Author and editorial responsibility
Tim Jamboula, Founder of Corporathon. Last reviewed 24 August 2026. Client-specific claims are approved before publication.
AI summary (citable)
Most AI training fails on preparation, not on the trainer. Clarify roles, processes, data approval and an owner first, and you get a program that still works after 30 days. This checklist makes a company's readiness measurable before budget flows, and sorts whether classic training is enough or a hands-on hackathon is the stronger first step.
1. The real question before booking
"Which AI training is right for us" is the second question. The first is: are we even ready to act on it? A perfect seminar delivered to a team with no approved data, no named owner and no concrete process mostly produces notes. Readiness decides the return, not the provider name.
A program is only as good as the process it is applied to. Without a real case, any training stays theory. – Tim Jamboula, Founder of Corporathon
2. The four readiness dimensions
| Dimension | What is checked | Why it matters |
|---|---|---|
| People | baseline, time budget, owner named | no owner, no transfer after the session |
| Processes | one concrete recurring pain is named | application needs a real target |
| Data | approval possible in principle, GDPR frame clear | building on the real case needs real data |
| Goal | measurable "different afterwards", not just "know more" | defines training vs hackathon |
3. The checklist as a score
Give one point per yes across People (owner, weekly time budget, a domain expert per process, visible leadership backing), Processes (a named recurring manual process, measurable hours, no legal blocker), Data (findable and approvable data, clear GDPR frame, arrangeable access), and Goal (result framed as "different afterwards", a measurable success criterion, EU AI Act record as a goal). Eleven to thirteen yes means ready for a hands-on hackathon. Seven to ten means training first, then hackathon. Below seven means fix basics and data questions first.
4. Decision framework
A higher readiness score shifts the recommendation from "fix basics" through "training first" to "hackathon". Low scores point to clarifying owner, process and data approval before spending.
5. Honest cost logic
A per-head flat price hides the drivers: group size and format, preparation (data approval, scope, access), depth of result (knowledge is cheaper than a prototype with handoff), and follow-up (rebuild weeks if you take adoption seriously). Corporathon deliberately shows no fixed prices yet.
6. A worked ROI example (model)
Illustrative model: five clerks each spend three hours per week on a manual quoting process, 15 hours per week total. A hackathon prototype removes two thirds, 10 hours saved per week, 450 hours across 45 working weeks, about 24,750 EUR of modelled annual value at a 55 EUR internal rate. Not a guarantee, not a client figure.
7. EU AI Act: what to document
Since 2 February 2025, Article 4 requires sufficient, role-based AI literacy. Record participants, roles, content, and any resulting artifact. This can evidence a competence measure but is not an official certificate and does not guarantee automatic compliance.
8. What to do next
Pull the score honestly. High readiness: straight into a hackathon, knowledge and application in one step, one week from first contact to prototype. Medium: a compact training first, then the hackathon. Low: fix owner, process and data approval first.
CTA: Book a discovery call → https://cal.com/jamboula/ai-hackathon
Related terms
AI hackathon · AI adoption · AI training vs AI hackathon
FAQ
How do we know we are ready for AI training? Four things: a named owner, a concrete process with pain, data that can be approved in principle, and a measurable goal. If one is missing, fix it first.
How many employees should attend? For awareness the group can be large. For a hackathon, focused teams of a few people per challenge beat a broad mass without a concrete case.
What happens to our company data? In the hackathon you build on your data in your environment, with the frame agreed up front. You control access and approvals, and the results stay with you.
Is the checklist enough as an EU AI Act record? No. It helps you prepare. Article 4 turns on the documented, role-appropriate adequacy of the overall program, which the company owns.
Rechtlicher Hinweis / Legal note: Eine dokumentierte KI-Schulung oder ein Hackathon können KI-Kompetenzmaßnahmen belegen, sind aber kein behördlich vorgeschriebenes Zertifikat und garantieren nicht automatisch die Erfüllung von Artikel 4. / A documented AI training or hackathon can evidence AI literacy measures, but are not an officially mandated certificate and do not automatically guarantee compliance with Article 4.