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
SME digitalisation in the EU: Trends, policies and impacts (2025)
Eiffe, Franz Ferdinand; Biaggi, Elena; Riso, Sara; Miliadis, Grigorios; Loo, Jasper van;Zitatform
Eiffe, Franz Ferdinand, Sara Riso, Elena Biaggi, Jasper van Loo & Grigorios Miliadis (2025): SME digitalisation in the EU: Trends, policies and impacts. (Eurofound research report / European Foundation for the Improvement of Living and Working Conditions), Luxembourg, 78 S. DOI:10.2806/8684886
Abstract
"This report discusses the digital transformation of small and medium-sized enterprises (SMEs) in the European Union, highlighting its importance for their competitiveness and the EU’s economy. The report explores the degreeof digitalisation in SMEs in the EU, including the adoption of digital technologies, e-commerce and e-business practices. It also examines the impact of the COVID-19 pandemic on SMEs’ digitalisation and identifieskey challenges, including lack of infrastructure, financing and digital skills. In addition, the report reviews policy frameworks and support measures related to digitalisation and the development of digital skills in SMEs. Furthermore, it presents an empirical analysis of how digital technology use is related to job quality at the workplace level." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Cross-country skills-technology policy debates through large language models (2025)
Zitatform
Einhoff, Jan, Isabella López Trejos & Caroline Paunov (2025): Cross-country skills-technology policy debates through large language models. (OECD science, technology and industry working papers 2025,20), Paris, 43 S. DOI:10.1787/d5f669be-en
Abstract
"Language models, this paper conducts a cross-country comparative innovation policy analysis of skills-technology policy debates across seven OECD member countries (Austria, Canada, Finland, Germany, Korea, Sweden, and the United Kingdom). Results highlight the dominance of STEM (science, technology, engineering and mathematics) and digital skills in these policy debates, the relative neglect of green skills, and the emphasis on soft skills across all technology fields. The analysis also identifies common policy instruments, which include collaborative platforms and direct financial support. Overall, the paper shows how large language models can help policy analysts identify patterns and gaps in extensive policy texts that nonetheless critically demands expert oversight and careful interpretation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial intelligence, tasks, skills, and wages: Worker-level evidence from Germany (2025)
Zitatform
Engberg, Erik, Michael Koch, Magnus Lodefalk & Sarah Schroeder (2025): Artificial intelligence, tasks, skills, and wages: Worker-level evidence from Germany. In: Research Policy, Jg. 54, H. 8. DOI:10.1016/j.respol.2025.105285
Abstract
"This paper examines how new technologies are linked to changes in the content of work and individual wages. As a first step, it documents novel facts on task and skill changes within occupations over the past two decades in Germany. We furthermore reveal a distinct relationship between ex-ante occupational work content and ex-post exposure to artificial intelligence (AI) and automation (robots). Workers in occupations with high AI exposure perform different activities and face different skill requirements compared to workers in occupations exposed to robots, suggesting that robots and AI are substitutes for different activities and skills. We also document that changes in the task and skill content of occupations is related to ex-ante exposure to technologies. Finally, the study uses individual labour market biographies to investigate the relationship between AI and wages. By exploring the dynamic influence of AI exposure on individuals over time, the study uncovers positive associations with wages, with nuanced variations across occupational groups, thereby shedding further light on the substitutability and augmentability of AI." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))
Ähnliche Treffer
frühere (möglicherweise abweichende) Version erschienen als: Ratio working paper, 371Weiterführende Informationen
