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
Automation and Polarization (2026)
Zitatform
Acemoglu, Daron & Jonas Löbbing (2026): Automation and Polarization. In: Journal of Political Economy, Jg. 134, H. 3, S. 1017-1072. DOI:10.1086/739330
Abstract
"We develop an assignment model of automation. Each of a continuum of tasks of variable complexity is assigned to either capital or one of a continuum of labor skills. We characterize conditions for interiorautomation, whereby tasks of intermediate complexity are performed by capital. Interior automation arises when the most skilled workers have a comparative advantage in the most complex tasks relative to capital, and when the wages of the least skilled workers are sufficiently low relative to both their own productivity and the effective cost of capital in low-complexity tasks. Minimum wages and other sourcesof higher wages at the bottom make interior automation less likely. Starting with interior automation, a reduction in the cost of capital (or an increase in capital productivity) causes employment and wage polarization. Specifically, further automation pushes workers into tasks at the lower and upper ends ofthe task distribution. It also monotonically increases the skill premium above a threshold and reduces the skill premium below this threshold. Moreover, automation tends to reduce the real wage of Workers with comparative advantage profiles close to that of capital. We show that large enough increases in capital productivity ultimately induce a transition to low-skill automation and qualitatively alter the effects of automation—thereafter inducing monotone increases in skill premia rather than wage polarization." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Who uses Generative AI? Patterns and inequalities across the EU: Employment and labour markets (2026)
Zitatform
Adăscăliței, Dragoș (2026): Who uses Generative AI? Patterns and inequalities across the EU. Employment and labour markets. (Eurofound working paper), Dublin, 19 S.
Abstract
"This paper describes generative AI use patterns across EU27 Member States in 2025, analysing crossnational variation and socio-demographic inequalities based on Eurostat aggregate data. Overall use of generative AI reaches 32.7% at the EU27 level, ranging from 17.8% in Romania to 48.4% in Denmark. Country patterns do not follow clear geographic clustering, with high and low adopters distributed across all European regions. Private use systematically exceeds professional use, whilst educational use remains concentrated among young populations. Educational attainment emerges as a strong predictor of AI use, with high-educated individuals using generative AI at more than double the rate of low-educated individuals. Age is also a strong predictor, with 63.8% of those aged 16-24 having used generative AI in the past three months compared to just 6.5% of those aged 65 and above. The gender gaps in AI use are moderate but widen with education. In terms of broad occupational groups, the analysis demonstrates that uptake is heavily skewed towards ICT professions. Labour force status also matters decisively, with students (72.0%) far exceeding employed (36.4%), unemployed (28.3%), and retired/inactive populations (12.9%) in technology usage. These patterns reveal stratified diffusion of generative AI use with implications for labour market inequalities across the EU." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Enhancing Worker Productivity Without Automating Tasks: A Different Approach to AI and the Task-Based Model (2026)
Zitatform
Agrawal, Ajay K., John McHale & Alexander Oettl (2026): Enhancing Worker Productivity Without Automating Tasks: A Different Approach to AI and the Task-Based Model. (NBER working paper / National Bureau of Economic Research 34781), Cambridge, Mass, 44 S.
Abstract
"The task-based approach has become the dominant framework for studying the labor-market effects of artificial intelligence (AI), typically emphasizing the replacement of human workers by machines. Motivated by growing empirical evidence that contemporary AI is more often used as a tool that augments workers, this paper develops two related task-based models in which AI enhances worker productivity without automating tasks. Abstracting from capital, we develop a pair of related task-based models that examine how technological progress in AI that provides new tools to augment workers affects aggregate productivity and wage inequality. Both models emphasize the role of human capital in intermediating the effects of AI-related technological shocks. In the first model, AI use requires specialized expertise, and technological progress expands the set of tasks for which such expertise is effective. We show that a larger supply of AI expertise amplifies the productivity gains from improvements in AI technology while attenuating its adverse effects on wage inequality. The second model focuses on non-AI skills, allowing AI tools to alter the set of tasks that workers can perform given their skills. In equilibrium, workers allocate across tasks in response to wages, generating an endogenous distribution of skills across the task space. A central result is that aggregate productivity and wage inequality depend on different global properties of this equilibrium distribution: productivity is particularly sensitive to thinly staffed tasks that create bottlenecks, while wage inequality is driven by the concentration of workers in a narrow set of tasks. As a result, improvements in AI tools can induce non-monotonic co-movement between productivity and inequality. By linking these mechanisms to multidimensional human capital---including AI expertise and higher-order non-AI skills---the paper highlights the role of education and training policies in shaping the economic consequences of AI-driven technological change." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
AI adoption, productivity and employment: Evidence from European firms (2026)
Aldasoro, Iñaki; Gambacorta, Leonardo; Pal, Rozalia; Wolski, Marcin; Weiß, Christoph; Revoltella, Debora;Zitatform
Aldasoro, Iñaki, Leonardo Gambacorta, Rozalia Pal, Debora Revoltella, Christoph Weiß & Marcin Wolski (2026): AI adoption, productivity and employment: Evidence from European firms. (Economics - working papers / European Investment Bank 2026/02), Luxembourg, 32 S. DOI:10.2867/1772538
Abstract
"This paper provides new evidence on how the adoption of artificial intelligence (AI) affects productivity and employment in Europe. Using matched EIBIS-ORBIS data on more than 12,000 non-financial firms in the European Union (EU) and United States (US), we instrument the adoption of AI by EU firms by assigning the adoption rates of US peers to isolate exogenous technological exposure. Our results show that AI adoption increases the level of labor productivity by 4%. Productivity gains are due to capital deepening, as we find no adverse effects on firm-level employment. This suggests that AI increases worker output rather than replacing labor in the short run, though longer-term effects remain uncertain. However, productivity benefits of AI adoption are unevenly distributed and concentrate in medium and large firms. Moreover, AI-adopting firms are more innovative and their workers earn higher wages. Our analysis also highlights the critical role of complementary investments in software and data or workforce training to fully unlock the productivity gains of AI adoption." (Author's abstract, IAB-Doku) ((en))
Ähnliche Treffer
auch erschienen als: BIS Working Papers, 1325 -
Literaturhinweis
The effect of AI on labour demand: A critical assessment of 'Power and Progress' by Acemoglu and Johnson (2026)
Aldred, Jonathan;Zitatform
Aldred, Jonathan (2026): The effect of AI on labour demand: A critical assessment of 'Power and Progress' by Acemoglu and Johnson. In: Structural Change and Economic Dynamics, Jg. 78, S. 188-196. DOI:10.1016/j.strueco.2026.03.008
Abstract
"Task-based models of production have led to a theoretical reappraisal of the effect of new technology on labour demand. This paper critically assesses the policy implications of this research agenda, with particular reference to Acemoglu and Johnson’s recent book, Power and Progress. While Acemoglu and Johnson take welcome steps away from previous orthodoxy, their analysis has several flaws which affect the policy lessons to be drawn, including: (i) the explanation for anti-labour bias is unclear; (ii) worker-friendly technologies are not clearly characterised in theory, and hard to identify in practice; (iii) macroeconomic policy orthodoxy is largely unquestioned. More generally, much of Power and Progress remains unhelpfully constrained by theoretical commitments to mainstream economics." (Author's abstract, IAB-Doku, © 2026 The Author. Published by Elsevier B.V.) ((en))
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Literaturhinweis
The end of work feels near. How do people perceive the impact of digital technologies and automation? (2026)
Zitatform
Arntz, Melanie, Sebastian Blesse & Philipp Doerrenberg (2026): The end of work feels near. How do people perceive the impact of digital technologies and automation? In: Labour Economics. DOI:10.1016/j.labeco.2026.102897
Abstract
"Anxieties about technological change in the context of the labor market are a recurring historical phenomenon. Using customized survey data collected in 2019 in the US and Germany, prior to the recent wave of generative AI applications, we study how respondents perceive the impact of the digital (automation) technologies available at the time of the survey on the labor market. We document that a majority views digital technologies and automation as a major threat to overall employment and as a cause of rising inequality, while a quarter is concerned about their own labor market prospects. Providing scientific information on the likely labor market implications of digital technologies in a randomized experiment reduces these concerns. Yet, treatment responses depend on prior beliefs about the future of work, resulting in heterogeneous and opposing treatment effects on policy demand." (Author's abstract, IAB-Doku, © 2026 Elsevier) ((en))
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Literaturhinweis
Technologischer Wandel und Löhne: Die Anpassung der Berufe spielt eine entscheidende Rolle (2026)
Zitatform
Bachmann, Ronald, Gökay Demir, Colin Green & Arne Uhlendorff (2026): Technologischer Wandel und Löhne: Die Anpassung der Berufe spielt eine entscheidende Rolle. (IAB-Kurzbericht 01/2026), Nürnberg, 8 S. DOI:10.48720/IAB.KB.2601
Abstract
