Digitale Arbeitswelt – Chancen und Herausforderungen für Beschäftigte und Arbeitsmarkt
Der digitale Wandel der Arbeitswelt gilt als eine der großen Herausforderungen für Wirtschaft und Gesellschaft. Wie arbeiten wir in Zukunft? Welche Auswirkungen hat die Digitalisierung und die Nutzung Künstlicher Intelligenz auf Beschäftigung und Arbeitsmarkt? Welche Qualifikationen werden künftig benötigt? Wie verändern sich Tätigkeiten und Berufe? Welche arbeits- und sozialrechtlichen Konsequenzen ergeben sich daraus?
Dieses Themendossier dokumentiert Forschungsergebnisse zum Thema in den verschiedenen Wirtschaftsbereichen und Regionen.
Im Filter „Autorenschaft“ können Sie auf IAB-(Mit-)Autorenschaft eingrenzen.
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen
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Literaturhinweis
AI innovation and the labor share in European regions (2025)
Zitatform
Minniti, Antonio, Klaus Prettner & Francesco Venturini (2025): AI innovation and the labor share in European regions. In: European Economic Review, Jg. 177. DOI:10.1016/j.euroecorev.2025.105043
Abstract
"This paper examines how the development of Artificial Intelligence (AI) affects the distribution of income between capital and labor, and how these shifts contribute to regional income inequality. To investigate this issue, we analyze data from European regions dating back to 2000. We find that for every doubling of regional AI innovation, the labor share declines by 0.5% to 1.6%, potentially reducing it by 0.09 to 0.31 percentage points from an average of 52%, solely due to AI. This new technology has a particularly negative impact on high- and medium-skill workers, primarily through wage compression, while for low-skill workers, employment expansion induced by AI mildly offsets the associated wage decline. The effect of AI is not driven by other factors influencing regional development in Europe or by the concentration of the AI market." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Artificial intelligence adoption and workplace training (2025)
Zitatform
Muehlemann, Samuel (2025): Artificial intelligence adoption and workplace training. In: Journal of Economic Behavior & Organization, Jg. 238. DOI:10.1016/j.jebo.2025.107206
Abstract
"As artificial intelligence (AI) reshapes business processes, firms must adapt their training strategies to cultivate a skilled workforce. Using German establishment-level panel data from 2019 to 2023, this study analyzes how firms adjust their training strategies following AI adoption. Staggered difference-in-differences analysis shows that sustained AI adoption is associated with a 14% increase in new apprenticeships among training firms (intensive margin), but is not linked to the training decision (extensive margin). AI adoption is also associated with a modest increase in continuing training, with resources shifting toward high-skilled employees. The results align with AI as an automation innovation that reduces demand for simple skills as well as an augmentation innovation that increases demand for more advanced skills. The German dual apprenticeship system appears critical for firms aiming to build a future-ready workforce in the age of AI." (Author's abstract, IAB-Doku, © 2025 The Author. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Wie Roboter die betriebliche Beschäftigungsstruktur verändern (2025)
Zitatform
Müller, Steffen & Verena Plümpe (2025): Wie Roboter die betriebliche Beschäftigungsstruktur verändern. In: Wirtschaft im Wandel, Jg. 31, H. 1, S. 10-13. DOI:10.18717/wwfyns-ep75
Abstract
"Der Einsatz von Robotern verändert die Arbeitswelt grundlegend – doch welche spezifischen Effekte hat dies auf die Beschäftigungsstruktur? Unsere Analyse untersucht die Folgen des Robotereinsatzes anhand neuartiger Mikrodaten aus deutschen Industriebetrieben. Diese Daten verknüpfen Informationen zum Robotereinsatz mit Sozialversicherungsdaten und detaillierten Angaben zu Arbeitsaufgaben. Auf Basis eines theoretischen Modells leiten wir insbesondere positive Beschäftigungseffekte für Berufe mit wenig repetitiven, programmierbaren Aufgaben ab, sowie für jüngere Arbeitskräfte, weil diese sich besser an technologische Veränderungen anpassen können. Die empirische, mikroökonomische Analyse des Robotereinsatzes auf Betriebsebene bestätigt diese Vorhersagen: Die Beschäftigung steigt für Techniker, Ingenieure und Manager und junge Beschäftigte, während sie bei geringqualifizierten Routineberufen sowie bei Älteren stagniert. Zudem steigt die Fluktuation bei geringqualifizierten Arbeitskräften signifikant an. Unsere Ergebnisse verdeutlichen, dass der Verdrängungseffekt von Robotern berufsabhängig ist, während junge Arbeitskräfte neue Tätigkeiten übernehmen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Weiterbildungsungleichheit und technologischer Wandel: Nach IT-Investitionen steigt vor allem die Weiterbildungsquote der Höherqualifizierten (2025)
