Understand the Fundamental Risk
The core issue with public AI chatbots is that many are designed to learn from the conversations they have. When an employee pastes text into a prompt—be it a chunk of source code, a client's email, or notes from a strategic meeting—that information can
be absorbed by the model. Once sensitive data is entered into a public AI tool, the company loses control over it. This information could potentially be stored, used to train future versions of the AI, or, in a worst-case scenario, be inadvertently revealed to another user in a completely different context. This isn't usually malicious; it's a byproduct of how these powerful systems are built. The convenience of getting a quick summary or a draft of an email can lead to unintentional exposure of proprietary information.
Not All Data Is Equal
The first step toward protection is recognizing what needs protecting. Not every piece of information carries the same level of risk. Organizations and employees should learn to classify data into different categories. Public information, like a press release, is safe to use. Internal data, such as general project plans, requires more caution. Highly sensitive information, however, should never be entered into a public AI tool. This includes personally identifiable information (PII) of customers or employees, protected health information (PHI), financial records, trade secrets, legal documents, and proprietary source code. Creating this mental framework helps employees make smarter, split-second decisions before they copy and paste.
Adopt Safe Prompting Habits
Even when working with non-sensitive data, good habits are crucial. The key is to sanitize and generalize your prompts. Instead of pasting a verbatim customer complaint, create a generic version that captures the essence of the problem without revealing names, account numbers, or specific details. Anonymize data before you submit it. Think of it as creating a hypothetical scenario for the AI to solve rather than giving it your actual, confidential problem. This practice of data minimization—using the least amount of specific data necessary—drastically reduces risk while still allowing you to benefit from the AI's capabilities. Also, take the time to review your privacy settings on any AI tool you use. Many services now offer options to disable chat history and opt-out of having your data used for model training.
Follow Your Company's AI Policy
The rise of “Shadow AI”—employees using unapproved AI tools without company knowledge—is a major security concern for businesses. To combat this, many organizations are establishing clear AI usage policies. These guidelines are not meant to stifle productivity but to create a safe framework for innovation. A typical policy will outline which AI tools are approved for use, define what types of data are prohibited from being entered, and clarify requirements for human oversight. It’s essential for every employee to be aware of and follow their company's specific rules. If your organization doesn't have a policy yet, advocate for one. In the meantime, the safest approach is to use company-provided, enterprise-grade AI tools, which often come with enhanced security and privacy features.
Choose Enterprise-Grade Tools When Possible
While public-facing chatbots are powerful, many companies are now deploying enterprise-level AI solutions that offer much greater security. These business-focused platforms are designed with data privacy as a core feature. Unlike their public counterparts, these tools often guarantee that your company's data will not be used for general model training and will be processed within a secure, private environment. Microsoft's Copilot and Google's Gemini for Workspace, for example, have specific provisions for data handling and compliance that are not available in their free, consumer versions. If you are handling any information that is even remotely sensitive, using a company-approved, secure AI platform is always the superior choice.