"Technischer Fortschritt verändert die Arbeitswelt - besonders in Berufen, in denen viele Tätigkeiten leicht automatisiert werden können. In den letzten Jahrzehnten ist der Anteil an Routinetätigkeiten in vielen Berufen deutlich zurückgegangen - häufig zugunsten nicht routinemäßiger kognitiver Tätigkeiten wie Analysieren, Planen oder Beraten. Dabei verzeichnen Berufe, deren Tätigkeiten sich im Laufe der Zeit stärker an den technologischen Wandel angepasst haben, steigende Löhne. Sie zeichnen sich zudem durch intensivere Weiterbildungsaktivitäten aus. In Berufen, deren Tätigkeitsprofil sich kaum verändert hat, stagnieren die Löhne dagegen häufiger." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
- Vollzeitbeschäftigte westdeutsche Männer in ursprünglich routinelastigen Berufen
- Veränderung von Tätigkeitsschwerpunkten durch technologischen Wandel
- Veränderung im Anteil der Routinetätigkeiten
- Veränderung im Anteil der Routinetätigkeiten im Vergleich zu nicht routinemäßigen (NR) kognitiven Tätigkeiten in exemplarisch ausgewählten, ursprünglich routinelastigen Berufsfeldern
- Anteil Beschäftigter in Weiterbildungskursen nach Tätigkeitsgruppen
- Relatives Lohnwachstum nach Tätigkeitsgruppen
- Vollzeitbeschäftigte westdeutsche Männer nach Tätigkeitsgruppen
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Literaturhinweis
How important are within‐occupation task changes for wage growth? Evidence from administrative micro data (2026)
Zitatform
Bachmann, Ronald, Gökay Demir, Colin Green & Arne Uhlendorff (2026): How important are within‐occupation task changes for wage growth? Evidence from administrative micro data. In: Economica, S. 1-40. DOI:10.1111/ecca.70054
Abstract
"We examine how changes in task content over time condition occupational wage development. Using survey data from Germany, we document substantial heterogeneity in within-occupation changes in task content. Combining this evidence with administrative data on individual employment outcomes over a 25-year period, we find important heterogeneity in wage penalties amongst jobs that were initially routine-task-intensive. While occupations that remain (relatively) routine-intensive generate substantial wage penalties, occupations with a decreasing routine intensity experience stable or even increasing wages. These findings suggest that changing task profiles of occupations is an important adaptation mechanism to technological change. They cannot be explained by composition or cohort effects." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Systematic literature review on the digital transformation of the personnel selection process (2026)
Zitatform
Baranyi, Virág (2026): Systematic literature review on the digital transformation of the personnel selection process. In: German Journal of Human Resource Management, Jg. 40, H. 2, S. 223-254. DOI:10.1177/23970022251363012
Abstract
"Digital Transformation technologies (DT technologies) are reshaping work processes, including personnel selection, an area traditionally viewed as inherently human-centric. While prior studies have examined various digital technologies in personnel selection, they have not provided sufficient evidence on the different levels of digitalization in selection processes and the factors influencing organizations’ adoption decisions. To address these gaps, this study systematically reviews 94 Scopus-indexed studies to analyze how DT technologies are applied across selection stages, categorizing practices into Manual, Digitalized, and Digitally Transformed approaches. By further distinguishing between Digital Technologies and AI Enhancements, this study offers a structured framework for understanding how organizations integrate digital technologies into selection and what drives or hinders their adoption. The findings highlight both the benefits (efficiency gains, potential bias reduction, improved candidate experience) and challenges (ethical concerns, algorithmic bias, technical and cultural barriers, and candidate perceptions) associated with these technologies, providing insights for both academic research and HR practice." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Winners and losers when firms robotize: wage effects across occupations and education (2026)
Zitatform
Barth, Erling, Marianne Røed, Pål Schøne & Janis Umblijs (2026): Winners and losers when firms robotize: wage effects across occupations and education. In: The Scandinavian Journal of Economics, Jg. 128, H. 1, S. 3-32. DOI:10.1111/sjoe.12593
Abstract
"This paper analyses the impact of robots on workers' wages in the manufacturing sector, with a particular focus on relative wages for workers with different levels of education and in different occupations. Using high-quality matched employer–employee register data with firm-level information on the introduction of industrial robots, we identify the effects of robotization on relative wages within firms. Skilled blue-collar workers with a vocational degree experience a decline in wages when firms introduce robots, while there are only small effects for the other groups of workers. These results suggest that robots are substitutes for tasks undertaken by skilled blue-collar workers in manufacturing, and furthermore that the adoption of robots contributes to a polarization of the labor market and a hollowing out of the wage distribution, rather than to skill-biased technical change." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Investigating social protection amongst platform workers in Germany: forced individualisation, hybrid income generation and undesired regulation (2026)
Zitatform
Beckmann, Fabian, Sabrina Glanz, Fabian Hoose & Serkan Topal (2026): Investigating social protection amongst platform workers in Germany: forced individualisation, hybrid income generation and undesired regulation. In: Journal of Social Policy, Jg. 55, H. 1, S. 100-118. DOI:10.1017/s0047279424000217
Abstract
"The social protection of platform workers is considered one of the most precarious features and political challenges of this new form of employment. Still, there have only been a few empirical investigations on this issue to date. This article presents an explorative empirical analysis of the social protection of platform workers in Germany – a conservative welfare regime with a strong link between standard employment and institutionalized social protection. On the basis of an online survey amongst 719 self-employed platform workers, we examine how different employment patterns correspond to institutionalized protection against sickness and old age. We empirically explore different protection types and analyse how they differ regarding working conditions in platform work and individual social policy preferences. Findings reveal that conditions of platform work and social protection as well as demands and regulatory preferences vary notably across different clusters of platform workers. Still, the vast majority votes against obligatory social insurances for platform workers and favors self-employment over dependent employment. Against this background, we discuss challenges for future attempts aiming at improving social protection for platform workers. This study adds to the literature by empirically exploring platform workers’ social protection and social policy preferences, which have been overlooked to date." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation Experiments and Inequality (2026)
Zitatform
Benzell, Seth Gordon & Kyle R. Myers (2026): Automation Experiments and Inequality. (NBER working paper / National Bureau of Economic Research 34668), Cambridge, Mass, 26 S., App. DOI:10.3386/w34668
Abstract
"Many experiments study the productivity effects of automation technologies such as generative algorithms. A key test in these experiments relates to inequality: does the technology increase output more for high- or low-skill workers? However, the theoretical content of this empirical test has been unclear. Here, we formalize a theory that describes the experimental effect of automation technologies on worker-level output and, therefore, inequality. Worker-level output depends on a task-level production function, and workers are heterogeneous in their task-level skills. Workers perform a task themselves or delegate it to the automation technology. The inequality effect of improved automation depends on the interaction of two factors: (i) the correlation in task-level skills across workers, and (ii) workers' skills relative to the technology's effective skill. In many cases we study, the inequality effect is non-monotonic --- as technologies improve, inequality decreases then increases. The model and descriptive statistics of skill correlations generally suggest that the diversity of automation technologies will play an important role in the evolution of inequality." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Digital divide and income inequality: causal evidence from Italian provinces (2026)
Zitatform
Bergantino, Angela Stefania, Giulio Fusco, Mario Intini & Gianluca Monturano (2026): Digital divide and income inequality: causal evidence from Italian provinces. In: The Annals of Regional Science, Jg. 75, H. 1. DOI:10.1007/s00168-025-01440-z
Abstract
"The digital economy can function either as a catalyst to stimulate economic growth or else as a driver of socioeconomic inequality when its benefits are unevenly distributed. This study investigates the effect of rural digital connectivity on income inequality in Italy. Utilizing NUTS 3 panel data spanning 2014–2022, we conduct a counterfactual Difference-in-Differences approach with continuous treatment intensity to estimate the impact of introducing rural broadband coverage at speeds of 30 and 100 Mbps on multiple measures of income distribution, including the Gini, Theil, and Atkinson indices. The empirical framework incorporates a comprehensive set of socioeconomic controls, as well as provincial and time fixed effects, to account for unobserved heterogeneity and regional path dependencies. Our findings indicate that broadband expansion is significantly associated with increasing inequality, suggesting that access alone does not guarantee inclusive outcomes, particularly in localities characterized by structural fragility and limited human capital. Additional heterogeneity and spatial analyses demonstrate that these inequality effects are more evident in southern provinces and localities with a higher concentration of inner areas, where the digital divide remains more pronounced. These findings accentuate the dual role of digitalization and highlight the necessity of coordinated policy interventions that combine infrastructure investment with digital skills development, institutional capacity-building, and spatially integrated governance strategies." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Mind the Gap: KI-Einführung in Europa und den USA (2026)
Zitatform
Bick, Alexander, Adam Blandin, David Deming, Nicola Fuchs-Schündeln & Jonas Jessen (2026): Mind the Gap: KI-Einführung in Europa und den USA. (CEPR discussion paper / Centre for Economic Policy Research 21337), London, 80 S.
