Nicole Koch, managing director aprentas

Artificial intelligence is transforming work processes at a rapid pace, especially in innovative industries. This raises a key question for vocational training: how can a proven system remain stable while being flexible enough to keep pace with technological developments?

The world of work has always been evolving. What is new today is less the change itself and more its speed. Digital technologies, and artificial intelligence in particular, are accelerating change across many sectors.

Stable and agile

Swiss vocational training is internationally regarded as a model of success and an important competitive advantage. It is built on stable structures: around 250 clearly defined occupations form its foundation, and reforms are jointly supported by the federal government, the cantons, and organisations from the world of work, and are regularly reviewed. This stability creates trust and planning certainty. At the same time, the world of work is changing in some cases faster than training regulations can be adapted. The system therefore needs to evolve.

A multi-tiered approach could be a solution: broad foundational qualifications across occupations as the basis of training, supplemented by more flexible modules or additional qualifications. Vocational continuing education could then build on these. In this way, the traditional occupational principle can be further developed without being abandoned.

What skilled workers need to be able to do in the AI age

Even as AI takes on more tasks, solid professional knowledge remains indispensable. Only those who understand the technical fundamentals can correctly interpret AI outputs, identify errors, and critically evaluate results. At the same time, the question arises: which knowledge is permanently essential, and which content is losing its relevance? This discussion is not always easy for experts.

Alongside professional knowledge, cross-disciplinary skills remain central. The so-called 4Cs—critical thinking, creativity, communication, and collaboration—have long shaped vocational training. In the AI era, these skills are evolving: collaboration increasingly includes cooperation between humans and machines. New skills are also becoming important, such as formulating precise prompts and critically evaluating AI responses. Simply using AI is no longer enough.

Social and personal skills continue to form the foundation: reliability, self-organisation, a sense of responsibility, and empathy. In practice, it is clear that professional competence gets young people into the workforce—social competence keeps them there.

Designing learning spaces with purpose

With increasing automation, another question arises: how can learning spaces be designed to ensure that skills continue to develop? Learning takes time—and, above all, opportunities to practice. Skills are not acquired by watching or through ready-made results, but through hands-on experience, comparison, and critical reflection.

At the same time, AI offers new possibilities. Digital learning assistants could provide more personalised support to learners, adapting to their knowledge level and learning pace.

The key message remains: automation saves time, but training requires time. Vocational education is an investment. If new technologies are integrated effectively while preserving space for meaningful learning, vocational training will remain a crucial factor for the success of the business location, even in the age of AI.