Staff just hide it better. You need governed enablement, not prohibition.
Impact: False sense of security
The Solution: Governed Enablement
You can’t eliminate shadow AI with bans—you eliminate it by providing a better alternative
What Doesn’t Work
Banning AI tools (staff use them anyway)
Policy documents with no enforcement
Quarterly training with no controls
Waiting for ‘the perfect tool’ to evaluate
Ignoring the problem and hoping it goes away
What Works
Discover all shadow AI usage (visibility first)
Provide approved AI tools with automatic PHI protection
Make the governed option easier than shadow tools
Enforce policies through technical controls
Continuous monitoring and enablement
What to Do Next
Assess Your Shadow AI Exposure
Book a free Shadow AI Risk Check to understand what AI tools are being used in your organization, where PHI exposure is happening, and what your governance gaps are.
Learn More About Shadow AI
Explore our other Shadow AI resources to understand how to discover it, why AI bans fail, and what the data shows about shadow AI adoption in healthcare.