Zitatform
Müller, Christoph (2025): Weiterbildungsungleichheit und technologischer Wandel: Nach IT-Investitionen steigt vor allem die Weiterbildungsquote der Höherqualifizierten. (IAB-Kurzbericht 06/2025), Nürnberg, 8 S. DOI:10.48720/IAB.KB.2506
Abstract
"Betriebliche Weiterbildung soll dazu beitragen, die Fähigkeiten der Beschäftigten an neue Anforderungen anzupassen. Gerade im Zuge der digitalen Transformation der Arbeitswelt sind solche Anpassungen dringend erforderlich. Die vorliegende Analyse des Zusammenhangs zwischen Investitionen in digitale Technologien und innerbetrieblicher Weiterbildung zeigt: In Betrieben mit IT-Investitionen steigen die Weiterbildungsquoten der Beschäftigten mit qualifizierten Tätigkeiten; bei denjenigen mit einfachen Tätigkeiten ist dies im Mittel hingegen nicht der Fall." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
- Nach IT-Investitionen fallen die innerbetrieblichen Weiterbildungsquoten von Beschäftigten mit qualifizierten Tätigkeiten höher aus
- Anteil der Betriebe mit IT-Investitionen und innerbetriebliche Weiterbildungsquoten der Beschäftigten
- Veränderung der innerbetrieblichen Weiterbildungsquoten der Beschäftigten im Zuge von betrieblichen IT-Investitionen
- Betriebliche IT-Investitionen und innerbetriebliche Weiterbildungsquoten der Beschäftigten 2019
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Literaturhinweis
Digital transformation, employment change and the adaptation of regions in Germany (2025)
Zitatform
Neumann, Uwe (2025): Digital transformation, employment change and the adaptation of regions in Germany. In: Structural Change and Economic Dynamics, Jg. 73, S. 37-50. DOI:10.1016/j.strueco.2024.12.014
Abstract
"Digital change is often said to lead to large-scale job losses. Using data from administrative sources in Germany, this study examines the extent to which adaptation to digital change has affected regional employment growth and disparities over the past decade. The analysis confirms previous research according to which increases in productivity coincide with regional job growth rather than decline. Incorporating various indicators of digitalisation and automation into a model of industry-specific regional job growth shows that local labour markets with very different characteristics – regions with strong manufacturing clusters on the one hand and large cities on the other – have achieved employment growth despite high automation exposure. While the study highlights regional differentials with respect to the adaptation to technological change, less prosperous regions may face a much greater challenge in realising job creation potentials. The results argue against policy efforts aimed at “protecting” jobs from digitalisation and automation." (Author's abstract, IAB-Doku, © 2025 The Author. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Artificial intelligence and technological unemployment: Understanding trends, technology's adverse roles, and current mitigation guidelines (2025)
Nigar, Meher; Golder, Uttam ; Alam, Mohammad Jahangir; Hossain, Mohammad Kamal ; Juli, Jannatul Ferdous;Zitatform
Nigar, Meher, Jannatul Ferdous Juli, Uttam Golder, Mohammad Jahangir Alam & Mohammad Kamal Hossain (2025): Artificial intelligence and technological unemployment. Understanding trends, technology's adverse roles, and current mitigation guidelines. In: Journal of open innovation, Jg. 11, H. 3. DOI:10.1016/j.joitmc.2025.100607
Abstract
"As artificial intelligence (AI) and automation continue to reshape industries, concerns about technological unemployment are intensifying. This study employs a Systematic Literature Review (SLR) guided by the PRISMA framework to examine peer-reviewed literature from the Scopus database (2015–July 09, 2025). It identifies threecore themes: (1) trends in AI-induced labor displacement, including task automation, skill polarization, and industry-specific disruptions in sectors such as healthcare, education, and creative industries; (2) the adverse roles of AI technologies, particularly in affecting white-collar professionals, gig workers, and freelancers by increasing precarity and skill mismatches; and (3) existing mitigation strategies, including responsible AI guidelines proposed by governments, institutions, and firms aimed at balancing technological advancement with employment protection. While a growing body of policy responses encourages human-AI complementarity, current measures remain fragmented and insufficient to address the structural risks of workforce displacement. This study presents a comprehensive synthesis of the evolving relationship between AI and employment, highlighting key areas for further inquiry and policy development." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by ElsevierLtd on behalf of Prof JinHyo Joseph Yun.) ((en))