Data product DOI: 10.5164/IAB.SIAB7519.de.en.v1 -
Literaturhinweis
Artificial intelligence, hiring and employment: job postings evidence from Sweden (2025)
Engberg, Erik; Hellsten, Mark; Sabolová, Radka; Lodefalk, Magnus ; Javed, Farrukh; Schroeder, Sarah ; Tang, Aili;Zitatform
Engberg, Erik, Mark Hellsten, Farrukh Javed, Magnus Lodefalk, Radka Sabolová, Sarah Schroeder & Aili Tang (2025): Artificial intelligence, hiring and employment: job postings evidence from Sweden. In: Applied Economics Letters, S. 1-6. DOI:10.1080/13504851.2025.2497431
Abstract
"This paper investigates the impact of artificial intelligence (AI) on hiring and employment, using the universe of job postings published by the Swedish Public Employment Service from 2014 to 2022 and full-population administrative data for Sweden. We exploit a detailed measure of AI exposure according to occupational content and find that establishments exposed to AI are more likely to hire AI workers. Survey data further indicate that AI exposure aligns with greater use of AI services. Importantly, rather than displacing non-AI workers, AI exposure is positively associated with increased hiring for both AI and non-AI roles. In the absence of substantial productivity gains that might account for this increase, we interpret the positive link between AI exposure and non-AI hiring as evidence that establishments are using AI to augment existing roles and expand task capabilities, rather than to replace non-AI workers." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Kassensturz. Daten, Fakten und Erfahrungen aus der Arbeitswelt des Berliner Einzelhandels: Branchenbericht (2025)
Engel, Sonja;Zitatform
Engel, Sonja (2025): Kassensturz. Daten, Fakten und Erfahrungen aus der Arbeitswelt des Berliner Einzelhandels. Branchenbericht. Berlin, 45 S.
Abstract
"Dieser Branchenbericht nimmt die Beschäftigung und die Beschäftigten des Berliner Einzelhandels genauer in den Blick. Der Bericht soll Anregung sein für Gespräche – zwischen Kolleg:innen, Arbeitnehmenden, Betriebsräten und Arbeitgebenden, sowie Akteur:innen, die sich in verschiedenen Positionen und in unterschiedlichen (politischen) Institutionen mit dieser Branche befassen. Es werden Daten und Statistiken analysiert, Fakten zusammengetragen und Perspektiven verschiedener Akteur:innen der Branche dargestellt. Er bietet Informationen über die aktuelle Situation und gibt einen Überblick über die Entwicklungen und Trends der vergangenen Jahre, präsentiert Einblicke in die Arbeitsbedingungen der Beschäftigten und die Herausforderungen, mit denen die Branche zu kämpfen hat. Auch der Onlinehandel und die Digitalisierung der Arbeit sowie die Frage des Fachkräftemangels werden genauer betrachtet. Für einen Gastbeitrag konnten wir Sarah Kuhn und Dr. Holger Seibert vom Institut für Arbeitsmarkt- und Berufsforschung (IAB) Berlin-Brandenburg gewinnen, die einen Exkurs zum Thema der Ersetzbarkeit von Tätigkeiten im Einzelhandel durch digitale Technologien präsentieren. Diese Publikation beruht dabei auf der Auswertung verschiedener Quellen: Offizielle Statistiken und Analysen, die von der Bundesagentur für Arbeit und weiteren Institutionen erhoben und veröffentlicht werden, sind eben - so betrachtet worden wie Ergebnisse wissenschaftlicher Untersuchungen und Umfrageergebnisse und Einschätzungen der Sozialpartner. Die Vereinte Dienstleistungsgewerkschaft (ver.di) und die von ihr geleisteten Sonderauswertungen der Daten des DGB-Index für Gute Arbeit liefern wichtige Erkenntnisse für das Verständnis des Arbeitsalltags der Arbeitnehmenden. Der Handelsverband Deutschland (HDE) trägt mit seinen Befragungen und Datenaufbereitungen die Perspektive der Unternehmen und Betriebe bei. Darüber hinaus kommen weitere Akteur:innen zu Wort, mit denen Hintergrundgespräche und Interviews geführt wurden, oder die an den Veranstaltungen des Projekts Joboption Berlin – drei Sozialpartnerdialogen und einem Werkstattgespräch teilgenommen haben." (Textauszug, IAB-Doku)
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Literaturhinweis
Predictive AI and productivity growth dynamics: Evidence from French firms (2025)
Zitatform
