Shadow AI

What is Shadow AI

Shadow AI is the use of AI tools by employees without the knowledge or approval of the organization. It is the AI equivalent of shadow IT.

Why Shadow AI is a problem

Scale

The extent varies by organisation. Assess actual use through an inventory and staff conversations. Common examples include:

Public chatbots used for work tasks
AI assistants in personal accounts
Unauthorized plugins and extensions
AI features in tools where the user is unaware of the AI component

Risks

Risk	Description	Regulatory impact
Data leakage	Employee inputs company data into a public AI tool	Possible GDPR infringement when personal data is processed; risk of unlawful disclosure of trade secrets
Uncontrolled outputs	AI generates incorrect information used in decision-making	Potential liability for harm under applicable law, depending on the legal basis, harm and causal link
Compliance gap	Organization unaware of AI systems it operates	Relevant obligations may be missed; the specific scope and role require assessment
Security	Phishing and social engineering via AI tools	Risk of a cybersecurity incident; reporting depends on scope, the regulated service and statutory conditions
Reputation	AI generates inappropriate content published under the company brand	PR crisis

Assess legal consequences against the actual data, processing and applicable law. In Czechia, cybersecurity incident reporting is governed in particular by Sections 15–18 of Act No. 264/2025; conditions differ by regime and regulated service. Sources: GDPR, Articles 2, 5 and 32, trade secrets, Articles 2–5 of Directive (EU) 2016/943, Czech Civil Code, Sections 504 and 2910–2914, Czech Cybersecurity Act.

Why employees use Shadow AI

It is not malicious intent — it is an attempt to be productive:

Organization offers no alternative — the employee needs AI, but the company has not approved any
Approval process is slow — it takes months to get a tool “whitelisted”
They don’t know it’s a problem — nobody told them they shouldn’t use public AI
AI is everywhere — AI features appear in tools employees already use

How to address Shadow AI

Step 1: You can’t manage what you don’t know about

Conduct an AI inventory — find out what AI tools employees actually use. Ask, don’t surveil — the goal is to understand reality, not to punish.

Step 2: Offer an alternative

A missing or unsuitable approved alternative can contribute to Shadow AI. Approve and deploy AI tools for the most common use cases:

Tools with assessed contractual and data conditions; an enterprise label alone is insufficient
AI assistants integrated into corporate tools
Sandbox environments for experimentation

Step 3: Set clear rules

AI policy — what is allowed, what is not, what requires approval
Data classification — what data should NEVER go into AI tools
Approval process — fast and transparent (not months)

Step 4: Educate

Employees need to understand why the rules are important — not just what they should or should not do.

Step 5: Monitor continuously

Shadow AI is not a one-time problem — new AI tools appear every week.

Shadow AI as a signal

Shadow AI is not just a threat — it is a signal that employees want to use AI. Organizations that merely ban Shadow AI without offering an alternative will not solve the problem — they will only push it deeper into the shadows.

The right approach: Use Shadow AI as motivation for faster but controlled AI adoption.