AI strategy consulting in Canada, priced before it's promised
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AI strategy consulting, three pillars, one operator.
One Canadian team scores the use cases, then has to build them. The deliverable is an AI roadmap you can fund, not an AI business strategy nobody sequenced.
Use case scoring
Every candidate gets scored on business value, data readiness, and effort to build, so the weak ones die in week three instead of month eighteen.
Costing and ROI advisory
Inference, GPU, storage, and rework priced per use case, not a benefit statement your board has no way to check.
Operating model design
Who owns models, who approves a deployment, who watches cost, and whether a centre of excellence earns its name at your scale.
Does AI Strategy Consulting work the same way in every industry?
No. The AI Strategy Consulting work is the same craft in every sector, but the conditions around it are not. In financial services that means OSFI's technology and cyber risk rules; in government, Protected A, B and C data handling; and in defence and aerospace, controlled goods rules, CMMC and the flow-down from your prime. We keep the service and change the part that bends.
OSFI's technology and cyber risk rules set what an examiner will ask to see.
OSFI B-13. Technology and cyber risk across three domains: governance, technology operations and resilience, and cyber security. It binds federally regulated institutions, and only those.
Protected A, B and C data handling decides where the work can run and who can touch it.
Protected A, B and C. Each level changes where the data can physically live, who can reach it, and what you have to prove about both. Most files turn on Protected B, and most disagreements turn on what counts as reaching it.
Controlled goods rules, CMMC and the flow-down from your prime set what a supplier can do.
ITAR and the Controlled Goods Program. Registration under the Defence Production Act is mandatory before anyone examines, possesses or transfers controlled goods in Canada. Technical data counts, so a drawing sitting on a laptop is in scope.
Health information sits under provincial privacy law, and your IT provider is usually the custodian's agent.
PHIPA. Ontario's health privacy act, with its own definition of a custodian and its own duties for the agents acting on a custodian's behalf. Your IT provider is usually an agent.
Solicitor-client privilege decides how a firm can handle its data.
Law Society obligations. Confidentiality and competence duties reach the technology you practise with, and the vendors who touch client information. The firm is expected to have assessed the provider, which means the provider should arrive with the answers.
What do you need from AI Strategy Consulting?
Tell us who you are and what you're working on. A senior engineer reads your message before replying, so the first answer is a real read on scope, risk and timing, within an hour, 24/7. Nothing here is a commitment, and we'll tell you plainly if we're not the right fit.
Your request
- Service
- AI Strategy Consulting
What happens next
- A senior engineer replies within an hour, 24/7, never an SDR.
- We book a 30-minute call to listen, sketch options, and flag risks.
- You get a scoped statement of work within 3 business days.
Call the 24/7 line
+1 514-465-1584AI strategy consulting in Canada, made real.
Most AI strategy work fails the same way: nobody priced the running cost. This is written by the engineer who'd have to hit the number.
Three use cases, not thirty.
An AI business strategy worth funding names three use cases, not thirty. Each one carries the data it needs, the cost to run it for a year, and what happens if it doesn't work. Ranking use cases by excitement is how firms end up with a pilot nobody uses. We score on value, data readiness, and effort, and the data readiness column kills more candidates than the other two combined. If the data isn't there, the AI use case isn't a use case yet. It's a data project wearing a better title.
Price the run, not just the build.
We price the run, not just the build, because that's where AI plans break. Risk sits in three places. Inference cost that scales with usage, so success gets expensive. A model that needs a human checking every output, which quietly removes the saving. And the pilot that works on curated data and fails on the real thing. Roughly 88% of agent pilots never reach production, and the most common root cause is unclear success criteria (source: Forrester and Anaconda research, 2026). We write the kill criteria before the work starts.
The Canadian picture, and the law that actually applies.
Canadian context is unusually favourable and worth naming. 19.2% of Canadian businesses used AI to produce goods or deliver services in Q2 2026, up from 12.2% a year earlier and 6.1% in 2024 (source: Statistics Canada, 2026-05-27). The top uses are data analytics, text analytics, and chatbots. On law: Canada has no AI-specific federal statute in force. AIDA died at prorogation in January 2025 and no successor has been tabled. What binds you is PIPEDA, Quebec's Law 25, your sector regulator, and your client contracts, applied to whatever data your models touch.
Want a Senior IT Consultant's Read on Your Setup?
Tell us what you run today and what keeps breaking. A senior SMEnode engineer replies within an hour with a first read on scope, risk and timing. No sales handoff.
Request a consultHow our AI transformation strategy work runs.
Four steps, and step two exists to disappoint people. Scoring a use case list honestly means telling a client that most of what came out of their innovation workshop isn't fundable yet, and we'd rather say that in week three than eighteen months into a programme. It's also why we insist on building at least one of them. A consultancy that only writes AI strategy never learns what its own advice costs. We do, because the engineers who priced the roadmap are the ones who have to hit the number.
Engagement phases
Phases 01 to 04
Inventory
Every candidate use case, where it came from, and who wants it. Then what data actually exists for each one, where it lives, and who trusts it. Most lists shrink here before anyone scores anything.
Score and kill
Value, data readiness, effort. We name what dies and why, in writing, and it's usually most of the list. The rejected page is the one clients circulate, because it's the money they don't spend.
Cost the run
Build cost, then twelve months of inference, GPU, storage, and human review. The second number surprises people, and it's the one that decides whether a use case survives contact with a budget.
Design the operating model
Who owns models, who approves a deployment, what gets measured, and who sees the cost line monthly. AI CoE design if you need one, and an honest answer if you don't.
AI strategy consulting questions, answered straight.
Answers first, including which use cases we'd talk you out of. An architect takes the call.
Where this work connects.
These disciplines share the same senior team and tend to land together. Follow the thread to the next one.
- AIAI Automation ServicesCanadian AI automation built on real integrations, real permissions, and a plan for when it breaks.
- AIAgentic AI DevelopmentCanadian AI agent development with narrow scope, real permissions, and measured task completion.
- AIAI GovernanceCanadian AI governance scoped to what binds you, with the controls running inside your systems.