Abstract
"This paper combines international evidence from worker and firm surveys conducted in 2025 and 2026 to document large gaps in AI adoption, both between the US and Europe and across European countries. Cross-country differences in worker demographics and firm composition account for an important share of these gaps. AI adoption, within and across countries, is also closely linked to firm personnel management practices and whether firms actively encourage AI use by workers. Micro-level evidence suggests that AI generates meaningful time savings for many workers. At the macro level, in recent years industries with higher AI adoption rates have experienced faster productivity growth. While we do not establish causality, this relationship is statistically significant and similar in magnitude in Europe and the US. We find no clear evidence that industry-level AI adoption is associated with employment changes. We discuss limitations of existing data and outline priorities for future data collection to better assess the productivity and labor market effects of AI." (Author's abstract, IAB-Doku) ((en))
Ähnliche Treffer
- spätere (möglicherweise abweichende) Version erschienen u.d.T. "Mind the Gap: AI Adoption in Europe and the US : BPEA Conference Draft, March 26-27, 2026" in: Brookings Papers on Economic Activity, Conference Draft (2026), 1-70
- auch erschienen u.d.T. "Mind the Gap: AI Adoption in Europe and the US" als: RF Berlin - CReAM Discussion Paper Series, 102/26
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Literaturhinweis
Re‐Skilling in the Age of Skill Shortage: Adult Education Rather Than Active Labor Market Policy: Special Issue: Bringing the Ecological and the Social Together in the Green Transition: A Multilevel Analysis (2026)
Zitatform
Bonoli, Giuliano, Patrick Emmenegger & Alina Felder-Stindt (2026): Re‐Skilling in the Age of Skill Shortage: Adult Education Rather Than Active Labor Market Policy. Special Issue: Bringing the Ecological and the Social Together in the Green Transition: A Multilevel Analysis. In: Regulation and governance, Jg. 20, H. 2, S. 482-494. DOI:10.1111/rego.70065
Abstract
"European economies face the task of providing the necessary skills for the “twin transition ” in a period of skill shortage. As a result, we may expect countries to reorient their labor market policy towards re-skilling. We look for evidence of a reorientation in two relevant policy fields: active labor market policy (ALMP) and adult education (AE). We explore general trends in both fields based on quantitative indicators and compare recent policy developments in four countries with strong ALMP and AE sectors: Denmark, France, Germany, and Sweden. We do not observe clear evidence of a general movement away from activation and towards re-skilling in ALMP. However, in AE, we identify several re-skilling initiatives that address skill shortages. Relying on insights from queuing theories of hiring and training, we argue that due to changes in the population targeted by ALMP, the locus of re-skilling policy is increasingly moving towards AE." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Der KI-Irrtum: Warum Deutschland auf Zuwanderung angewiesen ist: Leitartikel (2026)
Zitatform
Brücker, Herbert, Yuliya Kosyakova & Enzo Weber (2026): Der KI-Irrtum: Warum Deutschland auf Zuwanderung angewiesen ist. Leitartikel. In: Wirtschaftsdienst, Jg. 106, H. 5, S. 304-305. DOI:10.2478/wd-2026-0074
Abstract
"Sieben Millionen - so viele Arbeitskräfte wird Deutschland in den nächsten 15 Jahren allein aufgrund des demografischen Wandels verlieren. Bereits seit vielen Jahren ist der demografische Effekt negativ, mit mehr als 400.000 Arbeitskräften pro Jahr. Tatsächlich beginnt der deutsche Arbeitsmarkt jedoch erst jetzt zu schrumpfen. Denn bislang konnte dieser Rückgang überkompensiert werden - durch eine steigende Erwerbsbeteiligung von Älteren und Frauen; und vor allem durch Zuwanderung. Doch diese Ausgleichsmechanismen stoßen zunehmend an Grenzen. Europa altert insgesamt, und die Dynamik der Zuwanderung innerhalb Europas nimmt ab. Zugleich sind viele der besonders mobilen, jüngeren Kohorten bereits gewandert. Vor diesem Hintergrund wird Migration schwieriger - und genau hier setzt ein verbreitetes Argument an: Wenn Künstliche Intelligenz (KI) zunehmend Aufgaben übernimmt, braucht man doch keine zusätzlichen Arbeitskräfte mehr. Diese Folgerung ist ein Trugschluss. Arbeitskräfteknappheit lässt sich gesamtwirtschaftlich nicht einfach wegdigitalisieren." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Crowdwork als Beruf?: Subjektivierung, Kompetenzerwerb und Lernen in der digitalen Plattformarbeit (2026)
Büchter, Karin; Li-Gottwald, Jiayin; Kleemann, Frank; Schlömer, Tobias; Eckelt, Marcus; Krzywdzinski, Martin ;Zitatform
Büchter, Karin, Tobias Schlömer, Frank Kleemann, Martin Krzywdzinski, Marcus Eckelt & Jiayin Li-Gottwald (Hrsg.) (2026): Crowdwork als Beruf? Subjektivierung, Kompetenzerwerb und Lernen in der digitalen Plattformarbeit. Verlag Barbara Budrich: Berlin, 314 S. DOI:10.3224/84743131
Abstract
"Crowdwork ist eine junge Arbeitsform, bei der einzelne Arbeitstätigkeiten über Online-Plattformen an externe Arbeitskräfte vergeben werden. Der Band präsentiert Erkenntnisse aus einem breit angelegten Forschungsprojekt, in dem arbeitssoziologische, berufs- und wirtschaftspädagogische Perspektiven auf das Tätigsein, auf Lernpraktiken von Crowdworker*innen und auf die individuelle Bedeutung plattformbasierter Arbeit eingenommen werden. Die Beiträge setzen sich mit Aspekten wie Subjektivierung, Wissensgenerierung, Kompetenzentwicklung, Beruflichkeit und Lernen in der plattformbasierten Arbeit auseinander." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Making digital welfare work: conceptualizing digital compensatory work by frontline professionals (2026)
Carlsson, Julia S.; Svensson, Petra M.; Hjärpe, Teres;Zitatform
Carlsson, Julia S., Teres Hjärpe & Petra M. Svensson (2026): Making digital welfare work: conceptualizing digital compensatory work by frontline professionals. In: Journal of Professions and Organization, Jg. 13, H. 3, S. 1-17. DOI:10.1093/jpo/joag011
Abstract
"Digital technologies in welfare organizations frequently generate gaps, ambiguities, and misalignments that require professional intervention. Yet prior research has tended to portray frontline workers mainly as resistant or adaptive actors, leaving under-examined their active contributions to sustaining broader digital infrastructures. This article introduces the concept of digital compensatory work to capture how professionals intervene when specific digital technologies fall short of their own standards for professional service delivery. Drawing on an exploratory literature review, we identify three forms of such compensatory work: complementing digital technologies, rectifying their shortcomings, and dismissing them when they conflict with professional judgment. By theorizing these practices, the article expands existing understandings of professional discretion in digital welfare services, shifting attention from resistance and adaptation to value-driven interventions that actively uphold service quality within digital infrastructures. In doing so, it contributes to debates on digital welfare and highlights the essential role of professional agency in sustaining human service organizations under conditions of digital transformation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Revisiting the occupational impact of AI in the generative AI era (2026)
Casas, P.; González-Vázquez, I.; Salotti, S.; Martínez-Plumed, F.; Gómez, E.; Fernández-Macías, E.;Zitatform
Casas, P., E. Fernández-Macías, F. Martínez-Plumed, E. Gómez, I. González-Vázquez & S. Salotti (2026): Revisiting the occupational impact of AI in the generative AI era. (JRC working papers series on labour, education and technology 2026,02), Sevilla, 71 S.