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Literaturhinweis
Just another cog in the machine? A worker‐level view of robotization and tasks (2025)
Zitatform
Nikolova, Milena, Anthony Lepinteur & Femke Cnossen (2025): Just another cog in the machine? A worker‐level view of robotization and tasks. In: Economica, Jg. 92, H. 368, S. 1101-1148. DOI:10.1111/ecca.70006
Abstract
"Technological change has led to a decline in the share of routine and physical jobs, and a rise in the share of abstract and social ones at the economy level. However, much less is known about how these trends unfold at the individual level. Do workers' tasks become more or less routine and physical? Do workers shift towards more social and abstract activities? This paper is the first to explore these questions in the context of robotization. We use survey data from 20 European countries to develop worker-level indices of physical, routine, abstract and social tasks, which we link to industry-level robotization exposure. Using instrumental variable techniques, we find that robotization reduces physically demanding tasks but increases routine tasks, while also limiting opportunities for cognitively challenging work and human interaction. This study provides a worker-centric perspective on the relationship between technology and task composition, revealing insights that aggregate analyses miss." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial intelligence, automation and employment dynamics: empirical evidence from G7 economies (2025)
Zitatform
Okur, Fatih & Enes Özdemir (2025): Artificial intelligence, automation and employment dynamics: empirical evidence from G7 economies. In: Journal of Economic Studies, S. 1-17. DOI:10.1108/jes-06-2025-0414
Abstract
"Purpose: This study examines how the rapid adoption of artificial intelligence (AI) and automation affects employment dynamics across G7 economies. While previous research has often focused on either AI or robotics in isolation, their combined and long-term effects on employment remain poorly understood. Addressing this gap is crucial for policymakers seeking to balance technological progress with labor market stability. Design/methodology/approach: Using a balanced panel dataset covering 2010–2024 for the G7 countries, thestudy investigates the relationships between AI investment (proxied by information and communication technology (ICT) investment), robot density (ROBOT), wages, productivity (PRD) and education spending (EDU), and their impact on employment. The analysis employs panel unit root and cross-sectional dependence tests, a panel autoregressive distributed lag (ARDL) framework estimated via the pooled mean group (PMG) estimator, and robustness checks using Driscoll–Kraay fixed effects, common correlatedeffects (CCE) estimators, country-specific regressions and Dumitrescu –Hurlin panel causality tests. Findings: The results reveal that AI investment has a significant negative effect on employment in the long run, whereas ROBOT shows a positive but context-dependent relationship. Wage levels are negatively associated with employment, while PRD shows only a modest positive influence. Education expenditure exhibits mixed behavior – positive in the short run but negative in the long run – suggesting potential misalignment with evolving labor market needs. Causality tests confirm a unidirectional link from AI investment to employment, underscoring its structural role in labor market change. Research limitations/implications: This study is limited by data availability, particularly the lack of detailed sectoral or occupational breakdowns across countries. As a result, it cannot fully capture the distributional effects of AI and automation across different worker groups. The use of proxies, such as ICT investment for AI, may not reflect the full scope of AI deployment. Despite these limitations, the findings highlight important macro-level dynamics and suggest that technological investments significantly shape employment trends. Future research should utilize micro-level data to explore sector-specific impacts, wage effects and labor force transitions in response to digital transformation. Practical implications: The findings suggest that without targeted policy interventions, increased