6 Practical Ways to Stop Data Leaks Through AI

Public AI tools can simplify daily work. They help with brainstorming, writing emails, creating marketing content, and summarizing information that isn’t sensitive. Tools like ChatGPT and Gemini help you work faster.

However, this convenience also brings real risks, especially for businesses handling customer personal information or confidential data.

Many public AI platforms use your input to train their models. So, if an employee enters client details, internal plans, or proprietary code, that information could be stored or reused. One careless prompt can turn a helpful tool into a serious data leak. Preventing these leaks is now essential for businesses.

Protecting Your Finances and Your Reputation

AI is important for staying competitive, but using it unsafely can be costly. One data leak from improper AI use can result in fines, lost customer trust, and lasting damage to your brand. Preventing leaks is usually cheaper than fixing them.

A real-world example highlights this risk. In 2023, Samsung employees accidentally shared confidential semiconductor source code and internal meeting data by pasting it into ChatGPT. The issue was not a cyberattack, but human error and missing safeguards. Samsung responded by temporarily limiting the use of generative AI tools across the company to prevent more leaks.

This incident shows why clear rules and technical protections are needed before using AI as part of daily work.

6 Practical Ways to Prevent Data Leaks Through Public AI Tools

Here are six practical ways to use AI safely and still encourage innovation in your business.

1. Create a Clear AI Security Policy

Start with clarity. Your organization needs a written policy that explains exactly how public AI tools may—and may not—be used. Define what qualifies as sensitive or confidential information and explicitly ban entering items such as customer PII, financial records, source code, legal discussions, or product roadmaps into public AI tools.

Share this policy during onboarding and repeat it in regular refresher sessions. Clear rules remove guesswork and help employees see how serious AI-related data risks are.

2. Require Business-Grade AI Accounts

Free AI tools are designed to improve their models, not to protect your business data. This is why it’s important to use enterprise or business versions. Tools like Microsoft Copilot for Microsoft 365 or Google Workspace with AI features offer contracts that guarantee your customer data will not be used to train public models.

These paid versions add important legal and technical protection. You are not just paying for extra features, but also for data privacy assurances that free tools do not provide by default.

3. Use Data Loss Prevention (DLP) for AI Prompts

Even with strong policies, mistakes can still happen. Technology can help here. Data Loss Prevention tools can block sensitive information before it reaches an AI platform.

Solutions like Cloudflare DLP and Microsoft Purview check prompts and uploads in real time. They can block, hide, or flag sensitive data such as credit card numbers, client IDs, or internal project names. This acts as a safety net that catches mistakes immediately.

4. Train Employees Continuously, Not Once

A policy document by itself will not change behavior. Ongoing, practical training is essential. Instead of only giving lectures, hold interactive sessions where employees practice rewriting prompts to remove or hide sensitive details.

This hands-on approach shows people how to use AI safely for real tasks while keeping data protected. It also reminds everyone that security and productivity can go hand in hand.

5. Audit and Review AI Usage Regularly

You can’t protect what you can’t see. Business-tier AI tools typically include admin dashboards and usage logs—use them. Review activity on a regular schedule to spot unusual behavior or repeated policy violations early.

Audits are not meant to blame anyone. They help you find training gaps, unclear policies, or areas where you need more controls before a small problem becomes a serious one.

6. Build a Security-First Culture Around AI

Technology and policies only work if people support them. Leaders should set an example by using AI responsibly and encourage open conversations about data safety. Employees should feel comfortable asking, “Is this okay to share with AI?” without worrying about being punished.

When security becomes a shared responsibility, your workforce becomes your strongest defense against accidental data leaks.

Make Safe AI Use a Core Business Habit

AI is now essential for modern businesses because it brings speed and efficiency. That is why using it responsibly is so important. By following these six strategies, you can get the benefits of AI while keeping your most valuable data safe.

If you want to formalize your AI approach and lower the risk of costly data leaks, expert guidance can help you set up the right policies and controls. Contact us today to take the next step toward secure and confident AI use.