AI upskilling for employees and executives
AI upskilling as a hackathon, hands-on on a real case, with a certificate and prototype. Process, formats and honest limits. Ready to start in 1 week.
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Your team does not learn the right AI tools on a practice dataset. In the same window of time, it builds a solution for a real case from your own operation. AI upskilling is a facilitated build path that ends with a working prototype and a documented competence record, not an attendance list. We plan scope, challenges, roles, data, tool access and schedule together so your upskilling can be ready to start within a week.
AI upskilling is a structured qualification in which employees and executives build confident use of AI tools. At Corporathon, this happens hands-on on a real use case, so the result is a usable prototype and a documented competence record, not just course knowledge without provable application.
The problem this upskilling solves
Most training budgets flow into formats whose effect nobody can prove afterwards. It is rarely a lack of willingness among employees. It is four gaps that a course syllabus does not cover.
- The material never reaches the desk. An example prompt from the training does not fit your own, often sensitive report. Between the exercise and the real case sits a gap nobody bridges.
- HR has no provable output. After the seminar, a certificate of attendance remains. Leadership's question about impact cannot be answered with it.
- Executives stay on the sidelines. If leadership does not touch AI themselves, it stays a side topic for the team. Role modelling only comes from doing it yourself.
- Nothing carries on. On the Monday after the training, daily work is unchanged, because no artefact was created that anyone can use.
AI upskilling as a hackathon reverses the order. Instead of learning first and maybe applying it later, every team works on a real case from the first hour. Learning happens through building, and that is why the skill stays.
What the upskilling covers, specifically
This is not a developer course. It is a guided build path for business teams who cannot code and do not need to. Participants work with Cursor, Lovable, n8n, Gamma, Figma Make, Claude Code and custom GPTs on their own data. Facilitation keeps the focus on a clearly scoped learning goal that translates into a visible result.
A run consists of four building blocks that build on each other:
- 1Learning goal and challenge scoping. An upskilling intention becomes a real, tightly scoped use case with a named user and a desired output. Not "AI basics", but for example "turn 40 weekly proposal PDFs automatically into a structured comparison table".
- 2Tool workshop. Before building starts, each group learns exactly the tools its case needs. No tool zoo, just the right stack for the learning goal.
- 3Build phase. The teams build with guidance. We sit alongside, unblock issues, show the next step and keep the prototype's scope clear.
- 4Pitch, evidence and handoff. Each team shows its result, names open assumptions and hands it to an owner. In parallel, the documentation of the competence measure is created for each participant.
Benefits and goals
The goal is not a nice course evaluation on Friday. The goal is that HR has evidence, leadership has impact, and the business unit has a tool in hand.
- A working artefact that belongs to you and keeps running, instead of slides.
- Practical AI competence that emerged on a real work case and therefore sticks.
- A documented AI competence measure as a building block for Article 4 of the EU AI Act.
- A provable transfer from the upskilling into daily work that HR and leadership can follow.
Who it fits, and who it does not
Honest fit saves both sides time. The upskilling is the stronger lever when the left column applies. If not, we say so openly.
| Good fit when | Not the best fit when |
|---|---|
| a team has real, recurring friction (manual reports, slow customer replies, scattered knowledge) | you only want general AI awareness for a large plenary |
| HR needs provable evidence with application | a plain attendance confirmation without a result is enough |
| data and tool access can generally be approved | real data must never be touched for legal reasons under any circumstances |
| executives want to build along and set an example | leadership wants to deliberately stay out of it |
Services and deliverables
- Upfront scoping with a learning goal and challenge scope per group.
- A curated tool stack per challenge, including access.
- A facilitated build sprint with guidance throughout.
- At least one working prototype per team (automation, dashboard, custom GPT, app prototype or workflow).
- A handoff document per prototype with owner, access, open risks, acceptance criterion and next step.
- A certificate and documented AI competence measure per participant, prepared for HR and funding evidence.
Related course
Anyone who wants to build the AI manager role in the company will find the matching AI Manager Programme in our course overview.
Formats as offer cards
Spark
- What you get: 1 day, a focused prototype, tool workshop, handoff document, certificate plus documented AI competence measure.
- You work with: one Corporathon facilitator, the right stack for one challenge (e.g. n8n plus a custom GPT).
- Ideal for: up to 10 participants, a team that needs a first provable upskilling win.
- Your investment: on request.
Ignite (recommended)
- What you get: 2 days, several challenges in parallel, several prototypes, a handoff per team, broader qualification across the area.
- You work with: several facilitators, a curated stack per challenge (Lovable, n8n, Cursor, Gamma, Claude Code).
