What AI implementation actually costs (and why most quotes are wrong)

The most common question I get on a first call is some version of: how much does AI cost?

The honest answer is that the question is malformed. It's like asking how much a building costs. A shed and a hospital are both buildings. The number depends on what you're trying to make happen, and most people asking the question haven't yet decided.

Here's the rough shape I've seen, from actually running these projects:

A focused internal tool — something that automates a single repetitive task for one team — usually lands in the $4k–$15k range if it's scoped tightly. A lead-qualification flow, a reporting summarizer, a custom audit tool. Two to four weeks of build time. Often the highest ROI work, and the work most consultancies don't want because it's too small to mark up.

A customer-facing AI feature integrated into an existing site or app — a smart search, a docs assistant trained on real content, a configurator — typically runs $15k–$50k. The cost isn't the model. The cost is the design work, the data plumbing, and the rounds of iteration after real users get their hands on it.

A platform-level rebuild with multiple agents, evals, retrieval, and ongoing oversight is where the $80k–$250k quotes come from. Sometimes that price is honest. Often it isn't. I've watched two of those projects get scoped down to $12k after a real conversation about the underlying need, which was something I wrote about earlier.

The reason quotes vary so wildly isn't that the work is mysterious. It's that most AI shops are pricing for the buyer's anxiety, not the build. If a manufacturing client believes AI is exotic, the price reflects that belief. The actual labor is closer to a well-scoped web project than to anything novel.

A few things that consistently inflate the number:

The vendor charges a "discovery" phase before they'll even quote. That phase is sometimes useful, but more often it's a way to get the client emotionally committed before the real number lands. I prefer a free conversation, a written brief, and a fixed quote — which is roughly how I structure engagements.

The build assumes a frontier model when a smaller open one would do. Or assumes a custom-trained model when prompting a hosted one would do. Both of those mistakes can 5x the cost.

There's a "platform" being built when really one workflow needs fixing. The smaller, more boring version of the project almost always ships sooner and gets used more.

If you want a benchmark on the broader Canadian SMB picture, Statistics Canada has been tracking AI adoption rates among small businesses, and the numbers are still small. Most of the cost gap I see is between what shops quote and what owners are actually willing to spend on something they don't yet trust. That trust gap is the real budget question, not the dollar figure.

The shortest version: if a quote is more than 10x what your gut says it should be, the vendor is solving a different problem than the one you described.