## 1. AI Preparedness and Digital Indicators

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---

### Context and summary
- Artificial Intelligence (AI) and Generative AI models have evolved from automating routine tasks to performing complex cognitive functions, processing vast amounts of data, identifying patterns, and making decisions.
- The speed of AI adoption by workers and firms is described as unprecedented.
- The chapter maps occupational labor market micro data from the EU Labor Force Survey with measures of exposure and complementarity to AI to assess impacts across occupations, sectors, and demographic groups in Denmark.

### Government initiatives and digital preparedness
- Strategic Approach to AI (December 2024) — four initiatives:
  - Creation of a Digital Taskforce to promote AI use in the public sector, aiming to reduce administrative burdens, improve public service quality, and “free up” labor in the public sector in coordination with municipalities and regions.
  - Creation of a Center for Artificial Intelligence in Society to guide businesses and government agencies on responsible AI use.
  - Initiatives to facilitate development of AI models aligned with Danish norms (transparency and accountability) using Danish text data that will be made freely accessible to companies.
- Denmark ranks second worldwide on the IMF’s AI Preparedness Index (AIPI).
- Digital skills in Denmark exceed those in other European countries for both simple and complex tasks.
- Eurobarometer perceptions:
  - 78 percent of respondents think AI will benefit companies.
  - 55 percent think AI will benefit society as a whole.
  - 45 percent believe AI will benefit Danish employees.
  - Most Danes view the use of AI in the workplace positively (Eurobarometer 2024).

### AI adoption by firms (2024)
- Overall adoption:
  - About 25 percent of Danish companies with 10 or more employees were using at least one AI technology in 2024.
- AI use by task (Denmark, 2024):
  - Production of written text or spoken language: 18 percent (natural language generation)
  - Analysis of text (text mining): 17 percent
  - Workflow automation, machine learning for data analysis, image recognition and processing also widely used (percentages for these tasks reported in figure panels).
- AI use by sector (share of Danish enterprises using AI, 2024):
  - Information and communication: 70 percent
  - Professional, scientific and technical activities: 45 percent
  - Manufacturing: 22 percent
  - Transportation and storage: 21 percent
- Use of AI by firm size (2024):
  - Firms with 250 or more employees: over 60 percent using AI
  - Medium firms (50–249 employees): about 40 percent using AI
  - Small firms (less than 50 employees): 20 percent using AI
- Reported firm-level outcomes from AI adopters: Workflows; Products or services; Earnings; Decision making; Development of new products or services.

### Measuring exposure and complementarity to AI (methodology)
- Exposure index foundation: Felten et al. (2021) — link 10 applications of AI to 52 occupational abilities using O*NET data; occupations are combinations of the 52 abilities weighted by importance and complexity.
- Complementarity index foundation: Pizzinelli et al. (2023) — use O*NET ‘work contexts’ and ‘job zones’, identifying 11 relevant work contexts grouped into six components: communication, responsibility, physical conditions, criticality, routine, and skills.
- Conceptual matrix and classification:
  - Occupations categorized as ‘High Exposure and High Complementarity’ (HEHC), ‘High Exposure and Low Complementarity’ (HELC), and ‘Low Exposure’ (LE) using medians across exposure and complementarity values.
  - HE-LC interpreted as higher risk of job displacement.
- Application scope: Measures applied to the 2023 EU Labor Force Survey across 119 occupations, 19 economic activities, 3 age groups, gender, 3 educational attainment groups, 3 income groups, and 2 ‘country of birth’ groupings.

### Key labor-market findings (exposure and complementarity)
- Exposure and displacement risk:
  - Over 60 percent of Danish workers face high exposure to AI.
  - Danish high-exposure share is 9 percentage points higher than in other European countries.
  - Among highly exposed workers, two-thirds hold jobs with high complementarity to AI.
  - One-third of highly exposed workers have low complementarity, largely concentrated in business and administration professionals.
  - Approximately 20 percent of the Danish labor market is at risk of job displacement (HELC).
  - 36 percent of the Danish workforce is unlikely to be affected by AI (LE), concentrated in personal care, personal services, or as laborers.

