PIPELINEGuide
Do AI training yourself or have it done?
Much of AI training can be built in-house — the question is whether it pays off. When internal effort makes sense, where the limit is, and which approach is the most expensive.
Building AI training yourself pays off when the project stays small, someone in your business has time for it, and no one depends on it running on a specific day. As soon as other systems need to interact or someone is liable if it fails, external implementation is usually cheaper — the most expensive route is the half-finished one.
01 — In-house effort
Build yourself or have it built?
- Building yourself makes sense when someone in the business has the time and interest, the project stays small, and no one depends on it being live by a specific date.
- Ready-made platforms get you to a first result quickly, but hit limits where custom processes, custom data, or integrations with existing systems come into play.
- Having it done pays off as soon as AI training needs to communicate with other systems, as soon as someone is liable if it doesn't work, or as soon as internal effort becomes more expensive than external implementation.
- The most expensive path is the halfway one: built in-house for months on the side, then abandoned and rebuilt externally. If you decide on in-house effort, set a time budget and an abort point.
- Hybrid approach: Concept and setup externally, maintenance internally. This is often the most economical route for AI training — provided the handover is documented.
02 — Requirements
What you need for AI training
- A clearly defined trigger. Not “we should do something with AI,” but a process that demonstrably costs time or orders today.
- Existing content or data. AI training works with what's already there. The more complete the starting point, the shorter the setup.
- Access to the systems involved. Whoever manages the credentials needs to be involved from the start — this is, in our experience, the most common cause of delays.
- One decision-making contact person. One, not three.
- Willingness to refine after launch. The first weeks in real operation show what was missing in the concept. That's normal and accounted for.
03 — Calculation
How to calculate it
Four numbers are enough: How often does the process occur? How long does it take? What does an hour cost internally? And what does the solution cost — one-time plus operation over three years?
An example: A process that occurs twice a week and takes 40 minutes each time ties up around 69 hours per year. At an internal hourly rate of 45 euros, that's roughly 3,100 euros per year locked in there. If a solution reduces this effort by two-thirds, it often pays for itself — depending on the actual quote — within one to two years. We'll give you the exact figure for your case after the initial meeting.
This calculation is deliberately conservative: it only accounts for the time saved, not the errors avoided or the orders that come through due to faster response. In practice, the benefit is usually higher — but you shouldn't count on it before you've measured it.
04 — Questions
Frequently asked questions
Do you also cover industry-specific applications?
Yes, as far as known in advance. Bring your typical tasks — quote texts, protocols, customer correspondence — and we'll practice on exactly those instead of generic examples.
Won't that be outdated after three months?
The tools change, the mindset doesn't. The focus is on when such a system is appropriate and how you verify its output — that remains valid even if the interface looks different.
Does the EU AI Act require training?
For businesses that use AI systems, there is an obligation to ensure adequate AI competency among the people working with them. A documented training is the easiest way to demonstrate compliance.
Do we get materials?
Yes: the slides, a collection of proven prompts for your tasks, and the usage policy as an editable document.
What if individual employees don't want to?
That happens and it's not a disaster. We train everyone equally, but no one is forced to use it — experience shows that changes on its own once colleagues see the benefits.
Can we do this online as well?
Yes, then usually in two half-days instead of one full day — concentrated screen work over eight hours doesn't work well.
Do our people need prior knowledge?
No. We start from zero and divide the exercises according to prior knowledge. Experience shows that every team has both extremes.
05 — Decision
How to move forward
The most affordable next step is a conversation, not a quote. Twenty minutes is usually enough to clarify whether a project makes sense, what scope it involves, and whether we're the right fit.
If we're not, we'll say so. An honest no costs less than a project you abandon after three months — for both sides.
Next step
Let's talk briefly about whether this makes sense for you.
A twenty-minute conversation is usually enough to clarify whether a project makes sense. If not, we'll say so — that's cheaper for both sides than an offer nobody needs.