Why Your Business Data Shouldn't Live in Public AI Tools

AI tools are everywhere right now. From drafting emails to analyzing customer feedback, they offer speed and convenience that’s hard to ignore. But for growing businesses, especially those managing sensitive information, there’s a risk hiding in plain sight: feeding your business data into public AI platforms without fully understanding how that data is stored, used, and potentially exposed.

According to a 2024 IBM study, the average cost of a data breach is now $4.45 million globally—a 15% increase over three years. Many of these breaches stem from mishandled data in third-party platforms, including AI tools that weren’t designed with enterprise-grade data privacy controls. Despite disclaimers that input data won’t be used for training, several well-documented cases have shown otherwise. AI models are often built on massive data sets scraped from or contributed by users, and unless your business has strict policies in place, your internal data could end up somewhere you never intended.

In this post, we’ll break down why public AI tools are not the place for your sensitive business data, what steps you can take to protect it, and how our approach at Notics ensures safer, faster, and smarter IT management.

Why AI Tools Present a Business Risk

Common Challenges

Many public AI tools like ChatGPT, Bard, or Copilot run on cloud-based platforms that share architecture across users. This raises concerns about where your data is stored, how long it remains there, and who might access it. The lack of control is only part of the issue. Employees often input sensitive data without realizing the implications, especially when there's no formal guidance. This kind of unchecked usage falls into the category of shadow IT, which increases your exposure to breaches or compliance violations.

A 2023 Cisco Data Privacy Benchmark Study found that while nearly every organization considers data privacy a business priority, most still struggle to track how information flows through third-party platforms. That gap becomes even more problematic with tools that are constantly evolving and ingesting new data to improve.

‍Industry Examples

Take Samsung, for example. In 2023, employees unintentionally leaked confidential source code by using ChatGPT to debug code. In the legal sector, firms have been penalized for submitting AI-generated documents that included fabricated information. These aren’t isolated incidents—they’re indicators of what happens when businesses treat public AI platforms like internal tools without applying the same risk standards.

Strategic Solutions for Data Privacy in AI

The good news is that businesses can still benefit from AI while safeguarding their data. The key is to build a system of checks, controls, and clear expectations.

Start by creating an AI use policy tailored to your operations. It should outline which tools are approved, what data is considered off-limits, and how different teams should interact with AI systems. Without these guardrails, employees will often prioritize convenience over caution.

Next, explore options for private AI deployments. Hosting AI models in secure environments—either in-house or through enterprise-managed platforms like Azure OpenAI—ensures that your data isn’t shared or stored on infrastructure you can’t control.

Monitoring data flows is just as important. Many platforms now include embedded AI features that process data externally. If you’re not paying attention, your customer records or internal reports might be analyzed or cached without your knowledge. A formal audit of all integrated systems, paired with endpoint monitoring, can help you stay ahead of this.

Restricting access to sensitive information is another core strategy. Role-based access controls and data loss prevention policies can significantly reduce the risk of someone accidentally feeding private data into an AI tool. And finally, none of these solutions work unless your people understand why they matter. Ongoing employee training—especially with real-life examples—can make a big difference in how teams use these tools responsibly.

Using AI tools doesn’t have to mean compromising on data privacy. But if you’re relying on public platforms without the right controls in place, you could be exposing your business to serious risk.

Clear policies, secure environments, continuous monitoring, and employee training are essential to using AI effectively and safely. And when you partner with a strategic IT provider like Notics, you’re not just protecting your data—you’re putting the right systems in place to grow with confidence.

If you’re unsure where your risks are—or whether your team is using AI in ways that could create exposure—it’s time to take a closer look.

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