Fontanelli, Luca, Mattia Guerini, Raffaele Miniaci & Angelo Secchi (2025): Predictive AI and productivity growth dynamics: Evidence from French firms. In: Journal of Economic Behavior & Organization, Jg. 240. DOI:10.1016/j.jebo.2025.107336
Abstract
"While artificial intelligence (AI) adoption holds the potential to enhance business operations through improved forecasting and automation, its relation with average productivity growth remain highly heterogeneous across firms. This paper shifts the focus and investigates the impact of predictive AI on the volatility of firms’ productivity growth rates. Using firm-level data from the 2019 French ICT survey, we provide robust evidence that AI use is associated with increased volatility. This relationship persists across multiple robustness checks, including analyses balancing AI users and other firms based on key observables. To propose a possible mechanisms underlying this relation, we compare firms that purchase AI from external providers (“AI buyers”) and those that develop AI in-house (“AI developers”). Our results show that heightened volatility is concentrated among AI buyers, whereas firms that develop AI internally experience no such association. Finally, we find that the AI-volatility link among “AI buyers” is mitigated in firms with a higher share of ICT engineers and technicians, suggesting that AI’s successful integration requires complementary human capital." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))
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Literaturhinweis
Exploring Gender Disparities in the Era of AI (2025)
Fornasari, Tommaso; Bannò, Mariasole;Zitatform
Fornasari, Tommaso & Mariasole Bannò (2025): Exploring Gender Disparities in the Era of AI. In: M. Agostini, V. Beretta, M. C. Demartini, A. Ghio & S. Trucco (Hrsg.) (2025): Diversity and Equity in Accounting. Emerging Issues, Challenges and Opportunities, S. 203-214. DOI:10.1007/978-3-031-78247-3_14
Abstract
"This chapter investigates the gender disparities in the impact of artificial intelligence (AI) within the accounting profession, focusing on both the potential risks and benefits that AI presents. Automation technologies, including AI, have rapidly advanced, significantly altering the landscape of work across various industries. The integration of AI into the workforce raises concerns about widespread job displacement, particularly affecting both low-skill and high-skill positions. Our research aims to address the underexplored area of how AI impacts gender disparities in the workplace, specifically within the accounting field. Through qualitative methods, including in-depth interviews with diverse stakeholders, we analyze the risks and opportunities AI presents for women compared to men. The study seeks to uncover workforce inequalities and understand the gender-specific implications of AI, highlighting the need for equitable access to training and resources to ensure both men and women can thrive in an AI-driven work environment. The findings reveal that AI implementation can result in both positive and negative outcomes, influencing employment patterns and job satisfaction. While AI can enhance efficiency and productivity, it also poses risks such as job displacement and increased stress due to work insecurity. The gender disparity in STEM education exacerbates these issues, as women are underrepresented in fields that are crucial for AI-related job opportunities. The chapter emphasizes the importance of proactive measures, including targeted educational programs and inclusive policies, to mitigate the adverse impacts of AI and promote gender equality in the evolving job market." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
How AI-Augmented Training Improves Worker Productivity (2025)
Fouarge, Didier ; Stops, Michael ; Janssen, Simon ; Fregin, Marie-Christine ; Özgül, Pelin; Rounding, Nicholas; Montizaan, Raymond ; Levels, Mark ;Zitatform
Fouarge, Didier, Marie-Christine Fregin, Simon Janssen, Mark Levels, Raymond Montizaan, Pelin Özgül, Nicholas Rounding & Michael Stops (2025): How AI-Augmented Training Improves Worker Productivity. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 18224), Bonn, 29 S., App.
