## The Impact of Artificial Intelligence on Malta’s Labor Market ## Source details **Canonical URL:** [The Impact of Artificial Intelligence on Malta’s Labor Market](https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025008.pdf) ## Other formats - [Markdown version](/-/media/files/publications/selected-issues-papers/2025/english/sipea2025008.pdf.md) - [Structured JSON version](/-/media/files/publications/selected-issues-papers/2025/english/sipea2025008.pdf.json) --- ### Abstract and overview - AI and Generative AI models have advanced from automating routine tasks to performing complex cognitive functions, processing vast amounts of data, recognizing patterns, and making decisions. - Mapping occupational labor market micro data for Malta with measures of exposure and complementarity to AI indicates Malta is slightly less susceptible to AI job displacement than other advanced economies, but certain groups face greater risk. - Groups at greater risk: women, younger workers, and people with high school degrees only. ### Context - AI systems today routinely exceed human performance on standard benchmarks and new multimodal models can generate coherent text in dozens of languages, process audio, and explain photographs or memes. - As AI use expands, it can reshape jobs across a broad range of skills and sectors, yielding productivity gains but also potential job displacement during transitions. ### Infrastructure, human capital, and digital preparedness - Public funding and strategies: - Authorities allocate €196 million or 1.0 percent of 2023 GDP from EU funds for digital transformation. - Malta has a 2021-2027 Smart Specialization Strategy and a National AI Strategy; 80 percent of the existing AI strategy is completed and an updated AI strategy is being prepared. - IMF AI Preparedness Index (AIPI) assessment: - Malta aligns broadly with the average of advanced economies across “Regulation and Ethics,” “Human Capital and Labor Market Policies,” “Innovation and Economic Integration,” and “Digital Infrastructure.” - Digital skills and intensity: - 63 percent of the working age population have basic or above-basic digital skills. - Maltese companies’ digital intensity is relatively high compared to the EU-27 average. - AI use in firms (2023, excluding agriculture, fishing, mining, and the financial sector): - 13.2 percent of companies in Malta used at least one AI technology. - 83 percent of AI-using companies have more than 50 employees. - Sector shares of AI use: information and communication 35.3 percent; administrative and support service activities 12.4 percent; manufacturing 10.1 percent; wholesale and retail trade 9.4 percent; accommodation and food services 7.6 percent. - Barriers to broader adoption: - Lack of relevant expertise, high costs, and system incompatibility—challenges significantly higher than the EU average—suggesting potential labor and skill shortages and financial constraints. ### Labor market exposure and complementarity to AI - Malta’s economic structure: - Professional, scientific, and technical activities; trade; travel, accommodation, food services; and public services account for roughly half of economic output and two-thirds of employment. - Methodology summary: - Exposure measure based on Felten et al (2021) linking AI applications to workplace skills and occupations. - Complementarity measure follows Pizzinelli et al (2023), adding social, ethical, and physical context. - Categories: High Exposure and High Complementarity (HEHC), High Exposure and Low Complementarity (HELC), Low Exposure and High Complementarity (LEHC), Low Exposure and Low Complementarity (LELC). - Applied to Malta’s 2023 Labor Force Survey micro data with approximately 10,000 observations across 40 occupations, 21 economic activities, 5 age groups, gender, 4 educational attainment groups, income, and 3 country-of-birth groupings. - Key findings on exposure and displacement risk: - Around 60 percent of the labor market of Malta is highly exposed to AI. - Approximately 30 percent of the labor market is in the High Exposure and Low Complementarity category and thus at risk of job displacement—broadly similar to other advanced economies. - Malta exhibits slightly higher complementarity than other advanced economies, implying both lower susceptibility and higher potential productivity gains contingent on complementary skills and roles. - Distributional vulnerabilities: - Gender: Approximately 41 percent of women employees fall into the High Exposure and Low Complementarity category, compared to 27 percent of men. - Education: Tertiary education is associated with very high complementarity; 40 percent of those with only a high school degree are in the High Exposure and Low Complementarity category. - Age and income: Young people under 30 and those with low and lower-middle incomes are more at risk of job displacement. - Nationals vs immigrants: No major differences in the High Exposure and Low Complementarity category between Maltese nationals and