Abstract
"Generative AI is reshaping what artificial intelligence can do in the workplace, calling into question pre-GenAI assessments of which workers and tasks are most exposed. In this paper we trace the evolution of AI exposure in the European labour market from 2008 to 2024 by linking 352 AI benchmarks to 14 cognitive abilities, 108 work tasks and 127 ISCO-3 occupations, weighting benchmarks by their research intensity in the AI literature and thus deriving AI exposure by cognitive ability. Bundling work tasks into occupations based on intensity indicators, we explore occupational exposure to AI. We find that the cognitive abilities most exposed to the recent surge of AI research are ideas-related, such as attention and search, comprehension and expression and logical reasoning. Because the associated information processing and problem-solving tasks are the most transversal across occupations, we find an exponential increase in AI exposure across all occupational categories of workers, even though comparatively high-skilled occupations are more exposed than elementary occupations. This points at a substantial and transversal labour market impact of AI." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
How welfare states influence online platform work in Europe (2026)
Zitatform
Chueri, Juliana & Petter Törnberg (2026): How welfare states influence online platform work in Europe. In: Journal of European Social Policy, Jg. 36, H. 2, S. 119-135. DOI:10.1177/09589287251357463
Abstract
"Digital labor platforms are reshaping global labor markets by enabling the transnational contracting of service workers. While the dominant perspective emphasizes market forces, predicting that lower-wage countries will dominate the supply side, this view overlooks the institutional context in which platform labor emerges. This paper advances the argument that national welfare institutions are key to shaping participation in the platform economy. We provide the first large-scale cross-national comparative analysis of platform labor, combining micro-level data from one of the world’s largest remote work platforms with country-level indicators from 26 European countries. In line with market expectations, we find that lower-wage countries supply most low-skilled labor, while higher-wage countries show a more balanced distribution between low- and high-skilled workers. Crucially, however, our analysis reveals that greater welfare state generosity is associated with lower levels of platform participation, especially in low-skilled occupations. We argue that platform labor cannot be understood solely as a function of technological change or wage differentials. It is also an expression of structural constraints: where social protections are weak, people are more likely to turn to precarious forms of online work." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The EU compromise machine and the politicisation of social policy: Lessons from the regulation of platform work (2026)
Zitatform
Crespy, Amandine, Bastian Kenn, Matteo Marenco & Slavina Spasova (2026): The EU compromise machine and the politicisation of social policy: Lessons from the regulation of platform work. In: Journal of European Social Policy, Jg. 36, H. 1, S. 18-33. DOI:10.1177/09589287251345912
Abstract
"Over the past few years, the legal status and the working conditions of platform workers have been among the most debated manifestations of the digital transformation of work. Tense negotiations on the EU platform work directive (from 2021 to 2024) epitomize long-standing conflicts in EU social policymaking, namely the opposition between capital and labor, on the one hand, and resistance to EU involvement or impact on Member States’ social arrangements, on the other. This paper provides an in-depth inquiry of the policy process by focussing specifically on the presumption of employment in platform work, which was first proposed as an EU-wide provision and eventually nationalized with its definition left to national arrangements. Drawing on this case and mobilizing the literature on positive integration entrepreneurship, and politicization, we shed light on the ‘drivers’ and ‘inhibitors’ of EU social regulation. On the one hand, we provide evidence that joint entrepreneurship of the European Parliament (EP) and the European Commission is a primary driver and argue for acknowledging the role of the EP as a key entrepreneur of ‘Social Europe’. On the other hand, divisions in the Council, underpinned by domestic politics, hinder ambitious social policy regulation at EU level in several respects. Furthermore, we tease out the role of politicization and theorize its ambivalent role as both a driver and inhibitor, depending on contingent party political orientations, contextual factors, but also the role played by Council presidencies, so far overlooked in the literature. We conclude that the drivers and inhibitors we identify, and the resulting dynamics of compromise, are relevant beyond the case of platform work. While stressing the crucial, yet ambivalent, role of politicization, our findings cast a shadow on what has recently been described as a great come back of ‘Social Europe’ with the European Pillar of Social Rights." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Biased by Design? Case Managers' Multidimensional Preferences Toward the Design of Algorithmic Decision Support Systems (2026)
Zitatform
Dietz, Martin, Christopher Osiander, Mareike Sirman-Winkler & Markus Tepe (2026): Biased by Design? Case Managers' Multidimensional Preferences Toward the Design of Algorithmic Decision Support Systems. In: Public Administration Review, S. 1-14. DOI:10.1111/puar.70111
Abstract
"This study examines whether street-level bureaucrats' preferences toward algorithmic decision support (ADS) induce a unilateral shift of technology-related risks onto clients of the public employment service. Expanding on public value theory and research on moral agency in public service work, we argue that case managers' choices of ADS designs are shaped by a plurality of professional, service, and efficiency values. To test this argument, we conducted a conjoint experiment on a representative sample of German Federal Employment Agency case managers. Respondents compared pairs of hypothetical ADS systems that differed in their design features, reflecting varying degrees of the realization of public values. The empirical results indicate that case managers' choices do not result in biased design. Instead, case managers balance design features reflecting professional and service values while maintaining administrative efficiency. Case managers appreciate ADS support but firmly reject the mandatory use of such advice." (Author's abstract, IAB-Doku, © Wiley) ((en))
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Literaturhinweis
Algorithmic Profiling: Effective Tool for Targeting Active Labour Market Policies? (2026)
Zitatform
Eppel, Rainer, Ulrike Huemer, Helmut Mahringer & Lukas Schmoigl (2026): Algorithmic Profiling: Effective Tool for Targeting Active Labour Market Policies? In: Labour, S. 1-20. DOI:10.1111/labr.70013
Abstract
"Digitisation has sparked interest in automated decision making in Public Employment Services (PES). We evaluate an algorithmic profiling model in Austria that predicts the reemployment prospects of unemployed individuals to classify and assign them to active labour market policies. Our analysis shows that reallocating resources from jobseekers with low to medium prospects, as proposed by the PES, does not yield the expected efficiency gains. We find no systematic evidence that programmes are less effective for individuals with low predicted employment prospects than for those with medium prospects. These findings caution against crude algorithmic profiling and highlight the need for nuanced targeting strategies that prioritise the most disadvantaged jobseekers." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))
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Literaturhinweis
Digitalisierung der Arbeitswelt - Fluch und Segen zugleich (2026)
Franke, Andreas; Hildt, Elisabeth;Zitatform
Franke, Andreas & Elisabeth Hildt (2026): Digitalisierung der Arbeitswelt - Fluch und Segen zugleich. In: IAB-Forum H. 16.03.2026. DOI:10.48720/IAB.FOO.20260316.01
Abstract
