The short answer
There is no single price, because «implementing AI» can mean very different things: from training a team to use existing tools well to building an assistant connected to the company's data. What you can do is understand what drives the cost and start with the part that carries the least risk.
What drives the cost
- Scope: improving one task is not the same as transforming a whole area.
- The state of the data: if information is organised, the project is shorter; if it is spread across emails and spreadsheets, it must be prepared first.
- Integration: connecting AI to the ERP, CRM or website adds work, but it is usually what makes it get used.
- Licences and usage: many tools charge per user or by volume, and it is worth estimating that before scaling.
- Training and change: a system the team doesn't understand doesn't get used, however good it is.
The costs people forget
Maintenance, human review of what the AI produces, updating the information it works with, and compliance with the EU AI Act and GDPR. They are not big items, but if they aren't planned they show up later as a surprise.
How to start with little risk
First, a focused assessment that tells you where it pays off and where it doesn't. Then a small prototype on a single process, with a before-and-after metric. Only if the numbers work do you scale. That way the budget grows with results, not with promises.
If you want to know what it would cost in your case, the starting point is a one-hour conversation to understand what you want to solve.