immigrants. ### Conclusions and policy considerations - Summary conclusions: - Malta is well-prepared digitally to harness AI, with advanced digital infrastructure, high digital intensity in companies, and strong digital skills among people. - The labor market of Malta is slightly less susceptible to AI-related job displacement than other advanced economies due to higher complementarity, but approximately one-third of the labor force is at risk of job displacement. - Vulnerable groups: women, young workers, and people with only high school degrees. - A mitigating factor: Malta’s already tight labor market. - Policy priorities and recommendations: - Prioritize reskilling and upskilling through the education system and life-long learning. - National Education Strategy 2024-30 and the Lifelong Learning Strategy 2023-30 are pillars of this approach. - The Enterprise Skills Development Scheme supports training for existing and new employees; authorities could review both the size of support and target groups. - Advance private sector adoption, especially among SMEs: - Digital Decade Strategic Roadmap 2023-30 and a digitalization grant (covering 50 percent of expenses up to a maximum of €50,000) support SME digitalization. - Recommendations include lowering the administrative burden of accessing public support schemes and continuing to roll out e-Government to improve private sector adoption and efficiency. ### Annex: measuring exposure and complementarity to AI - Exposure to AI: - Felten et al. (2021) link common AI applications (e.g., image recognition, image generation, reading comprehension, language modelling, translation, speech recognition) to workplace skills and occupations using O*NET; the index measures overlap between AI capabilities and job skills weighted by importance and complexity. - Complementarity to AI: - Pizzinelli et al. (2023) build an index from O*NET ‘work contexts’ and ‘skills’, adding physical and social context, reflecting settings where societies may limit unsupervised AI use due to decision criticality and error consequences (e.g., health professionals, judges, certain technical experts and operators). - Combined conceptual framework: - Exposure and complementarity create a 2x2 matrix using medians as thresholds: HEHC, HELC, LEHC, LELC. The HELC (High Exposure and Low Complementarity) quadrant represents occupations at higher risk of job displacement. *Source: IMF Selected Issues Paper SIP/2025/008 (Section 1), prepared by Thomas Gade; completed December 17, 2024.* ### Section 1 ### The Impact of Artificial Intelligence on Malta’s Labor Market ### Abstract and Overview - Artificial Intelligence (AI) and Generative AI models have advanced from automating routine tasks to performing complex cognitive functions, processing vast amounts of data, recognizing patterns, and making decisions. - Mapping occupational labor market micro data for Malta with measures of exposure and complementarity to AI indicates Malta is slightly less susceptible to AI job displacement than other advanced economies, but certain groups face greater risk. - Groups at greater risk: women, younger workers, and people with high school degrees only. ### Context - AI systems today routinely exceed human performance on standard benchmarks and new multimodal models can generate coherent text in dozens of languages, process audio, and explain photographs or memes. - As AI use expands, it can reshape jobs across a broad range of skills and sectors, yielding productivity gains but also potential job displacement during transitions. ### Infrastructure, Human Capital, and Digital Preparedness - Authorities allocate €196 million or 1.0 percent of 2023 GDP from EU funds for digital transformation. - Malta has a 2021-2027 Smart Specialization Strategy and a National AI Strategy; 80 percent of the existing AI strategy is completed and an updated AI strategy is being prepared. - IMF AI Preparedness Index (AIPI) assessment: Malta aligns broadly with the average of advanced economies across “Regulation and Ethics,” “Human Capital and Labor Market Policies,” “Innovation and Economic Integration,” and “Digital Infrastructure.” - Digital skills and intensity: - 63 percent of the working age population have basic or above-basic digital skills. - Maltese companies’ digital intensity is relatively high compared to the EU-27 average. - AI use in firms (2023, excluding agriculture, fishing, mining, and the financial sector): - 13.2 percent of companies in Malta used at least one AI technology. - 83 percent of AI-using companies have more than 50 employees. - Sector shares of AI use: information and communication 35.3 percent; administrative and support service activities 12.4 percent; manufacturing 10.1 percent; wholesale and retail trade 9.4 percent; accommodation and food services 7.6 percent. - Barriers to broader adoption: lack of relevant expertise, high costs, and system incompatibility—challenges significantly higher than the EU average—suggesting potential labor