Using AI in your business: automating repetitive work with an AI agent

By the NRX3 team · Updated October 23, 2026

AI changes very quickly. This guide was written to the best of our knowledge as of October 23, 2026; some of it may now be outdated or no longer apply.

For most people, using AI means asking it a question: draft an email, summarize a document, prepare a presentation. That's useful, but the gain stops where the conversation stops. The real change comes when AI takes over a process: a task that comes back every day, which it handles from start to finish while your employees focus on what needs their judgment.

In Québec, about one business in eight (12.7%) used AI to produce its goods or services in the 12 months leading up to the second quarter of 2025, and about one in four (26.1%) among businesses with 100 employees or more. This guide shows how to go beyond questions.

Two ways to use AI

Give it a one-off task

You open a tool like ChatGPT, Claude, Copilot or Gemini and ask it for something: an email, a summary, a draft presentation, a translation. It's quick and anyone can do it. But you're the one fetching the information, pasting it into the tool and copying the result somewhere else. Every time.

Give it a process: the AI agent

An AI agent doesn't just answer. It follows a sequence of steps you've defined: it receives information where it arrives, understands it, decides what to do according to your rules, and acts in your tools: your email, your accounting software, your customer management. Once it's set up and connected to your tools, it doesn't wait to be asked: it gets to work whenever the situation comes up.

Example 1: the general inbox

Your info@yourbusiness.com address gets dozens of messages a week: quote requests, customer questions, invoices, vendor offers, job applications. Someone has to read them one by one, guess who they're for and forward them. An AI agent can do that work:

1. It reads every email as soon as it arrives, attachments included.
2. It works out what it's about and who it's for: a quote request goes to sales, a complaint to customer service, an invoice to accounting.
3. It writes a summary in two or three lines: who's writing, what they want, whether it's urgent.
4. It drafts a reply from your information: your services, prices, lead times, usual answers.
5. It sends it all to the right person, who only has to review, adjust and send.

The result: messages reach the right person right away, with a reply already prepared. Customers wait less, and nobody spends their morning sorting mail. And because an employee sends the reply, the contact stays human.

Example 2: supplier invoices

It's not unusual for someone to spend several hours a week opening invoices received by email, copying the amounts into the accounting software and checking them against orders. It's repetitive work where a data-entry error is costly. An AI agent can take it over:

1. It spots the invoices among incoming emails and opens them, as a PDF and, depending on the tool, even as a photo.
2. It extracts the information: supplier, invoice number, date, amounts, sales taxes (GST and QST), due date.
3. It compares them with the matching purchase order or receiving slip.
4. It prepares the entry in your accounting software, as a draft.
5. It flags anything off: an amount that differs from the order, a duplicate invoice, a new supplier.

The person in charge of accounting only has to approve the invoices that match and deal with the few flagged cases. They move from data entry to review.

Other processes that fit

• following up on quotes that got no answer;
• a daily summary of production or shift reports;
• onboarding new registrations or customers: confirmation, documents to provide, reminders;
• preparing accountability reports from data you already compile.

Where to start

1. Choose a repetitive process. Look for a task that comes up often, follows roughly the same path every time, and where a mistake is easy to spot. We can help you identify your first processes to automate.
2. Describe it step by step. Where the information comes from, what's done with it, where the result goes, and who decides what. If you can explain it to a new employee, you can hand it to an agent.
3. Choose the right tool. Depending on the case: a feature already in your software, an automation platform, or a custom-built agent. No tool does everything better than the others: compare them on your specific process.
4. Keep a person to approve. At first, the agent prepares and a person validates every result. Only remove checks once reliability is proven, and never for important decisions.
5. Measure, then expand. Compare the time spent before and after, and the number of corrections. If the gain is real, move on to the next process.

What to keep in mind

• AI can be wrong with great confidence: that's why the agent prepares and a person approves.
• It doesn't know your business: you need to give it your rules, examples and up-to-date information.
• Your data moves: an agent reads emails and invoices that contain personal information. Choose tools whose terms you know, and see our guide AI and privacy.
• Plan a fallback: if the agent goes down, the work must still be doable by hand.

When to call in a specialist

For a simple first trial, automation tools may be enough. A specialist becomes useful when the agent has to work inside your own software, handle sensitive data, deal with many exceptions or reach a high level of reliability. For what comes next, see our guide Integrating AI into your existing tools.