How should Canadian and Quebec companies use AI?

Your team is probably already using AI. Someone drafts emails with a chatbot, someone else summarizes a contract, and a manager asks it to clean up a spreadsheet. The question is no longer whether your company should use AI, but how to use it without losing control of your clients' and employees' information. This article explains the rules that apply in Canada and Quebec, the risks we see most often, and a practical way to start. It is not legal advice; your privacy officer or lawyer has the last word.

What the law says today

Canada does not have a federal law dedicated to artificial intelligence yet. The proposed Artificial Intelligence and Data Act (AIDA), part of Bill C-27, died when Parliament was prorogued in January 2025. Ottawa has said new rules could come, but for now your obligations come mainly from privacy law.

• Federal: PIPEDA applies to personal information handled in the course of commercial activity in most provinces. When you send information to a service provider, including an AI provider, you remain accountable for it and must protect it by contract.
• Quebec: Law 25 adds stricter rules. Before personal information is communicated outside Quebec, you must assess the privacy impact. When a decision about a person is based only on automated processing, you must tell them.
• Other provinces: Alberta and British Columbia have their own private-sector privacy laws, and health information has its own provincial rules.

In short, AI is not a legal grey zone. The privacy rules that apply to any other use of personal information also apply to a question typed into a chatbot.

The real risk: what goes with the question

The biggest risk is rarely the AI itself. It is what your staff paste into it: client names, contract amounts, salaries or health details. When that text goes into a public AI tool on a personal account, it leaves your company, and you usually cannot tell where it is stored or how long it is kept.

Banning AI rarely solves this. People who find it useful keep using it on their phones, and the company loses all visibility. A tool your team prefers, with clear rules built in, does far more than a policy no one follows.

Four principles for using AI well

1. Know what is sensitive. Sort your information into what can go to an outside AI service, what can go only once identifying details are removed, and what must never leave. Payroll is not handled like marketing copy.
2. Give your team one approved tool. When people have a good tool at work, they stop using personal accounts. You can then set the rules once, in the tool, instead of hoping everyone remembers them.
3. Keep a person in every decision. AI can draft, summarize and suggest. A named person should review and approve anything that affects a client, an employee or your books. Real human review also helps keep your uses of AI out of decisions based only on automated processing.
4. Keep a record. Know who asked what, and what left your company. That record is what your privacy officer needs for an assessment, and what you need if a client asks questions.

A practical way to start

You do not need an AI team or a large project to begin. A sensible path for a company of 20 to 200 people looks like this:

1. List where your team already uses AI, and for what.
2. Write a one-page rule: what can be shared, what cannot, and who to ask when in doubt.
3. Pick one team and one or two useful tasks, with success measures agreed up front.
4. Run a pilot in an environment you control, measure the results, then expand department by department.

Who owns your AI matters

Most AI tools are rented. Your questions, your documents and the record of what happened sit in the provider's systems, under its terms. If the price, the rules or the provider changes, you adapt or start again.

The alternative is to run AI in infrastructure your company owns: your own cloud account, in the region you choose. You decide who has access, you keep the records, and you are not tied to one AI provider as models change.

How Hybrid Zero-Trust Private AI answers this

At BADEP, our answer to these questions is Hybrid Zero-Trust Private AI. It gives your team the power of the best AI models without exposing your clients' or employees' information, on a platform you own.

• Every request is given one of three levels. Sealed work never leaves your environment: a private model inside it handles the request. Shielded work goes out only after identifying details are removed, and they are put back when the answer returns. Shared work, such as public information, goes to the best model directly.
• Sealed is the default. When in doubt, the request stays in.
• Every request is recorded in your environment: what was asked, what left, and which model answered.
• The platform runs in infrastructure you own. If we part ways, it keeps running.
• You do not need an AI team. You describe your business, and we build, connect and maintain the platform.

It is designed to support your privacy compliance under PIPEDA, Law 25 and other provincial laws. Compliance remains your responsibility, and the records the platform keeps feed your privacy impact assessments.

Talk it through

BADEP is a new company, but its founder is not new to this work. Over 16 years, our founder has delivered several ERP and AWS projects for companies with more than 200 users.

Not sure where your company stands? In a free discovery call, tell us how your team uses AI today, and we will tell you what we would do and what it would take. You can also read more about our AI services and Hybrid Zero-Trust Private AI.