### Sectoral differences and public vs private sector
- Public sector employment facts:
  - The public sector accounts for approximately 1/3 of Danish employees.
  - Public administration: 6 percent of total employment
  - Education: 9 percent of total employment
  - Healthcare: 19 percent of total employment
- Private sector risk:
  - Approximately 25 percent of the Danish private sector workforce faces risk of job displacement (HELC).
  - Most at-risk private sector occupations include business and administration professionals, sales, and information and communication technology specialists.
- Public sector risk and complementarities:
  - Approximately 13 percent of the public sector workforce faces risk of job displacement (HELC).
  - More than half of public sector employees are anticipated to benefit from AI due to high complementarity, particularly in education and healthcare.
  - Potential for labor reallocation within public administration (e.g., business and administration professionals, general clerks).
- International comparison:
  - Potential job displacement in Denmark’s public sector is higher than in other Nordics but lower than in the rest of Europe.

### Demographic and skill-related differences
- Gender:
  - Nearly 75 percent of the female workforce is highly exposed to AI; a substantial majority of these women are in jobs with high complementarity (education, healthcare).
  - Over 50 percent of the male workforce has low exposure to AI; men are more likely to work in roles such as laborers or drivers.
  - Women in Denmark are expected to gain more from AI adoption compared to women in other European countries.
- Education and income:
  - Tertiary-educated workers: 67.5 percent HEHC.
  - An estimated 20 percent of high-educated workers could be at risk of job displacement (HELC).
  - An estimated 25 percent of high-income workers could be at risk of job displacement (HELC).
  - Low-educated workers and low-income earners have a low risk of job displacement.
- Age and immigration:
  - The impact of AI is not expected to differ significantly across age groups.
  - Natives are anticipated to benefit more than immigrants; immigrants tend to occupy jobs with low exposure to AI.

### Occupations highlighted by exposure/complementarity (examples)
- High complementarity (examples): Primary School and Early Childhood Teachers; Nursing and Midwifery Professionals; Science and Engineering Professionals; Health Professionals.
- High exposure and low complementarity (examples): Business and Administration Professionals; Shop Salespersons; General Office Clerks.
- Low exposure (examples): Transport and Storage Labourers; Domestic, Hotel and Office Cleaners and Helpers; Drivers and Mobile Plant Operators.

### Policy-relevant observations and recommendations
- Strengths and risks:
  - Denmark’s strong digital infrastructure, well-educated labor force, and innovation and legal frameworks underpin high AI preparedness.
  - Rapid firm-level adoption concentrated in larger firms suggests potential scaling and diffusion challenges for small and medium-sized enterprises.
- Public sector policy guidance:
  - AI represents an opportunity to free up resources in the public sector by increasing efficiency, reducing administrative costs, and enhancing public services.
  - 13 percent of public sector employees hold low-complementarity positions, presenting potential efficiency gains given anticipated labor supply shortages, in particular for health and personal care professionals.
  - Recommendation: Accelerate adoption of AI in the public sector while continuing to review legal and technical barriers and ensuring sound ethical principles.
- Skills, flexicurity, and monitoring:
  - Denmark’s flexicurity model (labor market flexibility, strong social security measures, active training programs, and a highly educated workforce) makes Denmark resilient to AI challenges.
  - Rapid adoption of AI could lead to faster- and larger-than-expected job displacement; labor market impacts should be closely monitored.
  - Policy priorities:
    - Continue efforts to increase the supply of workers with relevant skills.
    - Strengthen digital literacy at school, including AI, as envisaged in the new reform in general school education.
    - Ensure high-complementarity workers continuously update their digital skills as AI technologies evolve rapidly.
- Supporting SMEs and regulatory environment:
  - Authorities launched SME:Digital to assist SMEs in digitally enhancing operations; the program offers grants for private consulting to assess digitalization potential, identify suitable solution providers, and support implementation.
  - Danish companies often encounter complex regulations and administrative burdens at the EU level when implementing new technologies, which could hinder AI adoption.
  - Recommendation: Ensure a clear and updated legal framework and seek scope to ease regulatory burdens to facilitate AI uptake by firms.

