How much does AI implementation cost?
By Michael Olufuwa, founder of Tiadara
AI implementation typically costs less than businesses fear and more than vendors admit. Expect a fixed discovery fee in the low thousands, a build priced to the outcome, and ongoing model-usage and maintenance costs that are modest but real. The biggest hidden cost is a project that never reaches production.
Discovery cost
Discovery is a fixed-fee engagement in the low thousands. In one to two weeks we map the problem, audit the data and systems, and define the first outcome we would ship. You get a written recommendation, a rough build estimate, and a clear go / no-go decision — with no pressure to proceed.
The point of discovery is not to produce a deck. It is to remove the uncertainty that makes build pricing meaningless, and to give you a real basis for deciding whether AI is the right tool for the job.
Build cost
The build is priced to the outcome and the scope, not open-ended time. A small internal tool that connects one API and one workflow might be a few thousand. A production agent with multiple integrations, review steps, and monitoring will be more. The key is that the price maps to something measurable, not to hours spent.
Because AI work changes once it touches real data, we prefer outcome-priced milestones over rigid fixed-price contracts. That lets us adapt without either side taking on unlimited risk.
Run cost
Running an AI system has three parts: model usage, hosting, and maintenance. For most business tools, model usage is modest — often tens to a few hundred pounds a month. If you are processing large volumes of documents or running always-on agents, it can be higher, but it should still be predictable.
Hosting depends on where the system lives and what uptime it needs. Maintenance is the one vendors skip: models drift, APIs change, and someone has to keep the system healthy. We always quote run cost honestly and document who owns it.
The hidden cost
The cost that never appears on a vendor quote is the project that never ships. A proof of concept that demos well, wins internal praise, and then dies in a drawer has consumed the full budget and delivered nothing. It is more common than most teams admit.
The best way to control total cost is to scope tightly, build against real data from week one, and agree ownership before handover. That is how you turn a budget into a live system instead of a slide deck.
Frequently asked questions
Why do vendors hide AI implementation costs?
Vendors often hide costs because the real total depends on messy details — data quality, integrations, maintenance, model usage — that are hard to estimate upfront. Some quote a low day rate and let the total drift. A better vendor breaks costs into discovery, build, and run, and tells you what each covers.
Is fixed-price or day-rate better for AI work?
Fixed-price works well for discovery, where the scope is contained. For the build, outcome-based pricing with clear milestones is usually better than either open-ended day rates or rigid fixed-price contracts, because AI work reveals unknowns once it touches real data.
What is the biggest hidden cost in AI implementation?
A project that never reaches production. A stalled AI implementation burns the full budget and delivers nothing. The fix is to scope to one measurable outcome, build against real data early, and agree who owns the system after handover.
If you want an honest estimate for an AI project — or a second opinion on a quote you have already received — we can help you break it down properly.
See how we run AI implementation →