"Die Arbeitswelt unterliegt seit einigen Jahren einer rasanten Digitalisierung. Damit sind sowohl Chancen als auch Risiken für die psychische Gesundheit der Beschäftigten verbunden. Zudem ergeben sich daraus handfeste ethische Implikationen. So droht nicht zuletzt ein Gerechtigkeitsproblem, weil bestimmte Gruppen von Beschäftigten eher Gefahr laufen als andere, durch die Digitalisierung Nachteile zu erfahren und mit der digitalen Entwicklung nicht mehr Schritt halten zu können." (Autorenreferat, IAB-Doku)
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Literaturhinweis
App-based delivery services in Germany: Why people take up gig-work and usually quit quickly (2026)
Zitatform
Friedrich, Martin, Ines Helm, Ramona Jost, Julia Lang & Christoph Müller (2026): App-based delivery services in Germany: Why people take up gig-work and usually quit quickly. In: IAB-Forum H. 27.04.2026. DOI:10.48720/IAB.FOO.20260427.01
Abstract
"App-based delivery services have spread rapidly in Germany in recent years. This has also fuelled public debate about the poor working conditions of the gig-workers in these services. However, there is still little reliable information about what motivates people to take on gig-work. Similarly, little is known about workers’ reasons for leaving these mostly short-term jobs." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Künstliche Intelligenz in deutschen Betrieben: Jeder vierte Betrieb nutzt mittlerweile generative KI (2026)
Zitatform
Friedrich, Martin & Christian Kagerl (2026): Künstliche Intelligenz in deutschen Betrieben: Jeder vierte Betrieb nutzt mittlerweile generative KI. (IAB-Kurzbericht 08/2026), Nürnberg, 8 S. DOI:10.48720/IAB.KB.2608
Abstract
"Generativer Künstlicher Intelligenz (KI) wird häufig bescheinigt, die Wirtschaft fundamental zu verändern. Wie verbreitet diese Technologie bereits in deutschen Betrieben ist, zeigen aktuelle Auswertungen aus dem IAB-Betriebspanel. Daten zum Themenschwerpunkt „Generative KI“ wurden 2025 erstmals erhoben." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
- Generative KI in deutschen Betrieben
- Weiterbildung und Regelungen zum Umgang mit der Technologie in Betrieben, die generative KI nutzen
- IAB-Forum Video
- Verbreitung von KI nach Betriebsgröße, Betriebsalter und Branchen
- Entwicklung des betrieblichen Einsatzes von KI
- Art des betrieblichen Einsatzes von KI
- Determinanten der Wahrscheinlichkeit, generative KI im Betrieb zu nutzen
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Literaturhinweis
Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? (2026)
Zitatform
Gallo, Giovanni & Amparo Nagore García (2026): Retirement decisions in the age of COVID-19 pandemic: are older employees in digital occupations working longer? In: Review of Economics of the Household, S. 1-34. DOI:10.1007/s11150-025-09827-9
Abstract
"This paper investigates the retirement response to the pandemic and to the resulting acceleration in the adoption of new technologies. Using the European Union Statistics of Income and Living Conditions datasets and leveraging the natural experiment of many workers being forced to work from home in Europe during the lockdown, we compare the retirement response of older workers in digital occupations (i.e. more exposed to the accelerated adoption of new technologies) versus non-digital occupations to detect any differences in retirement behaviour, which we interpret as digitalization effects. In addition, we analyze changes in retirement decisions by gender and geographic area. We find that retirement rates increased during COVID-19 in Europe, especially in Mediterranean countries and among women. This trend may be linked to gender occupational segregation. In Mediterranean countries, digitalization increases female retirement, likely due to challenges in balancing digital work and family responsibilities while working from home. In Eastern countries, and to a lesser extent in Northern countries, digitalization leads to postponing retirement among women, likely due to greater gender equality in unpaid work. In contrast, the retirement age for men is less affected by the pandemic with no significant differences between digital and non-digital occupations. This may exacerbate the existing gender gap in labor force participation and pension outcomes." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
AI‐powered skill classification: mapping technology intensity in the German labour market (2026)
Zitatform
Genz, Sabrina, Terry Gregory & Florian Lehmer (2026): AI‐powered skill classification: mapping technology intensity in the German labour market. In: Fiscal Studies, Jg. 47, H. 1, S. 25-51., 2026-02-20. DOI:10.1111/1475-5890.70020
Abstract
"The rapid evolution of technology is reshaping labour markets by altering skill demands and job profiles. This paper introduces a novel skill-based measure of occupational technology intensity – the occupational technology skill share (OTSS) – that distinguishes between manual, digital and frontier technologies, including artificial intelligence (AI). Using natural language processing, generative AI and supervised machine learning, we develop an AI-powered skill classification that enriches occupation-linked skill labels with standardised GenAI-generated descriptions and structured indicators of technological content, enabling transparent classification by technology intensity. We compute OTSS for all occupations in the German labour market. For the average worker in 2023, manual technologies account for the largest share of skill content (42 per cent), followed by digital (38 per cent) and frontier technologies (20 per cent). Frontier technologies remain concentrated in specialised occupations, while digital technologies are widespread. Linking these measures to administrative data from 2012 to 2023 shows a broad shift from manual and digital toward frontier skills across occupations, and reveals a non-linear, U-shaped relationship between changes in frontier skill intensity and employment growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Labour productivity gains or offshoring? Implications for post-growth proposals on the future of work (2026)
Zitatform
Godé, Lukas, Simon Mair & Erik Gómez-Baggethun (2026): Labour productivity gains or offshoring? Implications for post-growth proposals on the future of work. In: Ecological economics, Jg. 239. DOI:10.1016/j.ecolecon.2025.108778
Abstract
"Two visions prevail about the future of work in sustainable post-growth economies. According to the first, labour productivity gains resulting from technological development will enable to work less. The second contends instead that such gains are not always desirable and could be constrained by a shift towards less polluting production, potentially resulting in more work. Yet, conventional measures of labour productivity on which these proposals are based can conceal a displacement of labour requirements abroad. In this paper, we conduct a case study on Germany in 1995 –2020 to assess whether and to which extent labour productivity gainsresult from offshoring, and implications for post-growth proposals on the future of work. We first retrieve global labour requirements of German production across upstream supply chains. We then decompose conventional labour productivity gains to evaluate whether they result from a reduction in global labour requirements or of their increased displacement towards upstream sectors. Finally, we examine possible impacts on labour offshoring of shifting production to sectors with low productivity gains. We use a socially extended Multi-Regional Input-Output model based on OECD data. Our results show that a quarter of the global labour requirements for German production is provided abroad. This share increased until 2007 before it stabilized or decreased. We identify some potential for working time reduction without increases in labour offshoring. Shifting to service sectors could furthermore reduce labour offshoring relative to production. Yet critically, German production may cover only a fraction of domestic consumption. Related implications for post-growth proposals require further attention." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
AI-Powered Skill Classification: Mapping Technology Intensity in the German Labor Market (2026)
Zitatform
Grenz, Sabrina, Terry Gregory & Florian Lehmer (2026): AI-Powered Skill Classification: Mapping Technology Intensity in the German Labor Market. (IZA discussion paper / IZA Network @ LISER 18415), Bonn, 47 S.
