Data privacy when using AI

During 2023, the massive adoption of artificial intelligence assistants came with an uncomfortable lesson: several organizations discovered that sensitive information was leaking simply because their teams pasted it into public chatbots to “ask for help.” Snippets of code, customer data, and internal documents ended up traveling to third-party servers without anyone formally deciding it. It wasn’t a sophisticated attack: it was everyday use, well-intentioned and without clear rules.

That episode left a lesson that still holds for any Mexican small business that wants to take advantage of AI today. The tool is powerful and worth using, but what you type into a public chat can leave your control. The good news is that you don’t have to choose between productivity and privacy: with simple criteria and an architecture designed to your measure, your team can use AI every day while keeping your data, processes, and history in-house.

What you should never paste into a public AI

The practical rule is simple: if you wouldn’t publish a piece of data on your website, don’t paste it into an open chatbot. In a public tool, you don’t always know where what you type is stored, who can review it, or whether it will be used to train the model. Before copying and pasting, stop if the text contains:

• Personal data of customers or employees: names with tax ID, national ID, addresses, phone numbers, emails, or medical and financial information.
• Credentials and access: passwords, API keys, tokens, database connection strings.
• Business financial information: account statements, margins, internal price lists, supplier contracts.
• Intellectual property: source code, formulas, commercial strategies, unpublished legal documents.
• Regulated data: any information subject to the Federal Law on the Protection of Personal Data that you handle under a third party’s consent.

If you wouldn’t publish a piece of data on your website, don’t paste it into an open chatbot.

Not all AI is the same: public, enterprise, and custom

Lumping everything together is part of the problem. A free general-purpose chatbot doesn’t offer the same guarantees as an enterprise version with data processing agreements, nor as a solution installed on your own infrastructure. The difference isn’t the brand, but the conditions under which your information travels.

For a small business, the value lies in choosing the right level for each use case. Drafting a generic email can be handled with an open tool; in contrast, analyzing your customer portfolio or automating your quotes calls for a controlled environment. That’s where a custom solution makes the difference: you can connect AI to your own documents and systems without exposing your information, and decide with clear rules what gets processed, where, and for how long.

How to use AI without exposing your information

Privacy doesn’t depend only on the tool, but on how your team uses it. With a few habits and controls, the risk drops dramatically:

• Anonymize before asking: replace real names and identifiable data with fictional examples when you ask for general help.
• Define a clear internal policy: put in writing what can and can’t be shared, and share it with the whole team.
• Use business accounts: prefer business plans that let you disable the use of your data for training.
• Centralize on approved tools: keep each person from using whatever app comes to mind; offer an official, secure alternative.
• Start small and measurable: test first in an area with low-sensitivity data before scaling to critical processes.

How to take the first step in an orderly way

You don’t need to halt innovation out of fear, or dive in without a net. The middle ground is to prepare the terrain before accelerating:

• Do a quick inventory of what your team uses AI for today and with what information.
• Classify your data into three levels: public, internal, and confidential; the confidential ones never go to open tools.
• Train your people with concrete examples from your own business, not abstract rules.
• Evaluate a custom solution when the use case involves customer data or processes that give you a competitive edge.

Using artificial intelligence and protecting privacy aren’t opposing goals: framed well, they reinforce each other. At Normandia Web we help small businesses integrate AI securely, keeping control of their data and with solutions built for their real operation. If you want to take advantage of these tools without putting what matters most at risk, let’s talk and design that first case together.