Abstract
"We analyze the impact of AI-augmented training on worker productivity in a financial services company. The company introduced an AI tool that provides performance feedback on call center agents to guide their training. To estimate causal effects, we exploit the staggered roll out of the AI-tool. The AI-augmented training reduces call handling time by 10 percent. We find larger effects for short-tenured workers because they spend less time putting clients on hold. But the AI-augmented training also improves communication style with relatively stronger effects for long-tenured agents, and we find slightly positive effects on customer satisfaction." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
App-basierte Lieferdienste in Deutschland: Warum Menschen Gig-Work aufnehmen und meist schnell wieder beenden (Serie: „Beschäftigung in der Gig-Ökonomie“) (2025)
Zitatform
Friedrich, Martin, Ines Helm, Ramona Jost, Julia Lang & Christoph Müller (2025): App-basierte Lieferdienste in Deutschland: Warum Menschen Gig-Work aufnehmen und meist schnell wieder beenden (Serie: „Beschäftigung in der Gig-Ökonomie“). In: IAB-Forum H. 16.04.2025. DOI:10.48720/IAB.FOO.20250416.01
Abstract
"App-basierte Lieferdienste haben sich in den letzten Jahren rasant ausgebreitet. Das hat auch die öffentliche Diskussion um schlechte Arbeitsbedingungen der dort beschäftigten Gig-Worker angefacht. Allerdings gibt es bisher wenige gesicherte Erkenntnisse darüber, was Menschen zur Aufnahme von Gig-Jobs bewegt. Über die Gründe zur Beendigung dieser meist kurzen Jobs ist ebenfalls wenig bekannt. Das IAB bringt mit Ergebnissen einer neuen Befragung Licht in dieses Dunkel." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Algorithmisches Management bei App-basierten Lieferdiensten: Fast die Hälfte der betroffenen Gig-Worker fühlt sich dadurch überwacht (2025)
Zitatform
Friedrich, Martin, Ines Helm, Julia Lang & Christoph Müller (2025): Algorithmisches Management bei App-basierten Lieferdiensten: Fast die Hälfte der betroffenen Gig-Worker fühlt sich dadurch überwacht. In: IAB-Forum H. 23.09.2025. DOI:10.48720/IAB.FOO.20250923.01
Abstract
"Arbeit auf digitalen Plattformen zeichnet sich durch den Einsatz von algorithmischem Management aus. Eine Befragung zeigt, wie Gig-Worker bei App-basierten Lieferdiensten diese Praxis wahrnehmen. Die überwiegende Mehrheit der Gig-Worker gibt an, dass ihre Lieferdienstplattform digitale Arbeitsmittel beispielsweise einsetzt, um ihnen Aufgaben automatisch zuzuweisen und ihren Standort zu verfolgen. Fast die Hälfte der Betroffenen fühlt sich dadurch überwacht." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Die Arbeit: Wie wir sie mit KI neu erfinden … und was für uns übrig bleibt (2025)
Zitatform
Gerpott, Fabiola H. & Stephan A. Jansen (2025): Die Arbeit. Wie wir sie mit KI neu erfinden … und was für uns übrig bleibt. Hamburg: brand eins books, 124 S.
Abstract
"Wie wird sich die Arbeitswelt im Zeitalter der künstlichen Intis zwischen dem Menschen und seinen neuen Maschinen – für andere Arbeit, andere Arbeitsteilungen, andere Führung und andere Bildung. Neben Studien aus der Wissenschaft bietet das Buch konkrete Handlungsempfehlungen für ein neues «Human Machine Resource Management», das nicht nur das Personalmanagement, sondern jeden von uns zu einer anregenderen und sinnstiftenderen Arbeit nutzen kann. Und es lädt dazu ein, an der Zukunft der Arbeit aktiv mitzuarbeiten. Zentrale Themen sind unter anderem die ethischen Implikationen, wenn Entscheidungen an Maschinen delegiert werden, die Auswirkungen auf die Diversität und Leistungsfähigkeit der Belegschaft sowie die Neugestaltung von Arbeitsräumen und HR-Prozessen." (Verlagsangaben, IAB-Doku)
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Literaturhinweis
The Impact of a New Workplace Technology on Employees (2025)
Zitatform
Giebel, Marek & Alexander Lammers (2025): The Impact of a New Workplace Technology on Employees. In: Oxford Bulletin of Economics and Statistics, Jg. 87, H. 5, S. 1003-1024. DOI:10.1111/obes.12674
Abstract
