How to Prevent Leaking Private Data Through Public AI Tools

We all agree that public AI tools are fantastic for general tasks such as brainstorming ideas and working with non-sensitive customer data. They help us draft quick emails, write marketing copy, and even summarise complex reports in seconds. However, despite the efficiency gains, these digital assistants pose serious risks to businesses handling customer Personally Identifiable Information (PII).

Most public AI tools use the data you provide to train and improve their models. This means every prompt entered into a tool like ChatGPT or Gemini could become part of their training data. A single employee mistake could expose client information, internal strategies, or proprietary code and processes. As a business owner or manager, it’s essential to prevent data leakage before it turns into a serious liability.

Financial and Reputational Protection

Integrating AI into your business workflows is essential for staying competitive, but doing it safely is your top priority. The cost of a data leak caused by careless AI use far outweighs the cost of preventive measures. A single employee mistake could expose internal strategies, proprietary code, or sensitive client information. This can lead to devastating financial losses from regulatory fines, loss of competitive advantage, and long-term damage to your company’s reputation.

Consider the real-world example of Samsung back in 2013. Multiple employees at the company’s semiconductor division, in a rush for efficiency, accidentally leaked confidential data by pasting it into ChatGPT. The leaks included source code for new semiconductors and confidential meeting recordings, which were then retained by the public AI model for training. This wasn’t a sophisticated cyberattack; it was human error resulting from a lack of clear policy and technical guardrails. As a result, Samsung implemented a company-wide ban on generative AI tools to prevent future breaches.

6 Prevention Strategies

Here are six practical strategies to secure your interactions with AI tools and build a culture of security awareness.

1. Establish a Clear AI Security Policy

When it comes to something this critical, guesswork won’t cut it. Your first line of defence is a formal policy that clearly outlines how public AI tools should be used. This policy must define what constitutes confidential information and specify which data should never be entered into a public AI model, including client information, financial records, merger discussions, and product roadmaps. Educate your team on this policy during onboarding and reinforce it with quarterly refresher sessions to ensure everyone understands the serious consequences of non-compliance. A clear policy removes ambiguity and establishes firm security standards

2. Mandate the Use of Dedicated Business Accounts

Free, public AI tools often include hidden data-handling terms because their primary goal is improving the model. Upgrading to business tiers such as ChatGPT for Enterprise, or Microsoft CoPilot ements explicitly states that customer data is not used to train models. By contrast, free or Plus versions of ChatGPT use customer data for model training by default, though users can adapt their settings to limit this.

The data privacy guarantees provided by commercial AI vendors, which ensure that your business inputs will not be used to train public models, establish a critical technical and legal barrier between your sensitive information and the open internet. With these business-tier agreements, you’re not just purchasing features; you’re securing robust AI privacy and compliance assurances from the vendor.

3. Implement Data Loss Prevention Solutions with AI Prompt Protection

Human error and intentional misuse are unavoidable. An employee might accidentally paste confidential information into a public AI chat or attempt to upload a document containing sensitive client PII. You can prevent this by implementing data loss prevention (DLP) solutions that stop data leakage at the source. Tools like Cloudflare DLP and Microsoft Purview offer advanced browser-level context analysis, scanning prompts and file uploads in real time before they ever reach the AI platform.

These DLP solutions automatically block data flagged as sensitive or confidential. For unclassified data, they use contextual analysis to redact information that matches predefined patterns, like credit card numbers, project code names, or internal file paths. Together, these safeguards create a safety net that detects, logs, and reports errors before they escalate into serious data breaches.

4. Conduct Continuous Employee Training

Even the most airtight AI use policy is useless if it only sits in a shared folder. Security is an ongoing practice that evolves with advancing threats, and memos or basic compliance training are never enough.

Conduct interactive workshops in which employees practice crafting safe, effective prompts using real-world scenarios from their daily tasks. This hands-on training teaches them to de-identify sensitive data before analysis, turning staff into active participants in data security while still leveraging AI for efficiency.

5. Conduct Regular Audits of AI Tool Usage and Logs

Any security program only works if it’s actively monitored. You need clear visibility into how your teams are using public AI tools. Business-grade tiers provide admin dashboards; make it a habit to review these weekly or monthly. Watch for unusual activity, patterns, or alerts that could signal potential policy violations before they become a problem.

Audits are never about assigning blame; they are about identifying gaps in training or weaknesses in your technology stack. Reviewing logs can help you identify which team or department needs additional guidance or where to refine and close gaps.

6. Cultivate a Culture of Security Mindfulness

Even the best policies and technical controls can fail without a culture that supports them. Business leaders must lead by example, promoting secure AI practices and encouraging employees to ask questions without fear of reprimand.

This cultural shift makes security everyone’s responsibility, fostering collective vigilance that outperforms any single tool. Your team is your strongest line of defence against data breaches.

Microsoft Solutions Partner for Data & AI

At bzb IT, we are a Microsoft Solutions Partner for Data and AI. This means we help organisations adopt AI capabilities within the Microsoft ecosystem securely, compliantly, and well-governed.

Rather than relying on public AI tools, we support businesses using solutions such as Microsoft Copilot and Azure OpenAI, where data remains within your Microsoft tenant and is not used to train public models. This significantly reduces the risk of sensitive information being exposed while still unlocking real productivity gains.

If you are looking to use AI safely across your organisation, we can help you define the right approach, implement the right controls, and ensure AI works for your business rather than against it.

Contact the bzb team today to discuss your next steps.