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Method

The method behind the analysis

What is AI transformation?

AI transformation measures the degree to which AI is reshaping a given occupation. The concept comes from a research project by Andrej Karpathy (March 2026) that systematically scored 342 occupations against the Bureau of Labor Statistics' detailed job descriptions. The score doesn't predict whether the job disappears — it indicates whether the way the work is done is changing.

The score is nota prediction of job loss, a share of automatable hours, or a measure of current AI adoption. It's a directional indicator of where AI will have the most impact — not how much. Sector-level validation is supplemented with data from Anthropic's report “Labor market impacts of AI” (March 2026) and the ILO's assessment (March 2026), which emphasise that exposure scores capture “technological susceptibility, not labour-market outcomes.”

Denmark and AI — key figures

Denmark is a European frontrunner on AI adoption:

  • 42% of Danish companies use AI — more than double the EU average of 20%. (Statistics Denmark, 2025)
  • 37% of companies with 10–49 employees now use AI — up from 10% in 2023. (Statistics Denmark)
  • 70% of Danish AI use is limited to ChatGPT for simple text generation. (Dansk Erhverv)
  • 74% of Danish SMB leaders cite employees' skills gap as the biggest barrier to AI adoption. (Dansk Erhverv)

The numbers tell a clear story — Danish companies are willing to use AI, but most are stuck at the most basic application. The gap between AI's capability and actual utilisation is enormous — and that gap is exactly where the value sits.

How the analysis works

The analysis follows a structured four-step method:

  1. 01

    Industry → role template

    Your industry defines a typical role distribution, scaled to your headcount.

  2. 02

    Role adjustment

    You tune the distribution so it matches your actual team.

  3. 03

    AI exposure score per role

    Each role is matched against Karpathy's 342-occupation dataset and classified into four overlap tiers (from Gradual change to Fundamental change).

  4. 04

    Industry benchmark

    Your team composition is compared with the typical role distribution for your industry to show whether you are more or less exposed than average.

We deliberately don'tshow hours, money, or percentages. Karpathy's score measures the degree to which AI is reshaping an occupation — not a linear share of automatable hours. A 9/10 score doesn't mean 90% of work time can be automated; it means the role is facing fundamental change in how the work is done.

What does it mean for your business?

The result is a transformation curve for your team. Roles with Major shift or Fundamental change are in the same zone as translators, bookkeepers and software developers — occupations where the way the work is done is already fundamentally different from two years ago. Not because the jobs disappeared, but because they were transformed. The employees who adapted are thriving. This is about helping your team do the same.

About Qorpera

Qorpera is how your team becomes expert at working with AI — on their actual jobs. The platform connects your tools, gives every employee an AI companion that learns their work, and builds competence through real daily decisions. No technical prerequisites. No generic courses. AI that knows your business, helping your team.

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