6 Ways to Prevent Leaking Private Data Through Public AI Tools

Public AI tools like ChatGPT, Gemini, and Copilot have quickly become part of everyday work. They’re excellent for brainstorming ideas, drafting emails, creating marketing content, and summarising non-sensitive information in seconds.

However, when these tools are used carelessly, they can pose a serious risk to businesses that handle personally identifiable information (PII), confidential customer data, or proprietary business knowledge.

Most public AI platforms retain user inputs to help train and improve their models. That means a single prompt containing sensitive data could expose client information, internal strategies, or intellectual property. For business owners and managers, preventing AI-related data leakage is no longer optional, it’s a core security responsibility.

AI adoption is essential for productivity and competitiveness, but the consequences of getting it wrong can be severe. A data leak caused by improper AI usage can lead to:

A real-world example came in 2023 when Samsung experienced multiple internal data leaks after employees pasted confidential information into ChatGPT. This included source code and internal meeting data, which was retained by the public AI model. The issue wasn’t a cyberattack, it was human error combined with a lack of clear policies and technical controls. Samsung ultimately responded by banning generative AI tools internally.

The lesson is clear: without guardrails, even well-intentioned AI use can become a liability.

Your first line of defence is a formal AI policy. This should clearly define:

This policy should be introduced during onboarding and reinforced regularly. Removing ambiguity helps employees make safe decisions and sets clear expectations.

Free or consumer AI tools often include terms that allow user data to be retained for model training. Business-grade options such as ChatGPT Team or Enterprise, Microsoft Copilot for Microsoft 365, or Google Workspace AI offer contractual assurances that customer data is not used to train public models.

These platforms provide an essential legal and technical boundary between your business data and the wider internet. You’re not just paying for features, you’re paying for privacy, compliance, and control.

Even with good policies, mistakes happen. Data Loss Prevention solutions add a critical safety net by detecting and blocking sensitive information before it leaves your environment.

Tools such as Microsoft Purview and Cloudflare DLP can:

This prevents accidental data exposure and gives IT teams visibility into AI usage risks.

Policies alone are not enough. Employees need practical, hands-on training to understand how to use AI safely in their day-to-day roles.

Interactive training sessions help teams learn how to:

Well-trained staff become an active part of your security strategy rather than a weak point.

Security controls only work if they’re monitored. Business AI platforms provide audit logs and admin dashboards, these should be reviewed regularly.

Audits help identify:

The goal isn’t blame, but continuous improvement and early intervention.

Technology and policies are only effective when supported by the right culture. Leaders should model safe AI behaviour and encourage open conversations about security.

When employees feel comfortable asking questions or raising concerns, security becomes a shared responsibility. This collective awareness is often your strongest defence against data leaks.

AI is no longer optional, it’s a powerful tool for improving efficiency and competitiveness. That makes safe and responsible AI use a business-critical priority.

By putting the right policies, controls, and training in place, you can confidently embrace AI while protecting your most valuable data.

If you’d like help creating an AI usage policy, implementing DLP controls, or reviewing your current setup, Netserve can help. Get in touch to ensure your business is using AI securely and compliantly.