### Reasons enterprises do not use AI (Percent)
- Lack of relevant expertise: 14.9
- Lack of clarity about legal consequences: 8.6
- Concerns regarding violation of data protection and privacy: 7.5
- Availability or quality of the necessary data: 6.8
- Ethical considerations: 6.1
- Incompatibility with existing equipment, software or systems: 6.1
- Costs: 3.3
- Not useful for Enterprise: 2.9

_Italic: Source: IMF staff report content unit sipea2025119_

### 1. AI Preparedness and Digital Indicators _______________________________________________ 3

### 1. AI Preparedness and Digital Indicators

### Context and summary
- Artificial Intelligence (AI) and Generative AI models have evolved from automating routine tasks to performing complex cognitive functions, processing vast amounts of data, identifying patterns, and making decisions.
- The speed of AI adoption by workers and firms is described as unprecedented.
- The chapter maps occupational labor market micro data from the EU Labor Force Survey with measures of exposure and complementarity to AI to assess impacts across occupations, sectors, and demographic groups in Denmark.

### Government initiatives and digital preparedness
- The government published the Strategic Approach to AI in December 2024 with four initiatives:
  - Creation of a Digital Taskforce to promote AI use in the public sector, aiming to reduce administrative burdens, improve public service quality, and “free up” labor in the public sector in coordination with municipalities and regions.
  - Creation of a Center for Artificial Intelligence in Society to guide businesses and government agencies on responsible AI use.
  - Initiatives to facilitate development of AI models aligned with Danish norms (transparency and accountability) using Danish text data that will be made freely accessible to companies.
- Denmark is ranked second worldwide on the IMF’s AI Preparedness Index (AIPI).
- Digital skills in Denmark exceed those in other European countries for both simple and complex tasks.
- Eurobarometer perceptions:
  - 78 percent of respondents think AI will benefit companies.
  - 55 percent think AI will benefit society as a whole.
  - 45 percent believe AI will benefit Danish employees.
  - Most Danes view the use of AI in the workplace positively (Eurobarometer 2024 results summarized in the chapter).

### AI adoption by firms (2024)
- About 25 percent of Danish companies with 10 or more employees were using at least one AI technology in 2024.
- AI use by task (Denmark, 2024):
  - Production of written text or spoken language: 18 percent (natural language generation)
  - Analysis of text (text mining): 17 percent
  - Workflow automation, machine learning for data analysis, image recognition and processing also widely used (percentages for these tasks reported in figure panels).
- AI use by sector (share of Danish enterprises using AI, 2024):
  - Information and communication: 70 percent
  - Professional, scientific and technical activities: 45 percent
  - Manufacturing: 22 percent
  - Transportation and storage: 21 percent
- Use of AI by firm size (2024):
  - Firms with 250 or more employees: over 60 percent using AI
  - Medium firms (50–249 employees): about 40 percent using AI
  - Small firms (less than 50 employees): 20 percent using AI
- Danish firms that adopted AI report positive effects on workflows, products and services, earnings, and decision making (figure lists “Workflows, Products or services, Earnings, Decision making, Development of new products or services”).

### Measuring exposure and complementarity to AI
- Exposure and complementarity measures:
  - Based on Felten et al. (2021) occupational exposure index and on Pizzinelli et al. (2023) extension to include social, ethical, and physical contexts to derive complementarity.
  - Occupations categorized into: “High Exposure and High Complementarity” (HEHC), “High Exposure and Low Complementarity” (HELC), and “Low Exposure” (LE).
- Measures applied to the 2023 EU Labor Force Survey across 119 occupations, 19 economic activities, 3 age groups, gender, 3 educational attainment groups, 3 income groups, and 2 ‘country of birth’ groupings.