"How does the implementation of a new technology affect workers? Using detailed worker-level data for Germany, we analyse the impact of new technologies on non-monetary working conditions such as overtime, training and perceived labor intensity. We show that the strongest effects arise in the first year of their implementation. These effects diminish after the introduction period. We further provide evidence that the impact of technology adoption varies across diverse occupational and industrial contexts. Workers in occupations with a higher task substitution potential show stronger increases in overtime, training measures and labor intensity. Analyzing industry characteristics, we find that employees exposed to a new technology react more strongly in industries with higher business dynamics in terms of organisational capital and R&D investment. Extending these considerations to information and communication technology (ICT) usage, we show that new technologies exert stronger effects in industries with high investment in ICT equipment or low investment in software." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial intelligence and autonomy at work: empirical insights from Germany (2025)
Zitatform
Giering, Oliver & Stefan Kirchner (2025): Artificial intelligence and autonomy at work: empirical insights from Germany. In: Journal for labour market research, Jg. 59. DOI:10.1186/s12651-025-00401-5
Abstract
"Artificial intelligence (AI) is a prominent topic regarding the digitalisation of work and its diffusion is expected to radically change job quality. Overall, there exists a large discrepancy between discursive expectations and quantitative empirical evidence. In this article, we use a novel module from the German Socio-Economic Panel to examine the overall prevalence of AI at work, the determinants that increase the likelihood of AI use, and its association with autonomy. The results show that 38% of German workers use AI, and AI use is associated with the use of specific digital technologies. Workers in high-level, non-routine occupations are more likely to use AI, particularly in comparison to manual workers. Moreover, the association between AI and autonomy is merely superficial and cannot be properly evaluated without considering workplace preconditions." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
KI im Unternehmen: 19. ZAAR-Kongress, München, 9. Mai 2025 (2025)
Giesen, Richard; Junker, Abbo; Rieble, Volker;Zitatform
Giesen, Richard, Abbo Junker & Volker Rieble (Hrsg.) (2025): KI im Unternehmen. 19. ZAAR-Kongress, München, 9. Mai 2025. (ZAAR Schriftenreihe 56), München: ZAAR, 125 S.
Abstract
"„Künstliche Intelligenz“ (KI oder AI) wird zu einem Produktionsfaktor. Die Bandbreite der Anwendungen ist groß. Ausgangspunkt ist das maschinelle Lernen, das mit vorhandenen Daten „trainiert“ wird und Vorhersagen treffen soll, etwa zum erwartbaren Ausfall einer Maschine (vorausschauende Instandhaltung). Die Chat-Programme mit ihren Large Language Models (LLMs) setzen auf ein computerlinguistisches Wahrscheinlichkeitsmodell, um Texte „vorherzusagen“ und damit kommunizieren zu können. Nur wenige Juristen übersehen die praktische Anwendung in den Unternehmen. Deutlich mehr äußern sich in Vorträgen und Aufsätzen zu den Rechtsproblemen der KI-Anwendung. Ohne konkrete Anschauung lassen sich rechtliche Fragen indes nicht erfassen. Deswegen wurde erstmals ein ZAAR-Kongress überwiegend mit nichtjuristischen Themen zur Anwendung von KI veranstaltet und den Rechtsfragen nur ausblickend begegnet." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Inhaltsverzeichnis vom Verlag -
Literaturhinweis
Artificial intelligence and the wellbeing of workers (2025)
Zitatform
Giuntella, Osea, Johannes Konig & Luca Stella (2025): Artificial intelligence and the wellbeing of workers. In: Scientific Reports, Jg. 15, H. 1. DOI:10.1038/s41598-025-98241-3
Abstract
"This study explores the relationship between artificial intelligence (AI) and workers’ well-being and healthusing longitudinal survey data from Germany (2000–2020). Using a measure of occupational exposure to AI, we explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pretrends in workers’ well-being and health. We findno evidence of a sizeable negative impact of AI on workers’ well-being and mental health. If anything, there is evidence of an improvement in health status and health satisfaction, which may be explained by the decline in job physical intensity. Overall, our results are consistent with the lack of negative effects of AI on the labor markets." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
A technological construction of society: Comparing GPT-4 and human respondents for occupational evaluation in the UK (2025)
Zitatform
Gmyrek, Pawel, Christoph Lutz & Gemma Newlands (2025): A technological construction of society: Comparing GPT-4 and human respondents for occupational evaluation in the UK. In: BJIR, Jg. 63, H. 1, S. 180-208. DOI:10.1111/bjir.12840
Abstract
