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AI in the workplace: Boost productivity without losing control of your data

Written by Edward Knox | Jul 25, 2025 1:16:06 PM

AI is transforming the way people work. Tools like ChatGPT, Google Gemini and Microsoft Copilot are allowing teams to generate ideas, create reports, write code and uncover insights faster than ever before. AI innovation is unlocking new levels of productivity within businesses.

Although there are a number of benefits, there’s also new risks, particularly when it comes to data privacy. Many organisations are discovering that employees (often with the best intentions), may be putting sensitive or confidential information into public AI tools. This is a major risk because without proper controls in place, organisations are at risk of data leakage and compliance violations.

In this blog, we take a look at the risks of sharing sensitive data and how to find the right balance of boosting productivity whilst protecting data.

The risk of sharing sensitive data with LLMs

Large Language Models (LLMs) are trained to generate responses by analysing huge datasets, including the prompts users feed into them. So, when employees copy and paste internal documents, source code or customer information into AI platforms to get quick answers, they may inadvertently be sharing sensitive company data outside of secure boundaries.

AI platforms may process requests through shared infrastructure which logs or stores data temporarily. Depending on the platform’s policies, this data could potentially be retained, reviewed or used to retrain the model. In the worst-case scenario, the confidential information inputted could be exposed or repurposed in ways out of your control.

What employees are doing isn’t malicious, in many cases, employees simply just don’t realise the risks. This kind of accidental data egress is a form of insider risk and is a growing concern for IT and security leaders - especially in highly regulated industries.

Productivity vs. protection - finding the right balance

So, what can be done? Shutting down AI tools completely isn’t the answer and organisations that try to block AI use across the board may end up stifling innovation and frustrating employees who are simply trying to be more efficient. The smart approach is to use AI while ensuring safeguards are in place to control what data is shared and where.

Here’s four steps companies can take to strike the right balance between productivity and protection:

  1. Educate staff
    Strong security awareness is where it starts, employees need to understand the types of data that shouldn’t be shared with AI tools, such as personally identifiable information and financial data. Regular training can make a big difference in helping staff make smarter choices.
  2. Use enterprise-ready AI
    It’s important to choose platforms with clear data and privacy policies. Microsoft Copilot and Google Gemini, for example, offer managed enterprise environments with stricter controls than their public counterparts.
  3. Deploy data loss prevention solutions
    Automated Data Loss Prevention (DLP) tools can help enforce your data protection in real time. DLP solutions like FortiDLP can detect when users are attempting to send sensitive data to LLMs and block these actions before they take place. These tools analyse content and context, ensuring compliance without slowing down productivity.
  4. Define clear AI usage policies
    Create clear guidelines and an AI usage policy that gives employees clarity on when and how to use AI tools. Make sure these policies are reviewed regularly and are easy to access to ensure data continues to be kept away from risk.

Why FortiDLP?

FortiDLP is a comprehensive data protection solution that offers visibility and control over how data moves across your organisation - whether it’s on endpoints, within cloud apps or across your network. FortiDLP uses policy-driven controls to stop sensitive data from being shared improperly.

FortiDLP allows businesses to:

  • Automatically block sensitive information from being pasted into web-based AI tools like ChatGPT
  • Customise policies based on data classification, user roles and risk levels
  • Monitor data across devices and platforms
  • Maintain compliance with data privacy regulations like GDPR, HIPAA and more

We know that AI can be a powerful tool, but to fully benefit from it, organisations must be proactive about protecting their data. With the right combination of technology, education and policy, it’s possible to benefit from AI tools and increase productivity without compromising on security.

Putting data security first

Here at Brigantia, we offer a range of cybersecurity tools to support businesses of all shapes and sizes with their online security.

Chat to our team today about how FortiDLP can protect employees’ AI usage and help prioritise data security, all whilst boosting team productivity.

Book a FortiDLP demo today.