Walk into almost any small business in Toronto at closing time, and you will find someone still working through the inbox. Booking requests, supplier invoices, quote follow-ups and the same five customer questions asked in slightly different words. None of it is hard. It simply takes hours that an owner or office manager would rather spend on customers, staff or the actual craft of the business.
More of that work is now being handed to artificial intelligence. In the second quarter of 2025, Statistics Canada found that 12.2% of Canadian businesses had used AI to produce goods or deliver services over the previous 12 months, up from 6.1% a year earlier. Use doubled in a year, and yet close to nine in ten firms still reported none.
The gap between sectors is just as telling. Information and cultural industries reported 35.6%, professional services 31.7% and finance and insurance 30.6%, while accommodation and food services sat at 1.5%. In a city with as many restaurants, salons, contractors and independent shops as Toronto, most owners are clearly still at the starting line. The hard part is picking a first project that neither wastes money nor puts customer information at risk.
Start with the work nobody wants to do
The best first project is rarely the most impressive one. It is the task that repeats every day, follows the same pattern and frustrates whoever handles it. Think of a renovation company that types the details of every quote request into a spreadsheet, or a dental office that confirms each appointment by phone. These jobs have clear inputs, clear outputs and a person who will notice immediately if something goes wrong.
A simple test helps. Write down every task your team did last week that involved copying information from one place to another. Then mark the ones that happen more than ten times a week. That short list is usually where automation pays for itself fastest, because the time saved adds up quickly and the risk of a costly mistake is low.
Avoid starting with anything that makes a judgment call about a customer. Deciding who gets credit, which complaint deserves a refund or whether a job application moves forward should stay with a person for now. Software that sorts and drafts text quickly can still miss what never made it into the email: the customer’s history, the tone of the last phone call, the promise someone made at the counter.
Three automations that suit a Toronto small business
The first is inbox triage. An AI tool can read incoming messages, label them as bookings, quotes, complaints or supplier mail, and draft a reply for a human to approve. For a busy café catering business or a property manager with dozens of units, that alone can turn an hour of sorting into ten minutes of checking.
The second is invoice and receipt handling. Bookkeeping software already does much of this, but AI can read a supplier invoice that arrives as a photo or PDF, pull out the amount, date and HST, and file it in the right place. Your accountant still reviews the books. They just stop receiving a shoebox of crumpled paper every quarter.
The third is a website assistant that answers routine questions. Opening hours, parking near the shop, whether you serve a particular neighbourhood, what a typical job costs. A well-built assistant hands the conversation to a person as soon as a question goes beyond the basics, and it should never pretend to be human. Customers tend to accept the tool when it is honest about what it is.
The privacy rules still apply to your AI tools
The legal side is easy to overlook. Under federal law, the Personal Information Protection and Electronic Documents Act applies to private-sector organizations across Canada that collect, use or disclose personal information in the course of commercial activity. Alberta, British Columbia and Quebec have their own substantially similar laws, but an Ontario retailer or contractor is generally covered by PIPEDA. That obligation does not disappear because the data went into a chatbot.
In December 2023, Canada’s federal, provincial and territorial privacy commissioners published principles for generative AI. One of them is plain common sense for a small business: use anonymized, synthetic or de-identified data rather than personal information where the personal information is not needed. If a tool can draft the reply without the customer’s full name, home address or account number, it should not be given them.
The riskiest material is identity documents. Plenty of small businesses ask for a copy of a driver’s licence or passport, for a rental, a deposit or a new hire. Uploading a whole licence so a chatbot can pull out a name and a number hands over a photo, a date of birth and a home address along with it. Crop or cover what the task does not need, or simply type the two fields yourself.
Getting outside help without losing control
Some owners build these workflows themselves with off-the-shelf tools, and for a single automation that often works. Once the booking system, the accounting software and the inbox all need to talk to each other, the job starts to look like a project, and that is usually the point where it pays to bring in people who do this full time.
The right specialist will not necessarily be in the GTA, and that matters less than how they work. Aivy Automations, an Australian agency with teams in Melbourne and Sydney, is one example of the approach to look for: it builds on the software a business already uses rather than replacing it, and it starts with a free 30-minute diagnostic call before proposing anything.
Whoever you talk to, ask three direct questions before signing. Where will customer data be processed and stored? Who can see it? What happens to the automation if you stop paying for the service? A good answer is specific and written down. A vague one is a reason to keep looking, however polished the demonstration was.
Measure the first project before you scale
Before switching anything on, record how long the task takes today and how often errors happen. Run the automation alongside the old process for two or three weeks and compare. If the time saved is real and the error rate holds or falls, expand it. If not, adjust the workflow or drop it, because a failed pilot costs far less than a failed rollout.
Keep a person responsible for every automated process. Someone should read a sample of AI-drafted replies each week, check that invoices are landing in the right accounts and listen when staff say the tool is getting something wrong. Automation works best as a capable assistant that a person supervises, not as a system nobody remembers setting up.
A sensible pace for 2026
The Statistics Canada numbers show Canadian businesses moving, but most of them are still near the beginning. For a Toronto owner, that is a comfortable position. There is time to pick one tedious job, automate it with care, keep customers’ personal information where it belongs and learn what works before spending on anything larger.
Rent, wages and competition in this city are not getting any easier. Against that, winning back a few hours a week without giving customers a reason to worry about their information is a modest goal. For most small businesses it is also the right one, and it will do more for the bottom line than chasing every new tool in the week it launches.
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