Cost · ai consulting cost ontario
What does AI consulting actually cost in Ontario?
AI consulting in Ontario runs $1,500 to $5,000 for an assessment and $2,500 to $25,000 for a build. Here is what moves the number, with sources.
Lasse Pettersen
AI consulting in Ontario has three price bands, and they are stable enough to quote. A readiness or strategy assessment runs $1,500 to $5,000 among Canadian firms that publish rate cards, with several opening at $2,000 or $3,500. A single automation workflow runs $2,000 to $8,000 to build. A multi-workflow or custom agent project runs $2,500 to $25,000, occasionally higher where the work touches regulated records. Ongoing operation, where you want somebody else watching it, adds $150 to $400 a month.
Those are the numbers. The rest of this note is about what moves you within them, because the range is wide and the reasons are not mysterious.
Why the assessment is priced separately at all
An assessment exists because the expensive mistake in this work is not paying too much for a build. It is paying the right amount for the wrong build.
Statistics Canada asked businesses that were not adopting AI why not. Cost came fourth, cited by 10.6%. Cybersecurity and privacy came third at 13.4%. The leading answer, from 40.0% of them, was that AI is not relevant to what they do. That answer is usually a description of not knowing where to look rather than a considered judgement, and it is why the diagnosis and the build are separate purchases.
The assessment on this site is $999 for that reason, which is under the floor of the published Canadian band. The whole fee comes off any build that follows, so for anyone who proceeds it costs nothing. What it buys is ten business days of work, three named jobs with hours and dollars against each, and the ones I recommend against.
What actually moves a build price
Six things, in rough order of how much they matter.
| Driver | Cheap end | Expensive end |
|---|---|---|
| Systems involved | Two, both with a modern API | Four or more, one a desktop application with no interface |
| Decision logic | One path, straight through | Branching by customer, value, region or approval level |
| Error handling | Retry, then email somebody | Reconciliation, audit trail, rollback |
| Personal information | None, or internal only | Client health, financial or identity data |
| Volume | Tens of runs a day | Thousands, where per-run model costs matter |
| Who operates it | You, on your own accounts | Me, with monitoring and a response time |
The fourth row is the one people underestimate. A process that touches somebody else’s personal information cannot use whichever tool is cheapest. In May 2026 the Office of the Privacy Commissioner of Canada found that OpenAI’s initial training of ChatGPT did not comply with Canadian privacy law, and the guidance that followed treats prompts, retrieval corpora and model outputs as personal information handling like any other processing. The practical effect is a smaller list of eligible tools and a written data boundary in the scope. That is covered properly in what PIPEDA means for your AI tools.
The first row is the one people overestimate. Two modern systems talking to each other is not hard and should not be priced as though it were.
What “AI” is doing in these projects
Frequently, very little, and that is the honest answer rather than a criticism.
A large share of what gets sold as AI in a small business is two systems that were never introduced to each other, with a person in the middle acting as the integration. Automating that involves no model at all. It is plumbing, it is well understood, and it is the cheapest thing on the list.
Where a model earns its place is in the messy middle: reading a document that arrives in eleven different layouts, drafting a reply that then gets approved, classifying an enquiry that does not fit a dropdown. Statistics Canada’s Q2 2026 figures put data analytics at 36.6% of Canadian AI use, text analytics at 34.5% and virtual agents or chatbots at 28.2%, which is roughly the order those jobs appear in real businesses.
The rule worth applying to any quote you receive: if the proposal puts a model between a customer and a number that has to be correct, ask why. A model that composes an invoice total will eventually compose the wrong one.
Three worked examples at Ontario prices
A 14 person Hamilton fabrication shop. One estimator writes every quote from a drawing, a material price list and a memory of similar jobs. Quotes take two to five days and work is lost to whoever answered faster. Automating the assembly around the estimator’s judgement is a $4,000 to $9,000 build, because it touches the price list, the historical job records and the document template. The judgement stays with the estimator. The two hours of assembly around twenty minutes of thinking is what goes away.
A five person Barrie trades business. The owner is on site all day and the phone rings anyway. An intake agent that answers, captures the address and the problem, and books the standard jobs starts around $4,000 and runs $80 to $200 a month. This is the highest return automation available to a small service business and the arithmetic is unusually simple, because it pays back on a small number of recovered jobs. More detail in the four automations that pay in a trades business.
A 40 person Mississauga head office. Data comes out of a global system, gets reshaped locally for a Canadian requirement the global system does not handle, and goes back in. Somebody owns that spreadsheet and thinks of it as their job rather than as a process. That is usually a $3,000 to $6,000 build, and finding it is the hard part, not building it.
What you should not pay for
A discovery call that produces a proposal instead of a number. The complexity of your business is the same whether or not a supplier has qualified you first. A firm that will not publish a range is measuring what you will pay.
A strategy deck. If the deliverable is a slide about the AI landscape and a maturity curve, you have bought a summary of the news. What is useful is a list of your own processes with hours against them.
A model subscription marked up. Model and platform costs should be on your own accounts, billed to your own card, in your own name. When they are on your supplier’s account, changing supplier means rebuilding.
Anything that will not survive handover. Ask for the runbook before you agree: every credential, every trigger, every failure mode, written so a different supplier could take it over. If that request is awkward, you have learned something worth more than the answer.
The funding you may not have checked
Before paying for planning work at all, check whether a program will. The Ontario Centre of Innovation runs a Digital Modernization and Adoption Plan worth up to $15,000 toward a digital adoption plan, open to Ontario for-profit SMEs with 1 to 499 employees, on a first come first served basis while funds last. A follow-on Technology Demonstration Program offers up to $50,000 toward implementing what the plan recommends, with a minimum annual revenue threshold and a completed plan as prerequisites.
Programs open, close and change their terms, so verify current status with the administrator rather than with a consultant who benefits from your application. The detail as published is in the note on the DMAP grant.
The short version
Budget $999 to $5,000 for a diagnosis and $2,500 to $12,000 for the first build in a business under 100 people. Expect the price to move on how many systems must agree and whether personal information is involved, not on how impressive the technology sounds. Ask for every price before the call rather than after it, and ask what happens at handover before you ask what the model is.
If you already know exactly what you want built, skip the diagnosis and ask for a quote on workflow automation. If you do not, that is what the assessment is for, and it comes off the build.