Abstract
"The rapid evolution of technology is reshaping labor markets by altering skill demands and job profiles. This paper introduces a novel skill-based measure of occupational technology intensity – the Occupational Technology Skill Share (OTSS) – that distinguishes between manual, digital, and frontier technologies, including artificial intelligence (AI). Using natural language processing, generative AI, and supervised machine learning, we develop an AI-powered skill classification that enriches occupationlinked skill labels with standardized GenAI-generated descriptions and structured indicators of technological content, enabling transparent classification by technology intensity. We compute OTSS for all occupations in the German labor market. For the average worker in 2023, manual technologies account for the largest share of skill content (42%), followed by digital (38%) and frontier technologies (20%). Frontier technologies remain concentrated in specialized occupations, while digital technologies are widespread. Linking these measures to administrative data from 2012–2023 shows a broad shift from manual and digital toward frontier skills across occupations, and reveals a non-linear, U-shaped relationship between changes in frontier skill intensity and employment growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Generative AI and Career Choices (2026)
Zitatform
Gschwendt, Christian, Martina Viarengo & Thea S. Zoellner (2026): Generative AI and Career Choices. (Working paper / Swiss Leading House 251), Zürich, 52 S.
Abstract
"The economic impact of technological change will critically depend on how future workers invest in their human capital. Yet, little is known about how future workers themselves evaluate and choose their educational and occupational paths in light of emerging technologies. This paper examines how adolescents currently at the school-to-work transition stage value working with generative artificial intelligence (GenAI) in their future occupations, and how automation risk and opportunities for continuing education shape these preferences. We field a discrete-choice experiment among a nationally representative sample of over 7,000 Swiss adolescents aged around 15. We find that adolescents generally exhibit an aversion to collaborating with GenAI at work, with females consistently more averse than males. However, preferences are nuanced: adolescents welcome greater GenAI collaboration, provided that GenAI usage levels remain moderate and that it is not accompanied by increases in job-automation risk. Finally, continuing education opportunities in occupations improve attitudes towards working with GenAI across genders. Our results challenge simple narratives of technology acceptance or rejection, revealing that adolescents' willingness to work with GenAI depends on how it is implemented — its intensity, associated displacement risks, and accompanying skill development - rather than the technology itself. Our findings suggest that the way future workers value GenAI collaboration in their career choices critically depends on its intensity and on the interplay with automation risk and AI-related educational opportunities." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Automation, skill and job creation (2026)
Zitatform
Guo, Kaizhao (2026): Automation, skill and job creation. In: Empirical economics, Jg. 70, H. 5. DOI:10.1007/s00181-026-02912-7
Abstract
"This paper explores the heterogeneous effects of automation technologies on employment rate across US regions from different income groups, and investigates mechanisms through proportion of skilled workers. Automation, measured by both robotic penetration and ICT trade volumes, is replacing labour force. Exploiting variations across US commuting zones, this study finds that employment reductions are significant and substantial in low and middle income areas, and rising income levels could cause insignificant employment responses. Leveraging shift-share IV strategies and generalised model specifications, further evidence suggests that a simple net job creation channel can explain these patterns. Specifically, displacement effects outweigh productivity effects in low income CZs with lower proportion of skilled labour, and job losses are larger in middle income CZs with concentration of routine occupations; job creations are complementing job destructions with growing income levels and higher skill shares. These technical changes are particularly significant in manufacturing sectors." (Author's abstract, IAB-Doku, © Springer-Verlag) ((en))
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Literaturhinweis
Arbeitszeit, Produktivität, KI - wie Deutschland sein Arbeitskräfteangebot stabilisieren kann: Teil des Zeitgesprächs "Arbeitszeit im Wandel - Wie sich Wohlstand trotz sinkenden Arbeitskräfteangebots sichern lässt" (2026)
Hammermann, Andrea; Stettes, Oliver;Zitatform
Hammermann, Andrea & Oliver Stettes (2026): Arbeitszeit, Produktivität, KI - wie Deutschland sein Arbeitskräfteangebot stabilisieren kann. Teil des Zeitgesprächs "Arbeitszeit im Wandel - Wie sich Wohlstand trotz sinkenden Arbeitskräfteangebots sichern lässt". In: Wirtschaftsdienst, Jg. 106, H. 4, S. 248-252. DOI:10.2478/wd-2026-0064
Abstract
"Längere Arbeitszeiten können einen wichtigen Beitrag zur Stabilisierung des Arbeitskräfteangebots leisten, während Investitionen in technologischen und organisatorischen Fortschritt notwendig sind, um die Arbeitsproduktivität zu steigern. Vor diesem Hintergrund geht der Beitrag der Frage nach, wie sich das Arbeitskräfteangebot in Deutschland trotz des demografischen Wandels stabilisieren und der Wohlstand langfristig sichern lässt. Empirische Befunde legen nahe, dass KI und Humankapital in der Regel komplementär wirken und KIAnwendungen menschliche Arbeit eher ergänzen als ersetzen. Entscheidend für den Erhalt des Wohlstands ist somit, beide Hebel – Arbeitszeitund Produktivität – gemeinsam zu nutzen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Automatisierung und Weiterbildung: Weiterbildungslücke in gefährdeten Berufen: Zur Diskussion gestellt (2026)
Zitatform
Heß, Pascal, Simon Janssen & Ute Leber (2026): Automatisierung und Weiterbildung: Weiterbildungslücke in gefährdeten Berufen. Zur Diskussion gestellt. In: Ifo-Schnelldienst, Jg. 79, H. 03, S. 18-21., 2026-03-19.
