---
title: "Shadow AI: legal position, liability and what really helps"
lang: en
type: knowledge
canonical: https://www.arocom.de/en/knowledge/ai/shadow-ai
alternate: https://www.arocom.de/wissen/ki/schatten-ki
author: "Axel Roth"
published: 2026-08-07
last_updated: 2026-09-09
---

# Shadow AI: legal position, liability and what really helps

Shadow AI is the AI variant of shadow IT: staff do work tasks in private AI
accounts because the organisation provides nothing official. Four in ten
companies in Germany reckon with it. The organisation stays responsible,
without a contract, a log or any way to delete, and the management is
personally answerable for it. A ban does not remove the reason. What works
is approved access, a written usage rule and training, in that order.

## Shadow AI: when staff use AI on their own initiative

Somewhere in the building, someone is typing a customer email into an AI
chat right now. The account is private, and the organisation knows nothing
about it. That is exactly what shadow AI is: staff doing work tasks with
AI tools that nobody has approved. The term comes from shadow IT, meaning
programs that employees get hold of behind IT's back. What is new is that
texts and documents leave the building in the process, and that in the
end the organisation is still the one answerable for it.

## How widespread shadow AI is

How often this happens was measured by Bitkom in the summer of 2025, in a
telephone survey of 604 companies with 20 or more employees. The result,
published in October, shows above all a gap: considerably more companies
reckon with private AI accounts than provide one themselves, for instance
through an [AI platform](https://www.arocom.de/en/knowledge/ai/ai-platform).

**42%** assume private AI accounts are in use ([Bitkom, 21 Oct 2025](https://www.bitkom.org/Presse/Presseinformation/Beschaeftigte-nutzen-Schatten-KI))

**26%** provide access of their own ([Bitkom, 21 Oct 2025](https://www.bitkom.org/Presse/Presseinformation/Beschaeftigte-nutzen-Schatten-KI))

**67%** upload company data where AI is banned ([Melbourne and KPMG, 2025](https://kpmg.com/xx/en/our-insights/ai-and-technology/trust-attitudes-and-use-of-ai.html))

## What happens legally

The controller under the GDPR is whoever decides on the purposes and
means of a processing operation (Art. 4(7)). An application is reviewed
because the organisation is filling a post, so the responsibility stays
with the organisation and does not travel with the account.

The processing itself may be lawful under Art. 6 GDPR in an individual
case. Everything else is missing regardless: no contract with the
provider under Art. 28, no entry in the record under Art. 30, no
demonstrable safeguards under Art. 32, and neither access nor erasure is
possible. The steps that belong before an approval are in the article on
[GDPR-compliant AI use](https://www.arocom.de/en/knowledge/ai/gdpr-compliant-ai).

## Who is personally on the hook

Of the managing directors of a GmbH, section 43(1) GmbHG requires "the
care of a prudent businessman", and under section 43(2) they are liable
to the company for the damage that arises from a breach of duty. That
presupposes an attributable loss; for fines and removal from office this
restriction does not apply. In an association, a board member working
unpaid is liable under section 31a(1) BGB only for intent or gross
negligence.

What that care means organisationally was spelled out by the Higher
Regional Court of Nuremberg on 30 March 2022 (case 12 U 1520/19): an
internal structure including a compliance system against legal breaches
by employees. The judgment says nothing about AI, but the standard
applies regardless of the tool. An assessment, not legal advice.

## Who has to be involved inside the organisation

Before the first official seat is handed out, the staff representation
has to be involved. A platform with access logs and usage reporting is
objectively suitable for capturing conduct and performance, and the right
of co-determination hangs on that alone, whether or not anyone intends
to monitor. Which set of rules applies depends on the type of employer.

**Involvement for an AI platform by type of employer. An assessment, not legal advice.**

| Type of employer | Representation and legal basis | Result |
| --- | --- | --- |
| private-sector business | works council, section 87(1) no. 6 BetrVG, information duty under section 90(1) no. 3 | works agreement |
| public body | staff council, section 80(1) no. 21 BPersVG or the state equivalent | service agreement |
| Catholic employer | employee representation, section 36(1) no. 9 MAVO | service agreement, section 38 MAVO |
| Protestant employer | employee representation, section 40 MVG-EKD | service agreement, section 36 MVG-EKD |
| no body at all | no representation internally | a written internal rule adopted by management |

## Why a ban alone is not enough

In 2025 the University of Melbourne and KPMG asked 48,340 employees in 47
countries whether they upload sensitive company data into public AI
tools. The result is surprising: where AI is banned, 67 per cent do, under
a usage rule 56 per cent, and with no policy at all 33 per cent. What is
being compared here, though, is a ban against a policy, not a ban against
an offer of the organisation's own.

