5 Non-Negotiable Rules to Prevent Employee Leaks of Client PII via Public AI Tools

What happens when someone on your team pastes sensitive client information into ChatGPT to “just make things quicker”? According to TechRadar, 82% of AI-related data exposure incidents involved personal, unmanaged AI accounts. 20% of uploaded files to these tools included sensitive corporate data, according to Axios.

As generative AI becomes a go-to productivity tool, employees may unknowingly put sensitive personally identifiable information (PII) at risk. When that activity involves your client’s private information, it’s a data and credibility breach. 

This blog explores five practical, enforceable rules that your organization can implement today to protect client data while still embracing AI’s potential.

Why the Risk Keeps Growing

AI is outpacing internal policies, and employees often don’t wait for formal approval. They just want to get their work done.

The problem is that casual copy-paste into ChatGPT or a similar tool might involve names, addresses, invoices, or case notes. None of that belongs to a public model, yet it happens because employees think that using generative AI is safe or they assume no one will notice.

Nearly 60% of data breaches still begin with people, according to Verizon. AI adds a new dimension. IBM’s breach report revealed AI-specific incidents cost companies roughly $670,000 more than typical breaches, and they now make up 20% of all tracked incidents.

5 Rules to Stop PII Leaks to Public AI

These rules are about giving people structure that works. Clear guidance, firm boundaries, and the right tools let your team use AI without compromising client trust.

1. Identify Sensitive Data and Set a Hard Boundary

Be clear on what is off-limits. Client records, personal contact information, legal documents, and billing information should be tagged and secured. 

Define what data qualifies as sensitive, and then put up real guardrails. Create internal tags, set access rules, and make it clear that this kind of data never belongs in a public AI prompt. 

Next, implement controls. Use flags, automated reminders, and policy-based restrictions built into your systems. Like any effective layered defense, it’s not a single rule that protects you, it’s all of them working together quietly in the background.

2. Give People a Better Option Than Shadow AI

If AI is banned outright, employees won’t stop using it. They’ll just hide it.

That’s why the next rule focuses on empowering users. Provide a company-approved AI platform such as Microsoft Copilot, Azure OpenAI, or another system connected to your identity provider. Make your approved AI tool easy to access, fast to use, and secure by design.

By funneling usage into a controlled environment, you avoid most of the risk tied to unapproved platforms. This also allows you to wrap policy into the tool itself, warnings before submitting prompts, redaction prompts, or automated reminders not to input PII.

One of the benefits of cybersecurity investments is that they give your team tools that actually help them stay secure, without slowing them down. 

3. Control the Gateways With DLP, CASB, and Isolation

Even with rules in place, people make mistakes. That’s where technical controls help. Tools like Data Loss Prevention (DLP),  monitor for sensitive information, such as client IDs or Social Security numbers, before it leaves your network. Instead of relying on memory, these guardrails work quietly in the background, catching risky behavior before it becomes a real problem.

Pair DLP with a cloud access security broker (CASB) that can block or limit access to non-approved AI sites. You can also isolate risky browser sessions, reducing the chance of data being leaked through casual web use.

The same logic applies to network segmentation strategies, where containment often matters more than detection. 

4. Log AI Activity, and Tie It to the User Identity

If something goes wrong, could you trace it?

Logging is often the missing link. Every time someone accesses an AI tool, approved or not, it should be tied to a corporate identity, and verified through SSO and MFA. The prompts they submit, the data they enter, and the tools they use should all be tracked.

This doesn’t mean monitoring every keystroke, but it does mean maintaining records, keeping audit trails, and using security analytics to flag unusual activity.

Without visibility, you have no defense. With visibility, you can investigate, correct, and improve. CISA guidelines highlight the importance of monitoring, logging, and timely response, a priority that becomes even more critical as AI usage expands across teams.

5. Train, Remind, and Simulate

The fifth rule is simple, repetition.

Security training should be an ongoing conversation. Every employee needs to understand how public AI works, where data goes, and what can and cannot be entered into these tools.

Real-world examples make the lessons stick. Incorporate scenarios into your sessions, such as:

• “This intake form needs summarizing. Should I send it to Gemini?”
• “Can I rephrase a client’s support ticket using a chatbot?”

Test your team with AI-specific simulations, like prompt injection attempts or fake AI platforms. Teach them how to recognize red flags and when to seek guidance.

Micro-trainings are effective because they meet employees where they work, focusing on real tasks rather than abstract threats.

Time to Make the Rules Real

Putting AI usage rules into practice takes consistency. Start by labeling the data that needs protection, provide a secure AI tool that employees actually want to use, and back it up with smart controls that catch what people might miss. Make every action traceable, and reinforce it all with short, relevant, and repeatable training. When your systems support your team, security stops being a guessing game.

At Unbound Digital, we help companies bring structure to AI tools. Whether you’re building policies from scratch or enhancing current protections, we’ll guide your team through the process, from strategy to deployment. Our approach focuses on layered security that meets people where they work, without slowing them down.

Let’s make sure your data stays in the right hands. Reach out to us today to start building a secure, AI-ready framework.