Protecting Company Data When Using AI: 5 Essential Steps

Protecting company data when using AI requires three core habits: using only company-approved platforms, scrubbing every prompt of sensitive information, and verifying all outputs for accuracy. While generative AI tools significantly boost productivity, they introduce risks for data leakage that every employee must actively manage.

When you input information into a public chatbot, you often provide data that the model may use to train future versions of itself. This creates a vulnerability where your internal strategy, client lists, or proprietary code could surface in responses given to other users. Because AI platforms are designed to learn from inputs, the line between helpful assistance and an accidental data breach is thin.

Safeguarding intellectual property is no longer just an IT concern; it is a fundamental part of your professional workflow. By adopting consistent security practices, you can harness the power of these tools without compromising your organization’s assets.

Why AI Tools Pose a Risk to Corporate Data

The primary danger when using generative AI lies in how these models learn. Most public platforms improve by ingesting user inputs, meaning any information typed into a chat window may be stored and used to train future versions of the model. If you paste a draft of a confidential strategy document or proprietary code into a public chatbot, that data could potentially be surfaced in responses provided to users outside your organization.

The Hidden Danger of Shadow AI

Organizations face the growing challenge of Shadow AI, which occurs when employees use unauthorized or third-party tools without IT oversight. These tools often lack enterprise-grade security controls, such as data encryption and access management. When you bypass approved channels, you lose control over how your data is processed and stored.

What Qualifies as Sensitive Data?

To practice effective data privacy, you must recognize what information is sensitive. You should never input the following into public AI platforms:

• Personally Identifiable Information (PII): Names, email addresses, or phone numbers of employees and customers.

• Trade Secrets and Intellectual Property: Unpublished product designs, proprietary algorithms, or internal research notes.

• Financial Records: Unreleased earnings reports, budget spreadsheets, or banking details.

• Client Lists and Contracts: Private communication, non-disclosure agreements, or non-public terms of service.

Step 1: Stick to Your Company’s Approved AI Stack

The most effective way to begin protecting company data when using AI is to restrict your activity to tools vetted by your organization. Many popular platforms offer free, public-facing versions that lack the stringent privacy guarantees required for business. Enterprise-licensed versions, such as Microsoft Copilot, typically include agreements that prohibit the provider from using your input data to train global models. Always consult your IT or security department before signing up for new AI services or browser extensions.

Step 2: Master the Art of Data Sanitization

Before hitting enter, treat your input as if it were being published on a public billboard. Data sanitization is the practice of scrubbing sensitive details from your requests to ensure proprietary information never leaves your secure environment.

The Pre-Prompt Scrubbing Checklist

• Remove Identifiers: Delete specific client names, employee names, or project codenames.

• Generalize Figures: Replace exact revenue numbers or pricing structures with ranges or generic labels.

• Strip Proprietary Context: Remove internal URLs, email addresses, or file paths.

• Apply Data Minimization: Ask yourself if the AI truly needs the specific details provided to complete the task.

For example, instead of pasting a full internal memo, use placeholders like [REVENUE_FIGURE] or [PROJECT_NAME]. This maintains the utility of the AI tool while keeping sensitive information off the provider's servers.

Step 3: Monitor and Report AI-Related Security Incidents

Even with precautions, accidents happen. If you realize you have shared sensitive information with a public AI model, act immediately to notify your security team.

1. Document the incident: Note what information was shared, the tool used, and the time of the event.

2. Contact the security lead: Provide details so they can assess the risk and determine if access logs need to be audited.

3. Stop further input: Cease using the tool until you receive guidance from your security team.

Security is a team effort that relies on a culture of transparency. When organizations treat accidental exposure as a learning opportunity, employees are more likely to report mistakes quickly, preventing minor errors from becoming significant breaches.

As you integrate these technologies into your workflow, treat every prompt as a potential data point. If you are ever uncertain about whether information is safe to share, err on the side of caution and consult your internal security guidelines. Feel free to reach out to our team if you would like to learn more about auditing your current AI workflows for better security.