Generative AI tools like ChatGPT are, without doubt, game-changers for businesses across sectors. But they also come with significant risks. Sensitive data shared with these AI models can quickly spiral out of control, leading to unintentional but costly data leaks.
The result? Your business could be embroiled in a data breach before you even realize what’s happened.
In this blog, we’ll break down how generative AI creates these risks and, more importantly, how to protect your data without losing the AI-driven edge.
Generative AI: The data leakage risks to know about
Generative AI privacy and data leak risks come in two key forms. First, there’s the chance that a customer, contractor, or employee may unintentionally share sensitive data with LLM apps, leading them to store information that should never have been exposed. Second, these AI models can potentially regurgitate this data to other users, sparking a further data breach.
Let’s bring this into context. Picture someone on your marketing team struggling to segment customer profiles. Instead of wrestling with a spreadsheet, they turn to ChatGPT, a faster and more efficient solution. They upload a large amount of personally identifiable information (PII) about your customers, and within moments, the AI creates a clean, organized table.
Sounds like a win, right? Except that the data they’ve shared is now part of the AI’s memory. The result? This sensitive information could resurface for other users at any point, in various forms.
Here’s the issue—AI models are sharp, but they lack common sense. They don’t know the difference between a secret business strategy and a grocery list. Once sensitive data is shared, it’s effectively an open invitation for an unintentional data breach—similar to handing over confidential information to a bad actor.
What makes this worse is the compounding effect. Generative AI models don’t just forget. They’re capable of unknowingly sharing this sensitive information again and again, turning what could’ve been a one-off slip into a spiraling data breach that reaches multiple users.
How to protect sensitive data in AI-powered apps
With all the benefits generative AI tools bring, blocking them isn’t an option—especially if you want to gain a competitive advantage.
However, that doesn’t mean you need to simply accept AI data loss, either. With the right controls, you can unlock the benefits of AI without the risks.
Here are the steps to take:
- DLP for AI: Data loss prevention (DLP) tools built for AI use machine learning and automation to identify and redact sensitive data that users input into AI prompts, stopping it from ever being shared with the AI system. Now, we know that DLP gets a bad rep for being clunky and inaccurate, but there’s a new breed of DLP tools available with high fidelity. They use a mixture of reg-ex and natural language processing (NLP) to bring contextual awareness to the data redaction process, ensuring only genuinely sensitive data is captured and secured—with way less alerts for your security team.
- Bi-directional monitoring: Where sensitive data has already been inputted into your AI systems, you need a way to stop it from showing up in other users’ answers. A great DLP for AI tool will also feature bi-directional monitoring, which ensures that sensitive data is never received by employees, even if inadvertently generated by ChatGPT.
- Human risk management: It’s great that DLP mitigates the risks associated with employees making errors. But wouldn’t it be better if employees could learn from those mistakes and improve? Well, they can–with embedded human risk management. DLP for AI tools like Polymer combine smart data redaction with personalized user nudges. These educate the users on why their action was blocked or augmented in real-time, helping to build a culture of security and reduce repeat offenses.
- Enhanced data governance: Knowing how data is used in your organization is critical. Without proper oversight, vulnerabilities and blind spots for data leaks can form. It’s not just about human access—applications also duplicate sensitive data, often without the same security protections. Polymer helps you maintain control by using AI and natural language processing to monitor unstructured data flows in SaaS applications. This ensures quick, accurate classification and tighter control over data lineage, access, and usage.
One solution for all your AI problems
With Polymer DLP, you don’t have to choose between innovation and security. Our solution brings together AI-powered data loss prevention, bi-directional monitoring, and human risk management to ensure that sensitive data stays protected at every step. From real-time redaction of AI prompts to educating employees on security best practices, Polymer gives you the control and confidence to harness the power of generative AI—without the risk of data leaks.
Elevate your AI strategy today. Request a free demo.
