AI-driven production of content for courses and competences

We have helped a number of organisations to use artificial intelligence in the production of academic content, courses and training materials. The aim has been to make production faster, more structured and more scalable without reducing quality or professional precision.

Among the customers we have helped are: ScaleAQ, Career academy, Nordic Aesthetics Academy, SenZie, The VINN Foundation, Zinus Power, mf.

 

From subject knowledge to structured learning content

Many organisations possess considerable expertise internally but lack an effective methodology for transforming it into pedagogically structured content.

By using different AI models, we have established production runs where we:

  • Convert existing documentation (PDF, PowerPoint, procedures, technical descriptions) into structured course content
  • Generates learning objectives based on professional foundation
  • Prepares module structure and progression
  • Suggests practice tasks and control questions
  • Improves and adapts language to target audience
  • Standardise pedagogical structure

AI is used here as a production assistant that streamlines the work of professionals and editors.

Use of different AI models - the right model for the right task

In the projects, we have used several language models, depending on:

  • Customer security requirements
  • Sensitivity of the data basis
  • Need for structure vs. creativity
  • Language and terminology

We've worked with both API-based models and hybrid setups, where AI is combined with structured professional data. In some projects, we have also used RAG principles to ensure that the content is generated based on the customer's own documents and terminology.

This means that the result is not generic but customised to the business.

Tangible benefits for customers

Through AI-enabled production, customers have achieved:

  • Significant reduction in production time
  • Faster conversion from course content to finished course
  • More consistent pedagogical structure
  • Lower cost per course module
  • Easier updating when regulations or procedures change
  • Ability to scale course production without increasing staffing levels

For several of the organisations, this has been crucial to being able to launch new courses quickly in the market.

Customised for different industries

The projects have spanned:

  • Industry and aquaculture (ScaleAQ)
  • Energy and technical infrastructure (Zinus Power)
  • Expertise and training activities (Karriereakademiet AS)
  • Non-profit organisations and foundations (Stiftelsen VINN)
  • Professional and service-based organisations (SenZie, NA.Academy)

The approach has always been the same: We combine technology understanding, pedagogical structure and AI models to turn subject expertise into scalable learning.

AI as a production engine not a replacement for professional expertise

An important principle in all the projects is that AI does not replace professionals. It frees up time.

The subject matter experts are still responsible for quality assurance and decision-making. KI handles:

  • Structure
  • Language check
  • Division
  • First draft
  • Standardisation

This results in a more efficient and professional production process.

A new standard for content production

For organisations working with competence development, courses or documentation, AI represents a structural improvement, not just a technical innovation.

By strategically utilising different AI models, we've helped our customers establish a more forward-thinking, scalable and cost-effective way of producing content.