AI investment may displace workers in the long run. Policymakers should prioritize reskilling, adapt education systems to evolving technological needs, and differentiate strategies across sectors and worker skill levels. Social implications: This study highlights the potential for AI and automation to reshape labor markets, with implications for income distribution, job security and social cohesion. The displacement of routine jobs may disproportionately affect low-skilled and vulnerable workers, increasing the risk of inequality and social exclusion. To prevent deepening divides, social policies must focus on equitable access to education, digital literacy and lifelong learning. Supporting workforce adaptability through inclusive training programs and social safety nets is essential. The results underscore the urgent need for collaborative efforts between governments, educational institutions and industries to ensure a socially sustainable digital transformation. Originality/value: This study is among the first to jointly analyze AI and robotics within a dynamic panel framework, offering new cross-country evidence on their heterogeneous employment effects in advanced economies. By integrating multiple estimation strategies and country-specific perspectives, the paper contributes to a more nuanced understanding of how technological transformation reshapes labor markets and highlights the institutional conditions that mediate these effects." (Author's abstract, IAB-Doku, © EmeraldGroup) ((en))
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Literaturhinweis
Job polarisation OR AND upgrading! Recent evidence from Europe (2025)
Zitatform
Otoiu, Adrian, Emilia Titan, Dorel Paraschiv & Daniela-Ioana Manea (2025): Job polarisation OR AND upgrading! Recent evidence from Europe. In: The Economic and Labour Relations Review, Jg. 36, H. 1, S. 257-270. DOI:10.1017/elr.2025.12
Abstract
"Based on recent evidence from Europe, the paper shows that polarization and upgrading are not mutually exclusive trends, but rather, simultaneously defined recent structural changes in employment. The results show that (a) the occupational structure shows a general shift towards high-skill jobs, (b) the prevailing upgrading patterns are often accompanied by job polarization, as the share of middle-skill jobs declines in most cases, and (c) while low-skill employment often outperforms middle-skill jobs, it has tended to decline. In addition to analysing trends for EU-27 countries with different levels of development for the latest available time periods, the article also shows that occupational upgrading patterns are rather intertwined with job polarisation and are compatible with both the Skill-Biased Technical Change (SBTC) and Routine-Biaszd Technical Change (RBTC) hypotheses. The employment dynamics of low-skill workers are uncertain, as they are not fully compatible with any theoretical model, thus pointing to the need for a finer understanding of changes in occupational structure, and the extent to which both polarization and upgrading are shaping the evolution of the labor force structure under the impact of (ongoing) technological change." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Future-oriented occupations in the EU: main features, employment conditions, and job strain (2025)
Parent-Thirion, Agnes; Wukovits-Votzi, Nora; Muller, Jessye;Zitatform
Parent-Thirion, Agnes, Nora Wukovits-Votzi & Jessye Muller (2025): Future-oriented occupations in the EU. Main features, employment conditions, and job strain. 51 S. DOI:10.2767/2953537
Abstract
"The way we work is changing due to developments associated with the digital and green transition as well as demographic change, as a driver of current and future labour shortages. As these transitions impact job content, tasks and processes, they will change how people work, the skills needed to carry out jobs, employment conditions, and, ultimately, dimensions of their job quality. These transition-related changes in occupations are of high relevance for workers, job applicants, and students training to join these occupations, as well as stakeholders, and policy makers, at the sectoral, national, and European levels. While their impacts are separately treated in this analysis, the green and digital transitions can further exacerbate labour shortages given the skill profiles required by related occupations." (Text excerpt, IAB-Doku) ((en))
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Literaturhinweis
Exploring the delicate relation between technological innovations and work quality: A study among civil servants (2025)
Zitatform