Abstract
"Technologischer Wandel erhöht den Bedarf an Weiterbildung und lebenslangem Lernen. Neue empirische Evidenz für Deutschland zeigt jedoch, dass Beschäftigte in Berufen mit hoher Automatisierungsgefährdung seltener an Weiterbildung teilnehmen als Beschäftigte in weniger gefährdeten Tätigkeiten. Die Weiterbildungslücke betrifft insbesondere mittelqualifizierte und männliche Beschäftigte sowie zukunftsrelevante Kompetenzen wie IT- und soziale Fähigkeiten. Der Befund lässt sich wesentlich durch geringere betriebliche Weiterbildungsinvestitionen erklären. Die Ergebnisse verdeutlichen einen Zielkonflikt zwischen betrieblicher Investitionslogik und gesamtwirtschaftlichem Qualifizierungsbedarf." (Autorenreferat, IAB-Doku)
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Literaturhinweis
The impact of AI on global knowledge work (2026)
Ide, Enrique; Talamas, Eduard;Zitatform
Ide, Enrique & Eduard Talamas (2026): The impact of AI on global knowledge work. In: Journal of monetary economics, Jg. 157. DOI:10.1016/j.jmoneco.2025.103876
Abstract
"We analyze how Artificial Intelligence (AI) reshapes global knowledge work in a two-region world where firms organize production hierarchically to use knowledge efficiently: the most knowledgeable individuals specialize in problem-solving, while others perform routine work. Before AI, the Advanced Economy specializes in problem-solving services, whereas the Emerging Economy focuses on routine work. AI converts compute — which is located in the Advanced Economy — into autonomous “AI agents” that perfectly substitute for humans with a given level of knowledge. Basic AI reduces the Advanced Economy ’s net exports of problem-solving services, potentially reversing pre-AI trade patterns. In contrast, sophisticated AI expands these exports, reinforcing existing trade patterns. Finally, we show that a global ban on AI autonomy redistributes AI’s gains toward lower-skilled workers, while a regional ban — such as prohibiting autonomy only in the Emerging Economy — offers little benefit to lower-skilled workers and harms the most knowledgeable individuals in that region." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Online platforms' organizational resources and gig workers' self-leadership (2026)
Ihl, Andreas; Mayer, Anne-Sophie;Zitatform
Ihl, Andreas & Anne-Sophie Mayer (2026): Online platforms' organizational resources and gig workers' self-leadership. In: Journal of vocational behavior, Jg. 166. DOI:10.1016/j.jvb.2026.104214
Abstract
"An increasing number of gig workers turn to online gig work platforms to pursue potentially boundaryless and protean careers outside traditional organizational settings. Proactive career self-management and related self-leadership are essential to succeed in such careers. However, while traditional organizations facilitate self-leadership by providing traditional organizational resources, such as supportive human resource practices, gig work lacks these important resources. As a result, cultivating self-leadership among gig workers remains a considerable challenge. This study addresses this challenge by investigating how online platforms that centrally shape work environments may provide a resource-related context that facilitates gig workers' self-leadership strategies. Using a contextual and systemic approach to career self-management and inspired by the conservation of resources theory, we draw on insights from a 14-month field study of an online gig work platform, involving data collected from multiple sources. The findings show how platforms offer various types of platform-embedded resources and how workers utilize these resources to engage in behavior- and cognitive-focused self-leadership strategies. This study thereby contributes to the literature on careers in gig work by theorizing the role of online platforms in shaping gig workers' careers from a proactive and agentic perspective." (Author's abstract, IAB-Doku, © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))
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Literaturhinweis
Digital Gender Gap: Schwerpunkt 2026 Künstliche Intelligenz (2026)
Zitatform
Jahn, Sandy, Carola Burkert, Katharina Diener & Britta Matthes (2026): Digital Gender Gap. Schwerpunkt 2026 Künstliche Intelligenz. Berlin, 20 S. DOI:10.48720/IAB.D21.2026
Abstract
"Künstliche Intelligenz wird immer mehr zur Schlüsselressource. Ihre Nutzung entscheidet zunehmend über Wettbewerbsfähigkeit, Beschäftigungschancen und gesellschaftliche Teilhabe – vergleichbar mit Alphabetisierung oder Internetzugang in früheren Transformationsphasen. Die Studie des IAB und der Initiative D 21 zeigt: Es besteht ein signifikanter Gender AI Gap. Frauen nutzen KI-Anwendungen seltener und weniger intensiv als Männer (rund 16 Prozentpunkte Unterschied in der Ausgangsbetrachtung). Wenn Unterschiede in Alter, Bildung, Einkommen, beruflichem Kontext sowie Kompetenzen und Einstellungen statistisch berücksichtigt werden, verringert sich die Lücke zwar – bleibt aber auch dann bestehen (rund 8 Prozentpunkte)." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Interview mit den Autorinnen im Online-Magazin IAB-Forum -
Literaturhinweis
Der Gender AI Gap: "KI wird zur Schlüsselressource - aber Männer und Frauen nutzen sie nicht gleich" (2026)
Zitatform
Keitel, Christiane; Katharina Diener, Britta Matthes, Sandy Jahn & Carola Burkert (interviewte Person) (2026): Der Gender AI Gap: "KI wird zur Schlüsselressource - aber Männer und Frauen nutzen sie nicht gleich". In: IAB-Forum H. 23.04.2026. DOI:10.48720/IAB.FOO.20260423.01
Abstract
"Mit der rasanten Verbreitung von Künstlicher Intelligenz in der Arbeitswelt entsteht eine neue Lücke zwischen den Geschlechtern: der Gender AI Gap. Dies zeigt eine aktuelle Studie des IAB, die in Zusammenarbeit mit der Initiative D21 entstanden ist, Deutschlands größtem gemeinnützigen Netzwerk für die digitale Gesellschaft. Der Studie zufolge nutzen Frauen KI deutlich seltener und weniger intensiv nutzen als Männer – selbst bei vergleichbaren Voraussetzungen. Warum das so ist, welche Rolle Netzwerke und Wahrnehmungen spielen, und an welchen Stellschrauben Politik und Betriebe jetzt ansetzen müssen, erläutern die Autorinnen der Studie im Interview." (Autorenreferat, IAB-Doku)
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Literaturhinweis
„Es geht nicht darum, was KI uns wegnehmen könnte, sondern welche Chancen entstehen“ (2026)
Zitatform
Keitel, Christiane; Britta Matthes & Katharina Grienberger (interviewte Person) (2026): „Es geht nicht darum, was KI uns wegnehmen könnte, sondern welche Chancen entstehen“. In: IAB-Forum H. 11.05.2026. DOI:10.48720/IAB.FOO.20260511.01
Abstract
"Der IAB-Job-Futuromat zeigt, welche beruflichen Tätigkeiten durch digitale Technologien und KI potenziell automatisierbar sind – und welche nicht. Im Interview erklären die Forscherinnen Britta Matthes und Katharina Grienberger, wie das Tool funktioniert, welche Berufe besonders betroffen sind und warum es bei der Berufswahl nicht um die Angst vor der Automatisierbarkeit, sondern vielmehr um Chancen gehen sollte." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Strukturwandel in Thüringen: Digitalisierung. Mit einer Neuschätzung der Substituierbarkeitspotenziale (2026)
Kropp, Per; Fritzsche, Birgit; Theuer, Stefan;Zitatform
Kropp, Per, Stefan Theuer & Birgit Fritzsche (2026): Strukturwandel in Thüringen: Digitalisierung. Mit einer Neuschätzung der Substituierbarkeitspotenziale. (IAB-Regional. Berichte und Analysen aus dem Regionalen Forschungsnetz. IAB Sachsen-Anhalt-Thüringen 02/2026), Nürnberg, 42 S. DOI:10.48720/IAB.RESAT.2602
Abstract
"Die Arbeitswelt verändert sich in rasant. Technische Entwicklungen bei Software, Computer oder computergesteuerten Maschinen schaffen immer neue Anwendungsmöglichkeiten. Bislang waren insbesondere Routinetätigkeiten z. B. bei Helfertätigkeiten automatisierbar. Nun sind durch produktiv nutzbare KI-Technologie auch zunehmend nicht-routine-Tätigkeiten von Spezialisten und Experten betroffen. Im Vergleich zu Deutschland hatte Thüringen häufiger Berufe mit einem hohen Substituierbarkeitspotenzial. Das durchschnittliche Substituierbarkeitspotenzial über alle Berufe stieg bis 2016 rasant an, seitdem jedoch im geringeren Ausmaß. Sicherheitsberufe hatten 2019 mit rund 21 Prozentpunkten einen sehr hohen Anstieg, so wie zuletzt die IT- und naturwissenschaftlichen Dienstleistungsberufe mit rund 20 Prozentpunkten. Für diese Veränderungen konnten drei Faktoren identifiziert werden: die Veränderung der Substituierbarkeitspotenziale einzelner Berufe, innerberufliche Veränderungen wie bei den Kerntätigkeiten und der berufliche Strukturwandel. Für Männer und Frauen sind die Substituierbarkeitspotenziale seit 2013 ähnlich gestiegen, bei Männern allerdings von einem höheren Anfangsniveau. KI ersetzt dabei eher Tätigkeiten, die mehrheitlich von Frauen erledigt werden. Zwischen den verschiedenen Alterskohorten gibt es insgesamt kaum Unterschiede. Lediglich in zwei Berufssegmenten haben jüngere Beschäftigte ein höheres Substitutionspotenzial – bei Verkehrs- und Logistikberufen sowie bei den IT- und naturwissenschaftlichen Dienstleistungsberufen. Auch wenn sich einige Berufe durch Digitalisierung stark verändern führt das kaum zu Beschäftigungsverlusten. Für solche Berufe und für Regionen, in denen sie vermehrt vorkommen, können jedoch höhere Weiterbildungsbedarfe vermutet werden." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Online-Anhänge zu Substituierbarkeitspotenzialen in Thüringen (nicht barrierefrei) -