"Despite initial research about the biases and perceptions of large language models (LLMs), we lack evidence on how LLMs evaluate occupations, especially in comparison to human evaluators. In this paper, we present a systematic comparison of occupational evaluations by GPT-4 with those from an in-depth, high-quality and recent human respondents survey in the UK. Covering the full ISCO-08 occupational landscape, with 580 occupations and two distinct metrics (prestige and social value), our findings indicate that GPT-4 and human scores are highly correlated across all ISCO-08 major groups. At the same time, GPT-4 substantially under- or overestimates the occupational prestige and social value of many occupations, particularly for emerging digital and stigmatized or illicit occupations. Our analyses show both the potential and risk of using LLM-generated data for sociological and occupational research. We also discuss the policy implications of our findings for the integration of LLM tools into the world of work." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))
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Literaturhinweis
Generative AI and jobs: a refined global index of occupational exposure (2025)
Gmyrek, Pawel ; Troszyński, Marek; Berg, Janine ; Kamiński, Karol; Nafradi, Balint ; Konopczyński, Filip; Rosłaniec, Konrad; Ładna, Agnieszka;Zitatform
Gmyrek, Pawel, Janine Berg, Karol Kamiński, Filip Konopczyński, Agnieszka Ładna, Balint Nafradi, Konrad Rosłaniec & Marek Troszyński (2025): Generative AI and jobs. A refined global index of occupational exposure. (ILO working paper / International Labour Organization 140), Geneva, 72 S. DOI:10.54394/hetp0387
Abstract
"This study updates the ILO’s 2023 Global Index of Occupational Exposure to Generative AI (GenAI), incorporating recent advances in the technology and increasing user familiarity with GenAI tools. Using a representative sample from the 29,753 tasks in the Polish occupational classification system and a survey of 1,640 people employed in each 1-digit ISCO-08 groups, we collect 52,558 data points regarding perceive potential of automation for 2,861 tasks. We then compare this input with a survey and several rounds of Delphi-style discussions among a smaller group of international experts. Based on this process, we create a repository of knowledge about task automation that goes beyond national specificities and use it to develop an AI assistant able to predict scores for tasks in the technical documentation of ISCO-08. Our 2025 scores are presented in a revised framework of four progressively increasing exposure gradients, with a new set of global estimates of employment shares exposed to GenAI. Clerical occupations continue to have the highest exposure levels. Additionally, some strongly digitized occupations have increased exposure, highlighting the expanding abilities of GenAI regarding specialized tasks in professional and technical roles. Globally, one in four workers are in an occupation with some GenAI exposure. 3.3% of global employment falls into the highest exposure category, albeit with significant differences between female (4.7%) and male employment (2.4%). These differences increase with countries’ income (9.6% female vs 3.5% male in Gradient 4in HICs), and so does the overall exposure (11% of total employment in LICs vs 34% in HICs). As most occupations consist of tasks that require human input, transformation of jobs is the most likely impact of GenAI. Linking our refined index with national micro data enables precise projections of such transformations, offering a foundation for social dialogue and targeted policy responses to manage the transition." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Governing the Digital Transition: The Moderating Effect of Unemployment Benefits on Technology‐Induced Employment Outcomes (2025)
Zitatform
Golboyz, Mark (2025): Governing the Digital Transition: The Moderating Effect of Unemployment Benefits on Technology‐Induced Employment Outcomes. In: Social Inclusion, Jg. 13. DOI:10.17645/si.10114
Abstract