Peeters, Maria C. W., Jan Fekke Ybema, Pascale M. Le Blanc & Judith Plomp (2025): Exploring the delicate relation between technological innovations and work quality: A study among civil servants. In: Economic and Industrial Democracy, Jg. 46, H. 3, S. 851-873. DOI:10.1177/0143831x251347151
Abstract
"This study explores the delicate relation between technological innovations and work quality. It was conducted across various parts of the Dutch central government. The authors assessed how civil servants perceive changes in job demands, job resources and some relevant outcomes following the implementation of new technologies. Data were collected through an online Technology Monitor (TM) which was (at least partly) completed by 332 respondents. Results showed that employees perceived significant increases in various job demands, alongside a modest increase in the job resource autonomy after technology implementation. Additionally, civil servants who experienced more autonomy following new technology implementation reported higher levels of both work engagement and employability. In contrast, perceptions of increased workload were associated with more burnout symptoms. Interestingly, perceived increases in task variation were associated with fewer burnout symptoms, lower job insecurity and higher work engagement. These findings offer valuable insights for managers and HR professionals involved in managing technological transitions, emphasizing the importance of employee-centered strategies to safeguard and enhance the quality of work of civil servants." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Are artificial intelligence skills a reward or a gamble? Deconstructing the AI wage premium in Europe (2025)
Zitatform
Pouliakas, Konstantinos, Giulia Santangelo & Paul Dupire (2025): Are artificial intelligence skills a reward or a gamble? Deconstructing the AI wage premium in Europe. In: Eurasian business review, Jg. 15, H. 4, S. 1091-1128. DOI:10.1007/s40821-025-00302-0
Abstract
"Understanding the labor market impact of new, autonomous digital technologies, particularly generative or other forms of artificial intelligence (AI), is currently at the top of the research and policy agenda. Many initial studies, though not all, have shown that there is a wage premium to mostly technical AI skills in labor markets. Such evidence tends to draw on data from web-based sources and typically fails to provide insight into the mechanisms underlying the AI wage gap. This paper utilizes representative adult workforce data from 29 European countries, the second European skills and jobs survey, to examine wage differentials of the AI programmer workforce. The latter is uniquely identified as part of the workforce that writes computer programs using AI algorithms. The analysis shows that, on average, AI programmers enjoy a significant wage premium relative to a comparably educated or skilled workforce, such as programmers who do not yet write code using AI at work. Wage decomposition analysis further illustrates that there is a large unexplained component of such wage differential. Part of AI programmers’ larger wage variability can however be attributed to higher job-skill requirements, a propensity for remote work and a greater performance-based component in wage schedules. This indicates differences in the job design and performance management of the AI workforce." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Occupational Autonomy and Wage Divergence: Evidence From European Survey Data (2025)
Zitatform
Rabensteiner, Thomas & Alexander Guschanski (2025): Occupational Autonomy and Wage Divergence: Evidence From European Survey Data. In: BJIR, Jg. 63, H. 4, S. 696-713. DOI:10.1111/bjir.70003
Abstract
"Wages across occupations in Western Europe have diverged, resulting in increased wage inequality. However, existing theories such as routine-biased technological change (RBTC) or task offshoring fail to explain this trend. We propose a new explanation based on occupational autonomy. Autonomy measures workers' control and influence over their work process based on the tasks required in an occupation. Analysing individual-level data from the EU Survey of Income and Living Conditions, we reveal a rising autonomy wage premium, that is, higher wage growth for occupations with higher autonomy, which accurately predicts the observed occupational wage divergence. We also find that the autonomy premium increases more rapidly in countries and industries with greater employee monitoring and outsourcing, as well as in countries with declining minimum wages. These findings imply that low-autonomy occupations have been disadvantaged by recent socioeconomic trends that have altered power relations in the workplace. Notably, our analysis does not support previous explanations for occupational wage trends based on RBTC or task offshoring." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Die Hybridisierung von menschlichen und technischen Arbeitsleistungen mit Künstlicher Intelligenz als neuer Leittechnologie: Entwicklungen, Implikationen und Potenziale für menschengerechte Arbeit (2025)
