AI tools like ChatGPT and similar assistants have become genuinely useful for everyday work—drafting emails, summarizing documents, brainstorming ideas. But there’s a catch worth understanding: most public AI tools can use your inputs to train their models.
That means if someone on your team pastes confidential client information or proprietary code into a public AI chat, that data might become part of the model’s training data. It’s not malicious—it’s just how many of these services work by default.
This isn’t a reason to avoid AI entirely. It’s a reason to use it thoughtfully. Here are six practical ways to get the productivity benefits while keeping sensitive information where it belongs.
A Real-World Example
In 2023, Samsung discovered that employees in their semiconductor division had accidentally leaked confidential source code and meeting notes by pasting them into ChatGPT. The data was retained for model training. Samsung’s response was a company-wide ban on generative AI tools—which solved the immediate problem but also eliminated the productivity benefits.
A better approach is to set clear guidelines and technical guardrails so your team can use AI safely.
1. Create a Clear AI Usage Policy
Start with the basics: define what can and can’t go into public AI tools. Your policy should specify:
- What counts as confidential information (client data, financial records, proprietary processes, etc.)
- Which types of tasks are appropriate for AI assistance
- What the consequences are for non-compliance
This removes ambiguity. People generally want to do the right thing—they just need to know what the right thing is.
2. Use Business-Tier AI Accounts
Free versions of AI tools typically use your inputs for training. Business tiers—like ChatGPT Team or Enterprise, Microsoft Copilot for Microsoft 365, or Google Workspace AI—usually include contractual guarantees that your data won’t be used for model training.
The upgrade cost is minimal compared to the value of keeping your business data private. Check the specific terms for any tool you’re considering.
3. Implement Data Loss Prevention Tools
Data Loss Prevention (DLP) solutions can catch sensitive information before it leaves your network. Tools like Microsoft Purview or Cloudflare DLP can:
- Scan content being uploaded to AI platforms in real time
- Block or redact information that matches patterns (credit card numbers, Social Security numbers, etc.)
- Alert administrators to potential policy violations
This creates a safety net for the human errors that are bound to happen.
4. Train Your Team on Safe Prompting
Interactive training beats a memo every time. Show your team how to:
- Anonymize data before using it in prompts (replace real names with placeholders, remove identifying details)
- Ask AI for help with the structure of a document rather than pasting the actual content
- Recognize when a task involves information that shouldn’t leave your systems
Hands-on practice with realistic scenarios makes the guidelines stick.
5. Monitor AI Tool Usage
If you’re using business-tier AI tools, you likely have access to admin dashboards and usage logs. Review them periodically to:
- Identify unusual patterns that might indicate policy violations
- Spot training gaps (if one department is making more mistakes, they might need additional guidance)
- Verify that your technical controls are working as intended
This isn’t about surveillance—it’s about catching problems early and improving your processes.
6. Build a Culture of Thoughtful AI Use
The most effective control is a team that understands why this matters and takes ownership of data protection. Leaders should model good practices, encourage questions, and make it safe to admit mistakes.
When people understand the stakes—reputation, client trust, regulatory compliance—they’re more likely to pause before pasting.
The Bottom Line
AI tools are here to stay, and they offer real value. The goal isn’t to avoid them—it’s to use them in ways that don’t create new risks for your business.
A clear policy, the right tools, and some practical training can give you the best of both worlds: productivity gains without data exposure.
Need help creating AI usage guidelines for your team? We can help you think through the policy and technical controls that make sense for your situation. Let’s talk.
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