---
title: "How to Use AI Safely at Work (Without Exposing Company Secrets)"
description: "5 source-backed AI claims from How to Use AI Safely at Work (Without Exposing Company Secrets), with key statistics, context, and the original AI Adopters…"
url: "https://kbanc.com/claims-library/how-to-use-ai-safely-at-work-without-exposing-company-secrets"
source: "https://aiadopters.club/p/how-to-use-ai-safely-at-work-without"
date: "2025-07-23"
topics: ["strategy", "implementation", "business"]
generated: "2026-08-31"
---

# How to Use AI Safely at Work (Without Exposing Company Secrets)

By Kamil Banc | July 23, 2025

## Claims

1. **Samsung's ChatGPT Leak** (source summary): Samsung engineers pasted proprietary source code into ChatGPT, making the data visible to other users.
2. **McDonald's Chatbot Breach** (source summary): McDonald's AI chatbot exposed 64 million job applicants' personal information because of a weak password.
3. **Widespread AI Data Leakage** (source summary): 68% of organizations experienced data leakage from employee usage of AI tools.
4. **Cheap Training Data Extraction** (source summary): Researchers demonstrated extraction of 10,000 training samples from a model for just $200.
5. **Three-Tier Data Classification** (Kamil's interpretation): Classifying data into Never AI, Restricted AI, and AI-Safe tiers enables safe AI adoption.

## Evidence

### Quote
> "Blanket restrictions create workarounds that are less secure than thoughtful protocols." - Kamil Banc

### Key Statistics
- **68%**: Percentage of organizations that experienced data leakage from employee AI usage, per Security Magazine.
- **99%**: Percentage of companies that expose sensitive data to AI copilots, according to the article's cited reporting.
- **64 million**: Number of job applicants whose personal information was exposed by McDonald's AI chatbot in July 2025.
- **5%**: Increase in publicly reported data compromises this year attributed in part to AI, per the article.

## Context
The article grounds its guidance in documented breaches, including Samsung's source code leak via ChatGPT and McDonald's chatbot exposure of 64 million applicant records, to argue that ad hoc AI usage creates real organizational risk. Kamil Banc's methodology classifies data into three tiers—Never AI, Restricted AI, and AI-Safe—so employees can make fast, defensible decisions instead of relying on blanket bans that push usage underground. Practitioners can operationalize the framework through automated data discovery, masking and tokenization of restricted data, prompt sanitization workflows, and documentation aligned with the NIST AI Risk Management Framework. The author positions disciplined AI security not as compliance theater but as a competitive advantage that builds stakeholder trust and can even become a billable consulting service.

## Source
- Original: [How to Use AI Safely at Work (Without Exposing Company Secrets)](https://aiadopters.club/p/how-to-use-ai-safely-at-work-without)
- Cite: kbanc.com/claims-library/how-to-use-ai-safely-at-work-without-exposing-company-secrets

## Primary Evidence
- [McDonald's AI chatbot exposed 64 million job applicants' personal information](https://tech.co/news/data-breaches-updated-list) (tech.co; supports claim 2)
- [68% of organizations experienced data leakage from employee AI usage](https://www.securitymagazine.com/articles/101773-68-of-organizations-experienced-data-leakage-from-employee-ai-usage) (securitymagazine.com; supports claim 3)