Rehmer, Sabine; Juds, Maike; Fellmann, Michael; Menzel, Maren; Muehlan, Holger ; Röcker, Carsten; Dhiman, Hitesh;Zitatform
Rehmer, Sabine, Holger Muehlan, Maren Menzel, Maike Juds, Michael Fellmann, Hitesh Dhiman & Carsten Röcker (2025): Die Hybridisierung von menschlichen und technischen Arbeitsleistungen mit Künstlicher Intelligenz als neuer Leittechnologie: Entwicklungen, Implikationen und Potenziale für menschengerechte Arbeit. In: Zeitschrift für Arbeitswissenschaft, Jg. 79, H. 4, S. 525-533. DOI:10.1007/s41449-025-00489-y
Abstract
"Der Artikel untersucht die Hybridisierung menschlicher und technischer Arbeitsleistungen im Kontext Künstlicher Intelligenz (KI) als neuer Leittechnologie und analysiert ihre Entwicklungen, Implikationen und Potenziale für eine menschengerechte Arbeitsgestaltung. Ausgehend von der Beobachtung, dass KI zunehmend kognitive Tätigkeiten transformiert, wird mit dem Konzept des „Hybrid Man“ ein neues Menschenbild skizziert, das die enge Verschränkung von menschlicher und maschineller Intelligenz beschreibt. Damit einher gehen tiefgreifende Herausforderungen: Die Grenzen zwischen menschlicher und technischer Leistung verschwimmen, Verantwortungsfragen und rechtliche Unsicherheiten entstehen, während zugleich neue Anforderungen an Kompetenzen wie „AI Literacy“ sichtbar werden. Ebenso rücken Fragen nach Transparenz, Erklärbarkeit und Akzeptanz von KI-Systemen in den Vordergrund, die für Vertrauen und nachhaltige Integration entscheidend sind. Neben den Chancen zur Entlastung und Erweiterung menschlicher Fähigkeiten birgt die Hybridisierung Risiken wie Überwachungsdruck, Anpassungsstress und negative psychische Beanspruchungen. Vor diesem Hintergrund schlägt der Artikel mit dem Konzept des eudaimonischen Wohlbefindens („Eudaimonia“) ein normatives Kriterium für die Gestaltung zukünftiger Arbeit vor, das Wachstum, Sinnhaftigkeit, Authentizität und Exzellenz fördert. Ziel ist eine interdisziplinär fundierte, menschengerechte Arbeitswelt, die die Potenziale von KI nutzbar macht, ohne die psychische Gesundheit, Selbstwirksamkeit und Würde der Beschäftigten zu gefährden." (Autorenreferat, IAB-Doku)
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Literaturhinweis
European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure (2025)
Zitatform
Riccio, Federico, Jacopo Staccioli & Maria Enrica Virgillito (2025): European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure. (LEM working paper series / Laboratory of Economics and Management 2025/19), Pisa, 34 S. DOI:10.57838/sssa/02jp-b197
Abstract
"Does labor-saving technological change pose a threat to European employment, and if so, to what extent? This study investigates the degree of employment exposure to labor-saving technological change across NUTS-2 regions in Europe. We construct a cross-walked metric between the SOC and ISCO classification systems to adapt the direct measure of occupational exposure developed by Montobbio et al. (2024) for the US economy and apply it to the European context. This methodology enables us to generate detailed insights into the exposure of European occupations by leveraging the similarity rankings between technological classifications in the USPTO (CPCs) and task descriptions. To evaluate the transmission from occupational exposure to employment outcomes, we utilise data from the European Structure of Earnings Survey (EU-SES), thereby constructing exposure indices at both sectoral and regional levels. Finally, we examine the industrial and geographical diffusion of labor-saving technological change in recent years and provide robust econometric evidence indicating that low-wage regions, as well as deindustrialising areas heavily integrated into global value chains, are disproportionately vulnerable to the threat of substitution." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The impact of a decade of digital transformation on employment, wages, and inequality in the EU: a “conveyor belt” hypothesis (2025)
Richiardi, Matteo Guido ; Pelizzari, Lorenzo; Westhoff, Leonie ; Astarita, Caterina ; Khabirpour, Neysan; Fenwick, Clare; Ernst, Ekkehard ;Zitatform
