How to Safeguard Your Data When Using AI Tools Like ChatGPT or Microsoft Copilot

As more small businesses adopt AI to streamline operations, boost productivity, and save time, one question comes up again and again:

“Is my data safe when I use a large language model (LLM)?”

It’s a smart question — and one worth understanding before you integrate AI tools into your business workflow.

Why Privacy Matters with AI

When you use tools like ChatGPT, Claude, or Microsoft Copilot, you’re inputting data: client details, internal processes, marketing plans, and sometimes sensitive information. If that data is stored, used to train models, or accessed by others, it poses a real risk to your business and clients.

Fortunately, many Large Language Model (LLM) providers now offer privacy-conscious versions built specifically for business and enterprise use.

6 Best Practices to Protect Your Data

1. Use Business or Enterprise Versions

Tools like:

• Microsoft Copilot (365): Keeps data within your Microsoft tenant. Not used for training.

• ChatGPT Enterprise: No data stored or used for training. SOC 2 compliant.

• Claude for Teams (by Anthropic): Prioritizes privacy and secure team usage.

These options give you more control, security, and compliance features than their free or personal-use counterparts.

2. Avoid Free/Public Tools for Sensitive Work

Free versions of ChatGPT or web-based playgrounds might store input to “improve model performance.” For anything confidential — client info, internal strategy, financials — steer clear of those platforms.

3. Turn Off Data Sharing Settings

Some platforms (like ChatGPT Pro) allow you to turn off training by disabling Chat History & Training in settings. It’s quick — and smart — to do this right away.

4. Use API Access for More Control

If you're building internal tools or workflows, use API access (e.g., OpenAI API or Claude API). Data sent through APIs is not used for training, and you get stronger security assurances.

5. Train Your Team on AI Use Policies

Create a simple internal policy. For example:

• Never input real names, emails, or confidential business data.

• Use generic examples or pseudonyms.

• Clearly label any sensitive documents and avoid uploading them to online AI tools.

6. Consider Self-Hosted AI for Maximum Control

For companies in regulated industries, such as healthcare or law, hosting your own LLM (like LLaMA or Mistral) on secure infrastructure is an option, but it requires some dedicated technical resources.

Final Thought

AI is powerful — but it’s only useful if it’s safe.

Even with great tools, there’s always some risk — so be thoughtful about what you share and how you use them. If you’re working with sensitive or regulated data, check with your IT and/or legal resources. And, I always recommend reviewing the fine print from any AI provider before jumping in.

Want help choosing the right AI tools for your team, or designing AI workflows to gain efficiencies, get time back in your day, focus on higher-level work, or grow revenue?

Let’s connect: aigrowthadvisor.com