"The digital transition shapes work in numerous ways. For instance, by affecting employment structures. To ensure that the digital transition results in better employment opportunities in terms of socio-economic status, labor markets have to be guided appropriately. The European Pillar of Social Rights can be the political framework to foster access to employment and tackle inequalities that result from the digital transition. Current research primarily examines scenarios of occupational upgrading and employment polarisation. In the empirical literature, there is no consensus on which of these developments prevail. Findings vary between countries and across different study periods. Accordingly, this article provides a theoretical explanation for the conditions under which occupational upgrading and employment polarization become more likely. Further, this article examines how the use of information and communication technology (ICT) capital in the production of goods and services affects the socio-economic status of individuals and, more importantly, whether unemployment benefits moderate this effect. Methodologically, the article uses multilevel maximum likelihood regression models with an empirical focus on 12 European countries and 19 industries. The analysis is based on data from the European Labour Force Survey (EU-LFS), the European Union Level Analysis of Capital, Labour, Energy, Materials, and Service Inputs (EU-KLEMS) research project, and the Comparative Welfare Entitlements Project (CWEP). The results of the article indicate that generous unemployment benefits are associated with occupational upgrading. This implies that educational and vocational labor market policies need to be developed to prevent the under-skilled from being left behind and to enable these groups to benefit from the digital transition. Consequently, it is not only the extent to which work involves routine tasks or the skills of workers that determine how technological change affects employment, but also social rights shape employment through unemployment benefits." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI and the labour market: opening the black box (2025)
Zitatform
Greenan, Nathalie, Dario Guarascio & Jelena Reljic (2025): AI and the labour market: opening the black box. In: Eurasian business review, Jg. 15, H. 4, S. 925-951. DOI:10.1007/s40821-025-00324-8
Abstract
"This work aims at discussing some of the main (open) questions about the labour impact of AI technologies. First, we provide an in-depth literature review focusing on concepts and measurement approaches and distinguishing between up (invention and knowledge creation), mid (technological innovation and development) and downstream (adoption and diffusion) components of the AI value chain. Second, we summarise the six articles included in the Special Issue ‘AI and labor markets: opening the black box’, distinguishing between contributions focusing on AI exposure, occupations and skill demand; the relationship between AI and automation technologies and their impact on income distribution; and, finally, the effect on organisational structures, management practices, and power dynamics within workplaces. Our analysis emphasises that AI’s employment effects are neither predetermined nor uniform, but shaped by implementation contexts, organisational choices, and institutional frameworks. We find that heterogeneity matters at multiple levels—across countries, sectors, firms, and demographic groups—challenging deterministic narratives and highlighting the need for adaptive policy responses that recognise these asymmetries." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI and employment in Europe (2025)
Zitatform
Guarascio, Dario & Jelena Reljic (2025): AI and employment in Europe. In: Economics Letters, Jg. 247. DOI:10.1016/j.econlet.2025.112183
Abstract
"This paper contributes to the growing research on AI's labor market impact by presenting novel evidence on the heterogeneous employment effects of AI across EU countries from 2012 to 2022. While concerns persist about AI's disruptive potential, our findings show that occupations more exposed to AI technologies experience stronger employment growth, all else being equal. However, these effects are not uniform across the EU. Positive employment outcomes are concentrated in Innovation Leaders (Belgium, Denmark, Finland, the Netherlands and Sweden) and Strong Innovators (Austria, Cyprus, France, Germany, Ireland and Luxembourg), emphasizing the context-dependent nature of AI's impact. These findings reflect the uneven distribution of innovation capabilities, with a country's innovation system and ‘absorptive capacity’ playing a crucial role in fully harnessing AI's potential for employment (and economic) growth. Ultimately, this research challenges the notion of AI as universally beneficial or harmful, highlighting its asymmetric effects across countries and occupations." (Author's abstract, IAB-Doku, © 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))
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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