Richiardi, Matteo Guido, Leonie Westhoff, Caterina Astarita, Ekkehard Ernst, Clare Fenwick, Neysan Khabirpour & Lorenzo Pelizzari (2025): The impact of a decade of digital transformation on employment, wages, and inequality in the EU: a “conveyor belt” hypothesis. In: Socio-economic review, Jg. 23, H. 3, S. 1225-1251. DOI:10.1093/ser/mwaf011
Abstract
"We study the effects of digital transformation in the European Union on individual employment outcomes, wage growth, and income inequality, during the decade 2010–9. Our results allow us to formulate a ‘conveyor-belt’ hypothesis suggesting that employment confers a competitive advantage in navigating the digital transition due to the accumulation of pertinent skills in the workplace. Because digital skills are acquired with the changing demands of the job, their initial endowment matters less for the employed than for the non-employed. Furthermore, the ability of out-of-work individuals with higher digital skills to jump back on the labour market is reduced for those with higher education, suggesting a faster depreciation of their digital skills. A similar effect, although of limited size, is found for earning growth: out-of-work individuals with higher digital skills are not only more likely to find a job, but experience higher earnings growth, compared to their peers with lower digital skills. Our results point to a vulnerability of workers ‘left behind’ from the digital transformation and the labour market. The overall effects on inequality are, however, limited." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Sociotechnical imaginaries of social inequality in the design and use of AI recruitment technology (2025)
Zitatform
Sartori, Laura & Clementine Collett (2025): Sociotechnical imaginaries of social inequality in the design and use of AI recruitment technology. In: European Societies, Jg. 27, H. 3, S. 409-432. DOI:10.1162/euso_a_00035
Abstract
"Through interviewing 12 companies in Italy which either design (vendors) or use (clients) AI recruitment technology systems, we explore how these companies perceive their systems to interact with issues of social inequality and how these perceptions, in practice, carry societal impacts. Three sociotechnical imaginaries (Jasanoff and Kim, 2015) were consistently embedded within these companies’ visions of this intersection: the third eye, the river, and the car bonnet. Through critically analyzing these imaginaries, we find that they exhibit an overriding desire for productivity and talent capture from clients, and a consequential de-prioritization of addressing social inequality and scrutinizing the ways it could be reproduced from both vendors and clients. It demonstrates that the current ‘desired’ futures, shown by the sociotechnical imaginaries which vendors and clients share for AI-tec-tech are really leading us towards an ‘undesirable’ future of hiring which continues to perpetuate social inequality. This study contributes one of the first pieces of empirical work to simultaneously assess the perceptions of AI-rec-tech vendors ’ and clients’ surrounding social inequality, to shed light on the priorities for design and the motivations for usage, and to reflect upon how this impacts society. This is a significant and original contribution to the evolving body of literature on AI-rec-tech in sociology, critical data studies, and communications." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
A theory-based AI automation exposure index: Applying Moravec's Paradox to the US labor market (2025)
Schaal, Jacob;Zitatform
Schaal, Jacob (2025): A theory-based AI automation exposure index: Applying Moravec's Paradox to the US labor market. (arXiv papers), 33 S. DOI:10.48550/arXiv.2510.13369
Abstract
"This paper develops a theory-driven automation exposure index based on Moravec's Paradox. Scoring 19,000 O*NET tasks on performance variance, tacit knowledge, data abundance, and algorithmic gaps reveals that management, STEM, and sciences occupations show the highest exposure. In contrast, maintenance, agriculture, and construction show the lowest. The positive relationship between wages and exposure challenges the notion of skill-biased technological change if AI substitutes for workers. At the same time, tacit knowledge exhibits a positive relationship with wages consistent with seniority-biased technological change. This index identifies fundamental automatability rather than current capabilities, while also validating the AI annotation method pioneered by Eloundou et al. (2024) with a correlation of 0.72. The non-positive relationship with pre-LLM indices suggests a paradigm shift in automation patterns." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Auswirkungen des Strukturwandels auf die Arbeitsmarktregionen und Bundesländer in der langen Frist – Qualifikations- und Berufsprojektion bis 2040 (2025)