### Key labor-market findings (exposure and complementarity)
- Over 60 percent of Danish workers face high exposure to AI (share of workers classified as highly exposed).
- Danish high-exposure share is 9 percentage points higher than in other European countries.
- Among highly exposed workers, two-thirds hold jobs with high complementarity to AI (e.g., teaching, science and engineering, health professionals).
- One-third of highly exposed workers have low complementarity, largely concentrated in business and administration professionals.
- Approximately 20 percent of the Danish labor market is at risk of job displacement (HELC).
- 36 percent of the Danish workforce is unlikely to be affected by AI (LE), concentrated in personal care, personal services, or as laborers.

### Sectoral differences and public vs private sector
- Private sector:
  - Approximately 25 percent of the Danish private sector workforce faces risk of job displacement (HELC).
  - Most at-risk private sector occupations include business and administration professionals, sales, and information and communication technology specialists.
- Public sector:
  - Approximately 13 percent of the public sector workforce faces risk of job displacement (HELC).
  - More than half of public sector employees are anticipated to benefit from AI due to high complementarity, particularly in education and healthcare.
  - Potential for labor reallocation within public administration (e.g., business and administration professionals, general clerks).
- Compared internationally:
  - Potential job displacement in Denmark’s public sector is higher than in other Nordics but lower than in the rest of Europe.

### Demographic and skill-related differences
- Gender:
  - Nearly 75 percent of the female workforce is highly exposed to AI; a substantial majority of these women are in jobs with high complementarity (education, healthcare).
  - Over 50 percent of the male workforce has low exposure to AI; men are more likely to work in roles such as laborers or drivers.
  - Women in Denmark are expected to gain more from AI adoption compared to women in other European countries.
- Education and income:
  - Tertiary-educated workers: 67.5 percent HEHC (figure data for tertiary education employment exposure and complementarity profile shown).
  - An estimated 20 percent of high-educated workers could be at risk of job displacement (HELC).
  - An estimated 25 percent of high-income workers could be at risk of job displacement (HELC).
  - Low-educated workers and low-income earners have a low risk of job displacement.
- Age and immigration:
  - The impact of AI is not expected to differ significantly across age groups.
  - Natives are anticipated to benefit more than immigrants; immigrants tend to occupy jobs with low exposure to AI.

### Occupations highlighted by exposure/complementarity (examples from figures)
- Occupations with high complementarity (examples): Primary School and Early Childhood Teachers; Nursing and Midwifery Professionals; Science and Engineering Professionals; Health Professionals.
- Occupations with high exposure and low complementarity (examples): Business and Administration Professionals; Shop Salespersons; General Office Clerks.
- Occupations with low exposure (examples): Transport and Storage Labourers; Domestic, Hotel and Office Cleaners and Helpers; Drivers and Mobile Plant Operators.

### Policy-relevant observations (from chapter text and government actions)
- Denmark’s strong digital infrastructure, well-educated labor force, and innovation and legal frameworks underpin high AI preparedness.
- Public initiatives (Digital Taskforce; Center for Artificial Intelligence in Society; development of Danish-text-based AI models) aim to support responsible AI adoption and to capture productivity gains while addressing risks.
- Rapid firm-level adoption concentrated in larger firms suggests potential scaling and diffusion challenges for small and medium-sized enterprises.