A second problem: anyone who has accidentally uploaded a customer file
does not report it if the report is at the same time a breach of the
rules. What a notification under Art. 33 GDPR needs then never arrives.

## What works instead

Three steps, and their order matters.

First an official offer. As long as nothing approved exists, every rule
remains an imposition. For small teams, business plans with a data
processing agreement and a training exclusion are enough. From several
departments upwards an [AI platform](https://www.arocom.de/en/knowledge/ai/ai-platform) with
central user management and logging pays off, for instance
[Langdock](https://www.arocom.de/en/knowledge/ai/langdock).

Then a written usage rule. One page is enough if it says which tools are
approved, which data may go in, and where to report a mistake without
getting into trouble for it.

Finally, [training](https://www.arocom.de/en/services/training). It also satisfies the AI
literacy duty under Art. 4 of the AI Act, in force since 2 February 2025.

## What the approved access then gets used for

Access for which nobody names a task sits idle, and the private accounts
come back. Two tasks to start with: the assistant to management has a
draft set of minutes written from the notes of a meeting and approves it
before it goes into the meeting folder. In fundraising, the call for a
funding programme turns into a comparison: what does the application
require, what is already held, what is missing?

Both of these have long been happening in many places, only in a private
account. An official access point makes them visible, and everything
else builds on that: shared assistants, automation with
[n8n](https://www.arocom.de/en/knowledge/ai/n8n), company knowledge via
[RAG](https://www.arocom.de/en/knowledge/ai/rag). How a rollout runs is set out under
[introducing Langdock](https://www.arocom.de/en/services/langdock).

**Turn shadow AI into governed use?**

arocom records what is in use, sets up approved access and trains the
people involved. For organisations from 10 people upwards, whatever
their legal form.

- [Request a first conversation](https://www.arocom.de/en/services/langdock#kontakt)

### What is shadow AI, and how widespread is it?

Doing work tasks with AI tools that nobody has approved, usually through private accounts. According to Bitkom, 42 per cent of companies reckon with it, and 26 per cent provide access of their own.

### Who is liable when staff use AI on their own initiative?

The organisation first, because the controller under the GDPR is whoever decides on purposes and means. Personally, the managing directors are liable under section 43 GmbHG if an attributable loss arises from a breach of their duty of care.

### Is a ban on AI tools enough?

The data argue against it. In the University of Melbourne and KPMG survey, employees upload sensitive company data most often where AI is banned: 67 per cent against 33 per cent with no policy at all.

### We have no works council. Who do we have to involve?

That depends on the type of employer: public bodies involve the staff council, church employers the employee representation, in each case through a service agreement. Where there is no body at all, a written internal rule adopted by management takes its place.

## Read more

- [AI platform](https://www.arocom.de/en/knowledge/ai/ai-platform): The official route
- [GDPR-compliant AI use](https://www.arocom.de/en/knowledge/ai/gdpr-compliant-ai): The four core questions
- [Langdock](https://www.arocom.de/en/knowledge/ai/langdock): German contracting party
- [RAG: Retrieval-Augmented Generation](https://www.arocom.de/en/knowledge/ai/rag): Connecting company knowledge
- [Are we ready for AI?](https://www.arocom.de/en/ai-readiness): Ten questions as a printable checklist
- [Introducing Langdock](https://www.arocom.de/en/services/langdock): What arocom offers

## External resources

- [Bitkom on shadow AI](https://www.bitkom.org/Presse/Presseinformation/Beschaeftigte-nutzen-Schatten-KI): Press release, October 2025
- [Trust, attitudes and use of AI 2025](https://kpmg.com/xx/en/our-insights/ai-and-technology/trust-attitudes-and-use-of-ai.html): Melbourne and KPMG, 2025
- [Section 87 BetrVG](https://www.gesetze-im-internet.de/betrvg/__87.html): Co-determination of the works council
- [Section 80 BPersVG](https://www.gesetze-im-internet.de/bpersvg_2021/__80.html): Co-determination of the staff council
- [Section 43 GmbHG](https://www.gesetze-im-internet.de/gmbhg/__43.html): Liability of the managing directors
- [arocon](https://arocon.eu): The consulting brand in the arocom family