Schneemann, Christian ; Kalinowski, Michael; Bernardt, Florian; Wolter, Marc Ingo; Maier, Tobias ; Zika, Gerd ;Zitatform
Schneemann, Christian, Florian Bernardt, Michael Kalinowski, Tobias Maier, Gerd Zika & Marc Ingo Wolter (2025): Auswirkungen des Strukturwandels auf die Arbeitsmarktregionen und Bundesländer in der langen Frist – Qualifikations- und Berufsprojektion bis 2040. (IAB-Forschungsbericht 03/2025), Nürnberg, 46 S. DOI:10.48720/IAB.FB.2503
Abstract
"Die Bundesländer und die Arbeitsmarktregionen in Deutschland unterscheiden sich in ihrer Bevölkerungs- und Wirtschaftsstruktur, weshalb sie auch unterschiedliche Arbeitskräfteengpässe und -überhänge aufweisen. Aufgrund ihrer verschiedenartigen Entwicklungen werden auch künftig Unterschiede im Arbeitsmarktgeschehen bestehen. Mit Hilfe des sogenannten QuBe-Modellverbundes (8. Welle der QuBe-Basisprojektion) werden langfristige immanente Megatrends wie die demografische Entwicklung, der wirtschaftliche Strukturwandel und die Digitalisierung im Modell selbst erfasst und die Auswirkungen auf Wirtschaft und Arbeitsmarkt sichtbar gemacht. Die Analyse zeigt, dass sich die wirtschaftliche Lage in Deutschland nicht wie in der Vergangenheit durch positive Entwicklungen im Außenhandel erholen wird. Das zukünftige Handeln der USA, China und Russlands ist schwer abzuschätzen und erhöht die Unsicherheit auf dem Weltmarkt. Zudem wird das künftige Arbeitsmarktgeschehen zu einem großen Teil von der demografischen Entwicklung, dem stetigen strukturellen Wandel (z.B. Digitalisierung im Handel) und der schwächeren Nachfrage im Baugewerbe geprägt. So wird das Arbeitskräfteangebot infolge des Bevölkerungsrückgangs in vielen Bundesländern und Arbeitsmarktregionen bis zum Jahr 2040 sinken. Zwar können einige Arbeitsmarktregionen noch Bevölkerung aufbauen, aber die Bevölkerung im erwerbsfähigen Alter wird in allen abnehmen. Infolgedessen wird auch der Arbeitskräftebedarf fast überall sinken. Insgesamt wird in vielen Bundesländern und Arbeitsmarktregionen die Erwerbslosenquote sinken oder nahezu stabil bleiben, so dass dort trotz der schlechteren konjunkturellen Entwicklung weiterhin mit Engpässen in verschiedenen Wirtschaftsbereichen und Berufen zu rechnen ist. Die Rekrutierung von Arbeitskräften dürfte somit in vielen Wirtschaftsbereichen und Regionen langfristig zunehmend schwieriger werden. Der Bedarf an qualifiziertem Personal im Wirtschaftszweig „Heime und Sozialwesen“ oder im Bereich der IT-Dienstleistungen wächst kontinuierlich. Dies alles geschieht vor dem Hintergrund eines wohl eher noch beschleunigten Strukturwandels, der gerade die Bundesländer und Arbeitsmarktregionen schon jetzt vor große Herausforderungen stellt, in denen das Verarbeitende Gewerbe zum Beispiel die Automobilindustrie nach wie vor überdurchschnittlich. Die fortschreitende Digitalisierung und Dekarbonisierung erfordern eine permanente Modernisierung und Innovationsfähigkeit der deutschen Wirtschaft. Gerade die ökologische Transformation ist stark auf Erwerbstätige im Baugewerbe angewiesen. Eine Qualifizierung in diesem Bereich bleibt deshalb wichtig, weil die Rekrutierungssituation für Unternehmen trotz der langfristig vermutlich zurückgehenden Erwerbstätigkeit im Vergleich zu anderen Berufen auch in Zukunft schwierig sein wird. Die Umsetzung zusätzlich notwendiger Investitionen im Zuge dieser Transformation sollte nicht an fehlenden Fachkräften scheitern." (Autorenreferat, IAB-Doku)
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Literaturhinweis
KI-Nähe im Job zahlt sich aus (2025)
Seele, Stefanie; Stettes, Oliver;Zitatform
Seele, Stefanie & Oliver Stettes (2025): KI-Nähe im Job zahlt sich aus. (IW-Kurzberichte / Institut der Deutschen Wirtschaft Köln 2025,45), Köln, 3 S.
Abstract
"Beschäftigte, deren Aufgaben eine Nähe zu den Anwendungspotenzialen von Künstlicher Intelligenz (KI) aufweisen, erhalten höhere Tagesentgelte als Beschäftigte in KI-fernen Tätigkeiten. Sie wechseln zudem seltener den Betrieb und haben seltener längere Arbeitslosigkeitsperioden. Die Sorge vor einer zunehmenden Verbreitung von KI im Arbeitsalltag scheint bisher unbegründet." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Data product DOI: 10.5164/IAB.SIAB7521.de.en.v1
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Aspekt zurücksetzen
- Gesamtbetrachtungen/Positionen
- Arbeitsformen, Arbeitszeit und Gesundheit
- Qualifikationsanforderungen und Berufe
- Arbeitsplatz- und Beschäftigungseffekte
- Wirtschaftsbereiche
- Arbeits- und sozialrechtliche Aspekte / digitale soziale Sicherung
- Deutschland
- Andere Länder/ internationaler Vergleich
- Besondere Personengruppen