AI Training & Enablement
Practical training for teams that have to use AI themselves. Three tracks: leadership briefing, engineering upskilling, and role-specific practical modules. Experienced trainers, material tailored per engagement.
Who it is for
Teams inside a client organisation who need to use AI themselves. Engineering teams upskilling into agent design and LLM application development. Non-technical teams who need practical, role-specific AI literacy.
- Leadership (no-hype briefing)
- Engineering teams
- Non-technical teams (analysts, planners, case handlers, policy officers)
Problem it solves
Two gaps show up repeatedly: engineering can read an LLM API doc but does not yet know how to design, evaluate, and operate an agent; non-technical teams hear "AI can do your job" and either fear or overclaim it. Both tracks address this.
- "Our engineers want to build agents but don't know where to start."
- "Our team needs to use AI practically, not another YouTube video."
- "The board wants to understand what AI can and cannot do."
What a typical engagement looks like
| Phase | Duration | Output |
|---|---|---|
| Leadership briefing | Half day | One-page internal memo, 5 concrete opportunities, 2 risks |
| Engineering upskilling | 2 to 4 days | Team members with shipped prototypes and a shared playbook |
| Role-specific practical | 1 to 2 days | Measurable task-level time savings documented per participant |
Team: Trainers from our build team, with the same experience as in Custom AI Agents and Solution Architecture.
Approach
- Practical over theoretical. Every module uses your own systems and data.
- Honest. "This is not going to work for task X" gets said when true.
- Tailored per engagement, not boilerplate.
- Bilingual: Dutch or English.
Proof
TODO(sanne): name organisations Integratio has trained, or anonymised by sector, with a measurable outcome.
What this service is not
- Not a catalogue AI-literacy course.
- Not a certification programme.
- Not a recorded-video library.