---
title: "Shadow AI: Staff Already Use It, Pretending Otherwise Is the Real Risk"
description: "Source code pasted into chatbots, customer data in prompts, personal accounts used for work: how to govern shadow AI without banning it. Policy and tools."
url: https://csidia.com/en/notes/shadow-ai-governare-non-vietare/
lang: en
date: 2026-02-05
label: "Governance"
publisher: CSIDIA S.r.l. (https://csidia.com/)
italiano: https://csidia.com/note-operative/shadow-ai-governare-non-vietare/
---

# Shadow AI: Staff Already Use It, Pretending Otherwise Is the Real Risk

The **Samsung** case became a textbook example in 2023: semiconductor engineers pasted confidential source code and internal meeting minutes into ChatGPT to get help with their work, and the company — once it found out — banned external chatbots outright. Three years on, the evidence converges on one point: in most organisations, **more than half of those who use AI at work do so with unauthorised personal tools**, and largely without declaring it. It's called shadow AI, and the paradox is that companies with an outright ban have *more* of it, not less: the ban simply shifts usage onto personal phones, where no corporate control can reach.

## Why the Ban Doesn't Work

Someone who pastes a contract into a chatbot doesn't want to harm the company: they want to finish a tedious task sooner. Generic AI delivers an immediately perceptible time saving, and no internal memo competes with that. A ban produces three effects, all of them negative: usage continues, but invisibly; data still leaves the building, but towards consumer accounts with no guarantees whatsoever; and the company gives up the chance to understand *which* tasks its staff are actually trying to automate — which is the single most valuable piece of information there is, a free map of inefficient processes.

## What Actually Leaves, and Where It Ends Up

The concrete risk needs to be understood without hysteria. On free **consumer** accounts, the content entered can be used to train the models and is retained under terms you never negotiated. On **enterprise** accounts, as a rule, data is not used for training and contractual and data-residency guarantees apply. The difference between the two worlds is enormous — and it is exactly the difference that shadow AI erases: the employee using their own account applies the lowest level of guarantees available to the most sensitive data they have to hand.

## Governing It in Four Moves

1. **Offer the alternative before regulating.** A policy without an authorised tool is a ban in disguise. What's needed is corporate access to an AI assistant with adequate guarantees (no training on your data, logging, European data residency) — or, for more serious cases, an internal assistant that works [on connected company data](https://csidia.com/en/platform), where answers are grounded and traceable.
2. **A short policy, organised by data category.** One page, not thirty: what can be entered into authorised external tools (public information, text to be reworded), and what never can (personal data belonging to customers and colleagues, code, prices, contracts, know-how). People remember three rules, not an entire regulation.
3. **Provide training — now also a legal obligation.** Under the EU AI Act, anyone using AI systems at work must be trained in how to use them (the AI-literacy obligation has been in force since February 2025). Do it properly: half an hour on how to write a prompt without confidential data prevents more incidents than any firewall.
4. **Measure and update.** Traffic towards AI services can be observed at network level; requests for new tools should be welcomed as a signal, not dismissed as a nuisance. Every instance of shadow AI is a request for automation that the company hasn't yet listened to.

## The Useful Reversal

The last move is the most profitable one: treat the shadow-AI map as an **automation backlog**. If half the procurement office is pasting orders into a chatbot to extract data, that's a process crying out to be properly automated — with system grounding, controls and traceability. This is often how our [operational trials](https://csidia.com/en/approach) come about: not from a strategic plan, but from what people were already trying to do on the quiet.

*Want to turn shadow AI from a risk into a map? [Let's talk](https://csidia.com/en/contact): half an hour to set policy and priorities.*

## Sources

- [Bloomberg — the Samsung ban after the code leak (2023)](https://www.bloomberg.com/news/articles/2023-05-02/samsung-bans-chatgpt-and-other-generative-ai-use-by-staff-after-leak)
- [EU AI Act, Article 4 — AI-literacy obligation (EUR-Lex)](https://eur-lex.europa.eu/eli/reg/2024/1689/oj)

Note by CSIDIA S.r.l. (Vignola, MO, Italy): https://csidia.com/en/notes/shadow-ai-governare-non-vietare/ · Who we are and what we do: https://csidia.com/en/at-a-glance/ · engagement@csidia.com