and skill shortages and financial constraints. ### Labor Market Exposure and Complementarity to AI - Malta’s economy is diversified: professional, scientific, and technical activities; trade; travel, accommodation, food services; and public services account for roughly half of economic output and two-thirds of employment. - Methodology: - Exposure measure based on Felten et al (2021) linking AI applications to workplace skills and occupations. - Complementarity measure follows Pizzinelli et al (2023), adding social, ethical, and physical context. - Categories: High Exposure and High Complementarity (HEHC), High Exposure and Low Complementarity (HELC), Low Exposure and High Complementarity (LEHC), Low Exposure and Low Complementarity (LELC). - Applied to Malta’s 2023 Labor Force Survey micro data with approximately 10,000 observations across 40 occupations, 21 economic activities, 5 age groups, gender, 4 educational attainment groups, income, and 3 country-of-birth groupings. - Key findings on exposure and displacement risk: - Around 60 percent of the labor market of Malta is highly exposed to AI. - Approximately 30 percent of the labor market is in the High Exposure and Low Complementarity category and thus at risk of job displacement—broadly similar to other advanced economies. - Malta exhibits slightly higher complementarity than other advanced economies, implying both lower susceptibility and higher potential productivity gains contingent on complementary skills and roles. - Distributional vulnerabilities: - Gender: Approximately 41 percent of women employees fall into the High Exposure and Low Complementarity category, compared to 27 percent of men. - Education: Tertiary education is associated with very high complementarity; 40 percent of those with only a high school degree are in the High Exposure and Low Complementarity category. - Age and income: Young people under 30 and those with low and lower-middle incomes are more at risk of job displacement. - Nationals vs immigrants: No major differences in the High Exposure and Low Complementarity category between Maltese nationals and immigrants. ### Conclusions and Policy Considerations - Summary conclusions: - Malta is well-prepared digitally to harness AI, with advanced digital infrastructure, high digital intensity in companies, and strong digital skills among people. - The labor market of Malta is slightly less susceptible to AI-related job displacement than other advanced economies due to higher complementarity, but approximately one-third of the labor force is at risk of job displacement. - Vulnerable groups: women, young workers, and people with only high school degrees. - A mitigating factor: Malta’s already tight labor market. - Policy priorities and recommendations: - Prioritize reskilling and upskilling through the education system and life-long learning. - National Education Strategy 2024-30 and the Lifelong Learning Strategy 2023-30 are pillars of this approach. - The Enterprise Skills Development Scheme supports training for existing and new employees; authorities could review both the size of support and target groups. - Advance private sector adoption, especially among SMEs: - Digital Decade Strategic Roadmap 2023-30 and a digitalization grant (covering 50 percent of expenses up to a maximum of €50,000) support SME digitalization. - Recommendations include lowering the administrative burden of accessing public support schemes and continuing to roll out e-Government to improve private sector adoption and efficiency. ### Annex: Measuring Exposure and Complementarity to AI - Exposure to AI: - Felten et al. (2021) link common AI applications (e.g., image recognition, image generation, reading comprehension, language modelling, translation, speech recognition) to workplace skills and occupations using O*NET; the index measures overlap between AI capabilities and job skills weighted by importance and complexity. - Complementarity to AI: - Pizzinelli et al. (2023) build an index from O*NET ‘work contexts’ and ‘skills’, adding physical and social context, reflecting settings where societies may limit unsupervised AI use due to decision criticality and error consequences (e.g., health professionals, judges, certain technical experts and operators). - Combined conceptual framework: - Exposure and complementarity create a 2x2 matrix using medians as thresholds: HEHC, HELC, LEHC, LELC. The HELC (High Exposure and Low Complementarity) quadrant represents occupations at higher risk of job displacement. *Source: IMF Selected Issues Paper SIP/2025/008 (Section 1), prepared by Thomas Gade; completed December 17, 2024.* ### Section 2 ### sipea2025008 - Section 2 ### Citation - Li. 2023. "Labor Market Exposure to AI: Cross-Country Differences and Distributional Implications." IMF Working Paper 2023/216, International Monetary Fund, Washington, DC. *Source: sipea2025008 - Section 2* --- _Source: https://www.imf.org/-/media/files/publications/selected-issues-papers/2025/english/sipea2025008.pdf_