Understanding, not access
People need to judge when AI helps, where it fails, and when a human decision is required.
In-house AI education / gateB Academy
Lead AI yourself.Don’t just use it.
A structured, role-specific learning path that turns AI curiosity into capability your organisation can own — and evidence you can show.
Meet the Academy
90 sec
A learning path.An organisational capability.
Josef AbelHead of AI Consulting & Transformation
Video placement preview — plays only on click, never with sound by default. Main film 90–105 sec, header cut 45–60 sec. Final film, poster and subtitles pending.
The organisational challenge
Access to AI is notthe same as capability.
Almost everyone now has AI tools. Far fewer organisations have the shared understanding, the working habits and the governance to use them well. That gap is a learning problem — not a licensing problem.
Where organisations stand
Companies using AI in at least one business area88%
Companies that have reached AI maturity1%
Source: McKinsey, State of AI 2025. Figures taken from the internal Academy concept — to be confirmed and referenced before publication.
Shared practice, not isolated experiments
Individual experimentation only becomes capability once it reaches shared processes and responsibilities.
Role-specific relevance
A controller, a recruiter and an architect need different evidence that AI is worth their time.
How the Academy works
Learn it. Try it.Put it to work.
Three stages, one direction. Each stage changes what people can do — and leaves something behind that the organisation can use.
A shared starting line.
Before anyone automates anything, everyone needs the same words for the same things. This stage removes the guesswork — what the technology does, where it breaks, and which questions to ask before it touches real work.
The learning path
Six courses.Different starting points.
Nobody needs all of it. Tell us what should change in your organisation and the path configures itself — then adjust it with us in the Readiness Session.
02 / Suggested learning path
path 01 · foundation
A common language.
Understand first, decide second. A shared starting point for teams that want to place AI realistically before investing in it.
This path creates a common basis without forcing everyone into the same deep-dive course.
Validate this path with us
The courses
Named for what they give you.
Internal track numbers stay in the background. Open a course to see who it is for and what participants can do afterwards.
One concrete example
This is whatparticipants build.
A real AI workflow from the Academy — not a demo. Press play, or step through it. Note where the work stays human: that boundary is part of the learning.
Step 01 · Trigger
Month-end close completes
What the AI does
What stays human
Built by participants, not for them. Workflows like this are the hands-on result of the Agentic AI courses — designed, bounded and documented by the people who will run them.
See which course builds this
What people take away
Not a certificate.Something that works.
Pick a course. The left side shows a situation most teams recognise. The right side shows the artefact participants leave with — a prompt set, a workflow, an architecture sketch, a roadmap.
Before / a familiar situationunclear
After / on the deskusable
The outcome is not course completion. It is the judgement, prompt set, workflow, architecture sketch or roadmap someone can take straight back into the organisation — and show to the people who approved the budget.
capability made visible
AI Readiness Session
Start with whereyou actually are.
A low-threshold diagnostic entry point. Four steps, one documented result — and a learning path recommendation you can take into your own organisation.
A short conversation
We discuss your context, your roles and what should be different in six months.
Step oneA structured assessment
Current AI use, capability levels and organisational readiness, captured in a consistent framework.
Step twoA diagnostic report
A documented view of where you stand — written to be shared internally, not just discussed.
Step threeYour recommended path
Which courses, for which roles, in which order — with the reasoning behind each choice.
Step fourMade for the people who have to make the case.
Most AI learning programmes are researched by L&D, HR and People & Culture — and approved by someone else. The Readiness Session is designed to give you something concrete to put on that table.
What you walk away with
Four things you can forward
- A written readiness picture of your organisation
- A recommended learning path per role and level
- An indicative scope: courses, formats and duration
- How the programme relates to AI literacy obligations under Art. 4 EU AI Act
The EU AI Act reference describes the programme’s contribution to AI literacy. Final wording requires legal review before publication.
Why gateB
Practical experience.Translated into learning.
The Academy draws on gateB’s project work across AI, CRM, marketing technology, customer engagement and transformation.
Grounded in real work
Courses are built from the processes, decisions and implementation questions we meet in client projects — not from a generic curriculum.
Technology-independent
The capability and the organisational need come first. No learning path is designed around a single vendor’s product.
Continuity into implementation
Enablement does not stop at the last slide. Participants leave able to assess, plan and lead the next step themselves.