_Italic: Prepared by Théodore Renault (EUR); chapter content from "THE IMPACT OF ARTIFICIAL INTELLIGENCE ON DENMARK’S LABOR MARKET" (June 18, 2025)._

### 11.      Denmark is well-prepared to reap the benefits of AI. Denmark is digitally equipped to

### 11.      Denmark is well-prepared to reap the benefits of AI. Denmark is digitally equipped to

### Digital preparedness and labor-market exposure
- Denmark’s digital infrastructure is advanced, AI usage in companies is high, and Danes have strong digital skills.
- Compared to other European countries, Denmark has a higher share of workers with high-complementarity occupations and a lower share of low-exposed workers.
- Nevertheless, Denmark faces similar vulnerabilities as other European nations regarding adverse labor market impacts, with approximately one-fifth of its workforce at risk of job displacement.
- Lack of relevant skills is identified as an important reason companies are not using AI.

### Public sector opportunities and risks
- AI represents an opportunity to free up resources in the public sector by increasing efficiency, reducing administrative costs, and enhancing public services.
- 13 percent of public sector employees hold low-complementarity positions, presenting potential efficiency gains given anticipated labor supply shortages, in particular for health and personal care professionals.
- Recommendation: Accelerate adoption of AI in the public sector while continuing to review legal and technical barriers and ensuring sound ethical principles.

### Flexicurity, skills policy, and monitoring
- Denmark’s flexicurity model (labor market flexibility, strong social security measures, active training programs, and a highly educated workforce) makes Denmark resilient to AI challenges.
- Rapid adoption of AI could lead to faster- and larger-than-expected job displacement; labor market impacts should be closely monitored.
- Policy priorities:
  - Continue efforts to increase the supply of workers with relevant skills.
  - Strengthen digital literacy at school, including AI, as envisaged in the new reform in general school education.
  - Ensure high-complementarity workers continuously update their digital skills as AI technologies evolve rapidly.

### Supporting AI adoption in the private sector, especially SMEs
- Authorities launched SME:Digital to assist SMEs in digitally enhancing operations; the program offers grants for private consulting to assess digitalization potential, identify suitable solution providers, and support implementation.
- Danish companies often encounter complex regulations and administrative burdens at the EU level when implementing new technologies, which could hinder AI adoption.
- Recommendation: Ensure a clear and updated legal framework and seek scope to ease regulatory burdens to facilitate AI uptake by firms.

### Reasons enterprises do not use AI (Percent)
- Lack of relevant expertise: 14.9
- Lack of clarity about legal consequences: 8.6
- Concerns regarding violation of data protection and privacy: 7.5
- Availability or quality of the necessary data: 6.8
- Ethical considerations: 6.1
- Incompatibility with existing equipment, software or systems: 6.1
- Costs: 3.3
- Not useful for Enterprise: 2.9

### Annex I — Measuring exposure and complementarity to AI (methodology)
- Measuring Exposure to AI: Felten et al. (2021) link 10 applications of AI to 52 occupational abilities using O*NET data; occupations are combinations of the 52 abilities weighted by importance and complexity.
- Measuring complementarity to AI: Pizzinelli et al. (2023) develop an index using O*NET ‘work contexts’ and ‘job zones’, identifying 11 relevant work contexts grouped into six components: communication, responsibility, physical conditions, criticality, routine, and skills.
- Conceptual matrix: Occupations categorized as ‘High Exposure and High Complementarity’ (HEHC), ‘High Exposure and Low Complementarity’ (HELC), and ‘Low Exposure’ (LE) using medians across exposure and complementarity values; HE-LC interpreted as higher risk of job displacement.

### Annex II — Employment by occupation and sector (key facts)
- The public sector accounts for approximately 1/3 of Danish employees.
  - Public administration: 6 percent of total employment
  - Education: 9 percent of total employment
  - Healthcare: 19 percent of total employment
- The share of workers in the health sector is higher than in other European countries, including the Nordics.
- Manufacturing represents 12 percent of total employment.
- Notable occupations: many Danish employees work as personal care workers, primary school teachers, childcare workers; physical and engineering science technicians are Denmark’s second-largest occupation; administrative professionals constitute a significant share of the workforce.

*Source: IMF staff report content unit sipea2025119*

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_Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025119.pdf_