AI Consulting Frequently Asked Questions
Plain-language answers to the questions businesses actually ask us about AI consulting. Pricing, scope, frameworks, and where most AI projects go wrong. No buzzwords, no filler.
AI consulting basics
What AI consulting actually is, what it gets you, and when it makes sense.
What are AI consulting services?
AI consulting services help businesses move from curiosity about AI to working systems that save time or generate revenue. The good ones cut through hype and focus on what actually ships.
What does an AI consultant do?
An AI consultant turns vague ambitions like "we should use AI" into concrete projects with measurable outcomes. The work is part strategist, part product manager, part teacher.
Is AI consulting worth it?
Only when it is tied to specific business outcomes instead of open-ended experiments. If you cannot say what success looks like before the engagement starts, you are paying for someone else to learn.
Pricing and cost
Honest numbers on what AI consulting costs, how rates work, and what to expect.
How much does an AI consultant cost?
In Canada, small assessments start around $1,500 to $5,000. Implementation projects run $5,000 to $25,000. Enterprise engagements go $25,000 to $100,000 and up. Ongoing retainers sit between $2,000 and $10,000 a month.
What is the hourly rate for an AI consultant?
In Canada, hourly rates for experienced AI consultants sit between $200 and $500. Senior strategists and specialized implementers charge more. Sub-$150 rates usually signal a freelancer learning on your dime.
What is a reasonable consulting fee?
Reasonable fees are ones where the expected value clearly exceeds the cost and the scope is spelled out up front. Anchor the fee to outcomes, not hours.
Frameworks and rules
Principles and rules of thumb that keep AI projects on the rails.
What are the 4 types of AI?
A practical way to think about AI in business: descriptive (what happened), predictive (what might happen), prescriptive (what should we do), and generative (create something new).
What are the three golden rules of AI?
Start from a business problem, not a tool. Respect your data (quality, security, consent). Keep a human in the loop for anything that matters.
What is the 30% rule in AI?
A rule of thumb that says start by automating the 30% of a workflow that is repetitive and low-judgment. Leave the 70% that needs context, approval, or nuance to humans.
Why AI projects fail
Where most AI efforts break down, and what AI cannot do.
Why do 85% of AI projects fail?
Not because the models do not work. Because objectives are fuzzy, data foundations are weak, nobody owns the project after the pilot, and change management gets skipped.
What are the 5 things AI cannot do?
AI cannot feel empathy, take responsibility, reason well in novel situations with no data, set strategy or values, or be held legally accountable for outcomes.
What is the biggest flaw of AI?
It sounds confident even when it is wrong. Fluent output is not the same as accurate output, and that gap is where most AI-caused damage happens.
Still have a question we have not answered?
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