Every agency site promises agents and transformation. These ten questions — and what a good answer sounds like for each — are how you tell them apart before you sign.
The short answer: vet a Canadian AI automation agency on ten things — where your data lives, production references, a written scope with a stated price range, who owns the code and prompts, security practice, monitoring, and your exit plan. Any agency worth hiring answers all ten without hedging.
Because the category is two years old and the marketing is uniform. Every agency site promises agents, automation and transformation, and almost none of them publish a price, a delivery method or a compliance posture you could check. Meanwhile the failure rate is documented: MIT's 2025 NANDA report, "The GenAI Divide: State of AI in Business 2025", found that roughly 95% of enterprise generative-AI pilots delivered no measurable business impact, and that buying from specialist vendors and forming deployment partnerships succeeded far more often than internal do-it-yourself builds. Choosing the partner well is most of the outcome.
The questions below are ordered so the disqualifying ones come first. Ask them in a first call, before anyone opens a slide deck. If you want to see who is operating in this market before you start, we maintain sourced roundups of AI automation agencies in Toronto and AI agents companies across Canada, and we include our own entry with the same criteria applied.
Ask each vendor where every provider in its call path processes and stores data, which copies exist, what retention applies to each, and what contractual and operational evidence supports those answers.
The gap between a pilot and production is where most AI projects die. A demo proves the agency can build a demo. A reference call proves someone's staff use the thing every day.
Good answer: a named reference in a comparable industry, running the work in production, who will take a call. If everything is under NDA and nothing can be described even in outline, treat that as a data point.
AI projects are mostly discovery, and an open-ended engagement with no written scope transfers all of that risk to you. A written scope forces the agency to understand the problem before quoting it, and a change-order process keeps later changes visible.
Good answer: a written scope describing the workflow, the integrations and the exclusions, a stated price range, and a written change-order process so that changes are agreed in writing before they are billed. Published tiers are a good sign; ours are on the deployment page, and typical Canadian ranges are broken down in our AI agent cost guide.
Prompts, tool definitions and workflow configuration are the real asset in an agent build. If the agency keeps them, you are renting your own process back from them for as long as you use it.
Good answer: you own the deliverables outright, including prompts and configuration, delivered into a repository you control. Licensing a shared platform is legitimate — but it should be stated plainly, not discovered at renewal.
"It works" is not a test. Without written criteria, the final invoice arrives at the moment the agency thinks the project is finished, which is rarely the moment you do.
Good answer: a list of specific cases the agent must handle correctly — including the awkward ones and the ones where it must refuse or escalate — agreed before work starts and tied to the final payment.
Sales-led agencies are frequently selling a senior engineer and staffing a junior one, or subcontracting offshore without saying so. That matters for quality and it matters for where your data goes.
Good answer: named people, their role on your project, and a clear statement about subcontractors and their location. Ask who you call when the agent misbehaves at 4pm on a Friday.
An agent that fails silently is worse than no agent, because you keep believing the work is being done. Monitoring is the difference between a system and a science project.
Good answer: logging of every action the agent takes, alerting on failures and anomalies, a named owner for the alerts, and a way for you to inspect what happened on any given interaction without filing a ticket.
You are granting a third party credentials to your calendar, your CRM and possibly your practice-management system. The blast radius of a compromised integration is your entire customer list.
Good answer: least-privilege credentials scoped per integration, secrets held in a managed vault rather than in code or configuration files, rotation on staff changes, and a described incident-response process.
The build is the smaller number. Usage, hosting, monitoring and the inevitable adjustments are what you pay every month for years, and vendors who avoid the question are usually avoiding a bad answer.
Good answer: an itemized estimate of ongoing costs — model and telephony usage, hosting, monitoring — plus a stated rate or included allowance for changes. Ask what a typical month looks like for an existing client.
The best time to negotiate leaving is before you arrive. Agencies that expect you to want out write long lock-ins; agencies that expect to earn renewal do not need them.
Good answer: no multi-year lock-in for standard work, your data exported or deleted on request, documentation good enough for another team to take over, and a stated notice period. If they cannot describe an orderly handover, you are the one carrying that risk.
A few answers should end the conversation early. "We can't discuss where the data is processed" — that is always a decision someone made. "We'll scope it as we go" on a project quoted in tens of thousands of dollars. "Our platform, our prompts" without saying so up front. And any pitch that leads with a percentage improvement it cannot source: a real firm cites Statistics Canada or a named study, not a number from a competitor's landing page.
Be equally suspicious of the opposite failure — an agency that agrees to everything. Good partners tell you when your problem does not need them, which is often. If the task has a fixed trigger and a fixed outcome, you may only need workflow automation; our comparison of AI agents, chatbots and Zapier-style automation walks through how to tell.
Send the ten questions to your shortlist in writing before the first meeting and compare the written answers side by side. Written answers are harder to improvise and easier to hold someone to later. Then use the meeting for the two things writing cannot do: meet the person who will actually build the thing, and watch how they respond when you push on a detail they got wrong.
Score each vendor on all ten rather than on the demo. Demos are the part every agency has rehearsed; data residency, ownership, monitoring and exit are the parts that determine whether you still have working automation in eighteen months. And put the same questions to us — the checklist is not a trick that only Mihron AI passes, and if another firm answers them better, hire that firm.
Mihron AI is a Toronto-based AI agents and workflow-automation company building and operating agents for Canadian businesses. See our services, our approach as an AI agents company in Toronto, our workflow automation guide, and what projects cost in our AI agent cost guide.