Sector
Where every algorithm has to be explainable to the person it was applied to.

Public organizations answer to citizens, not customers, and that difference runs all the way down. A decision supported by a model has to be explainable to the person it was applied to, defensible to a council or a supervisory body, and traceable long after the person who built it has moved on. The Dutch algorithm register exists precisely because this is now expected rather than optional.
The EU AI Act sharpens it further. Several typical public uses fall in the high-risk category, which comes with duties for documentation and for human oversight by people with the right competence. Competence is the part organizations most often forget to arrange.
And the workforce is unusually varied: policy advisors, service desk staff, planners, inspectors, drivers. A single generic course reaches none of them properly, while procurement rules make it hard to keep changing supplier until you find one that fits.
The behavior a public organization actually needs is this: someone who can explain a model-supported decision to the person it was applied to, in language that person follows, and who knows which decisions may never be automated at all. Under the EU AI Act, organizations must take measures that support this kind of competence.
Building it takes knowledge of what has to be documented and who oversees a model, skill in the tools your people already have, practiced in the browser on your own processes and cases, and the judgment to spot where automation genuinely helps and where it would harm the people it is meant to serve. A policy advisor, a planner and a service desk lead each need a different version of that, which is what the persona framework is for.
Adoption has to outlast a project budget, so champions and community are built in from the start and ownership passes to your own organization at the end. Growth is measured from a baseline before the start and benchmarked against other organizations, a defensible figure for an accountability document rather than an attendance list.
We work with public organizations including Provincie Limburg.
Across all our clients, cohorts finish at 80% completion over the last twelve months and more than 10,000 learners, against 46% for learners who paid for a MOOC.
Our Data & AI Skills Framework is what lets a program be aimed at a policy advisor, a planner and a board member separately, and it is what turns "we trained people" into a measured skill level you can put in an accountability document.
Course completion
over the last twelve months
Learners
have been through our programs
Average skill growth
Measured pre vs post, never self-reported
These are the personas we train in this sector.