- Ideal for: 10 to 15 participants, a department that wants to use AI competently across several processes.
- Your investment: on request.
Blaze
- What you get: 3 to 5 days, several teams, deeper, production-close prototypes, handoff with a clear implementation path.
- You work with: a facilitator team, the full tool stack, an optional link to a follow-on implementation sprint.
- Ideal for: 15+ participants, several departments, companies with a company-wide upskilling goal.
- Your investment: on request.
Teams from Adobe, YOYABA, Onventis and NavVis have worked with us. Prices on request for now; the scope depends on team size, number of challenges and desired depth of handoff.
AI upskilling vs. classic training
| Criterion | Classic training/course | Corporathon AI upskilling |
|---|---|---|
| Output | Certificate, attendance confirmation | Certificate plus a working prototype you keep |
| Learning mode | Lectures, slides, example prompts | hands-on with real data and tools |
| Transfer into daily work | unclear without transfer measurement | visible through the prototype, usage and handoff |
| Evidence for HR | attendance | a competence measure with a provable result |
| Proof of ROI | hardly provable | a tangible artefact as the starting point for your own measurement |
| Time to first result | weeks to months | ready to start in 1 week, result depending on scope |
The table compares ways of working, not providers. It deliberately contains no invented percentages. Reliable figures only emerge once you have your own baseline.
How the upskilling can pay off (a model, not a customer figure)
An honest ROI view does not use a borrowed case figure, but your own numbers. The model has three inputs and one formula.
- Time per week for a recurring manual task, for example reporting.
- The share a prototype realistically takes off that task.
- Internal hourly rate times the number of people affected.
Formula: *hours saved per week × hourly rate × 45 working weeks × people − one-off cost of the upskilling and the follow-up weeks*. A worked example as a model. If reporting costs four hours per person per week and a prototype takes off half of that, that is two hours. At an internal rate of 60 euros and ten people affected, that is 2 × 60 × 45 × 10, so 54,000 euros a year in freed-up capacity, against which you can honestly weigh the investment. We do exactly this calculation in the discovery call with your real numbers, not ours.
Interactive upskilling rollout planner: /en/ki-weiterbildung/tools/rollout-planer/.
Social proof
Teams from Adobe, YOYABA, Onventis and NavVis have worked with us. We show their names and logos as references and, where approved, workshop photos and public feedback. We deliberately publish concrete figures on adoption or time saved only once the source, method and period are documented and approved.
Everything at /en/case-studies.
The process as an animated timeline, in 1 week
| # | Step | Owner | Output |
|---|---|---|---|
| 1 | Intro call | Corporathon + sponsor | clarified goal, rough scope, date |
| 2 | Tools and challenges call | Corporathon + team leads | scoped challenges, tool choice per challenge |
| 3 | Finalising information and data | Client (IT, data protection) | approved data access, documented limits |
| 4 | Hackathon preparation | Corporathon | prepared environments, access, schedule |
| 5 | Tool workshop | Corporathon + teams | teams can operate their stack |
| 6 | Hackathon sprint | Teams (guided) | working prototypes |
| 7 | Result pitches and handoff | Teams + owner | shown results, handoff documents, evidence |
Your Corporathon, in just 1 week.
30-minute discovery call: clarify the need, pick a challenge, set the schedule.
The calendar is embedded via Cal.com and only loads external content once you ask for it.
Frequently asked questions
Short answers to the questions that come up most before booking.
An online course conveys knowledge that fades quickly without application. Upskilling as a hackathon trains on a real project, so the skill stays and a prototype emerges with direct use in daily work. HR also gets provable evidence.
In many cases, yes. The format is set up as workplace training with evidence and documentation. Which grants or education vouchers fit depends on the federal state and company size, and we clarify this in the first conversation. Details at /en/ki-weiterbildung-foerderung.
From small teams to over 15 people. Spark fits up to 10 participants, Ignite 10 to 15, Blaze 15 and more. We set the right scope in the discovery call.
No. The whole point is that business teams build with AI tools without classic programming. We choose the stack so the challenge is solvable without prior knowledge.
We clarify data access and limits with your IT and data protection team before the start. Only what is approved gets used, and the limits are documented.
Yes. Everyone receives a certificate, and unlike a plain seminar, a self-built prototype stands behind it. A certificate plus hands-on proof, not just a piece of paper.
The upskilling can document a practical AI competence measure and so contribute to satisfying Article 4. It is not an official certificate and does not guarantee automatic compliance. The company must assess the adequacy of its overall programme by role and risk.