Literaturhinweis
Gestaltungsprinzipien individueller Beruflichkeit am Beispiel von Crowdworker:innen: Theoretische Ansätze und empirische Ergebnisse zum Zusammenhang von Arbeit, Beruf und Subjektivierung (2026)
Külpmann, Inga;Zitatform
Külpmann, Inga (2026): Gestaltungsprinzipien individueller Beruflichkeit am Beispiel von Crowdworker:innen. Theoretische Ansätze und empirische Ergebnisse zum Zusammenhang von Arbeit, Beruf und Subjektivierung. (Berufsbildung, Arbeit und Innovation. Dissertationen, Habilitationen 92), Bielefeld: wbv, 352 S. DOI:10.3278/9783763979080
Abstract
"Die Studie untersucht, wie Crowdworker:innen in Plattformarbeit individuelle Beruflichkeit entwickeln und wie Arbeitserfahrungen Subjektivierung prägen. Im Mittelpunkt steht die Frage, welche Gestaltungsprinzipien Lern- und Entwicklungspotenziale in Crowdwork unterstützen. Aus berufs- und wirtschaftspädagogischer sowie arbeitssoziologischer Perspektive verbindet die Publikation theoretische Ansätze zu Arbeit, Beruf und Subjektivierung mit empirischen Ergebnissen aus Untersuchungen von Crowdwork-Plattformen in Deutschland. Die Ergebnisse werden im Kontext des Forschungsprojekts CKoBeLeP (2021-2024) eingeordnet und auf Implikationen für lernförderliche Plattformgestaltung bezogen. Geeignet für Studierende und Forschende der Berufs- und Wirtschaftspädagogik, Arbeitssoziologie und Digitalisierungsforschung sowie für Akteur:innen in Arbeitsgestaltung, Weiterbildung und Plattformregulierung." (Verlagsangaben, IAB-Doku)
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Literaturhinweis
Automation and the risk of labor market exclusion across Europe (2026)
Zitatform
Lamperti, Fabio & Davide Castellani (2026): Automation and the risk of labor market exclusion across Europe. In: Structural Change and Economic Dynamics, Jg. 77, S. 62-76. DOI:10.1016/j.strueco.2025.12.014
Abstract
"Labor market exclusion represents a major concern in several European economies, particularly affecting highly exposed demographic groups. This paper examines the potential effect of automation technologies on the risk of being locked into protracted unemployment or inactivity, using Labour Force Survey data for the European Union 27 countries and the United Kingdom, between 2009 and 2019. Our study employs repeated cross-sections of individual-level data to compute probabilities of exclusion outcomes due to automation adoption, controlling for several individual, macroeconomic, and region-specific characteristics, and for potential selection mechanisms. Findings highlight that, on average, the adoption of new automation technologies is associated with a higher probability of being inactive. This is consistent with the view that automation may exacerbate job insecurity, psychological discouragement, and detachment from job-seeking. This relationship is heterogeneous across demographic groups, with younger individuals being relatively more affected." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
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Literaturhinweis
Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation? (2026)
Li, Wensu; Lyu, Harry; Goehring, Brian C.; Aboutorabi, Atin; Qian, Kaizhi; Thompson, Neil; Fleming, Martin;Zitatform
Li, Wensu, Atin Aboutorabi, Harry Lyu, Kaizhi Qian, Martin Fleming, Brian C. Goehring & Neil Thompson (2026): Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation? (arXiv papers 2603.29121), 57 S.
Abstract
"This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation. On the supply side, we estimate an AI production function via scaling-law experiments linking performance to data, compute, and model size. Because AI systems exhibit predictable but diminishing returns to these inputs, the cost of higher accuracy is convex: good performance may be inexpensive, but near-perfect accuracy is disproportionately costly. Full automation is therefore often not cost-minimizing; partial automation, where firms retain human workers for residual tasks, frequently emerges as the equilibrium. On the demand side, we introduce an entropy-based measure of task complexity that maps model accuracy into a labor substitution ratio, quantifying human labor displacement at each accuracy level. We calibrate the framework with O*NET task data, a survey of 3,778 domain experts, and GPT-4o-derived task decompositions, implementing it in computer vision. Task complexity shapes substitution: low-complexity tasks see high substitution, while high-complexity tasks favor limited partial automation. Scale of deployment is a key determinant: AI-as-a-Service and AI agents spread fixed costs across users, sharply expanding economically viable tasks. At the firm level, cost-effective automation captures approximately 11% of computer-vision-exposed labor compensation; under economy-wide deployment, this share rises sharply. Since other AI systems exhibit similar scaling-law economics, our mechanisms extend beyond computer vision, reinforcing that partial automation is often the economically rational long-run outcome, not merely a transitional phase." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy (2026)
Zitatform
Liu, Cathy Yang & Rory Renzy (2026): Good Jobs or Bad Jobs? Immigrant Workers in the Gig Economy. In: International migration review, Jg. 60, H. 1, S. 114-138. DOI:10.1177/01979183241309585
Abstract
"New work arrangements enabled by online platforms, or gig work, saw substantive growth during the COVID-19 pandemic. Various estimates have suggested the wide participation of workers in the gig economy, with minority and immigrant workers well represented. The quality of work is a multi-dimensional concept that goes beyond earnings. One framework of good jobs and bad jobs centers on control over work schedule, content and duration, stability, safety, benefits and insurance, as well as career advancement opportunities. Using a newly released national survey focused on entrepreneurs and workers in the United States, we find that about 18.5 percent immigrant workers and 21.1 percent native-born workers participated in the gig economy as their primary or secondary job. In terms of job quality, immigrant gig workers work shorter hours and have significantly less fringe benefits than non-gig workers as well as U.S.-born gig workers, reflecting a double disadvantage. However, they tend to have higher entrepreneurial aspirations, suggesting the transient nature of gig arrangements and potential for career advancements. This paper provides a comprehensive analysis of the characteristics and implication of immigrants’ engagement with the gig economy and offers policy and theoretical discussions." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
The Enshittification of Work: Platform Decay and Labour Conditions in the Gig Economy (2026)
Zitatform
Maffie, Michael David & Hector Hurtado (2026): The Enshittification of Work: Platform Decay and Labour Conditions in the Gig Economy. In: BJIR, Jg. 64, H. 1, S. 5-20. DOI:10.1111/bjir.70004
Abstract
"This study investigates the mechanisms by which gig platforms degrade labor conditions over time, building on the concept of platform decay, or ‘enshittification’, initially developed in the context of social media platforms. In this article, we draw on 30 interviews with long-term gig workers in the ride-hail and grocery delivery sectors, offering insights into how these companies shift from offering attractive working conditions to exploiting labor as these services develop market power via network effects. We identify three mechanisms through which gig companies claw back value from workers over time: burden shifting (transferring operational costs to workers), feature addition and alteration (increasing the demands on workers), and market manipulation (reducing worker bargaining power). We then explore how workers respond to platform decay, finding that workers adopt three responses: effort recalibration , multi-homing and navigating the changing conditions through what we term toxic resilience . This study contributes to the gig work literature by developing a framework to explain how working conditions in the gig economy improve or degrade over time. In doing so, this article provides a framework for organizing the growing constellation of labour research on gig workers." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))
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Literaturhinweis
Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members (2026)
Zitatform
Matsuki, Takashi (2026): Improving the effects of industrial robot adoption on employment, total factor productivity, and real wages in 52 world economies and OECD members. In: Review of world economics, S. 1-32. DOI:10.1007/s10290-025-00626-z
Abstract
"This study investigates the effects of industrial robot adoption in the production process on unemployment rate, employment ratio in manufacturing, and total factor productivity (TFP) growth in 52 countries, and real wage growth in 31 and 20 OECD member countries for 2007–2019. The operating stock of robots per employee significantly impacts these variables; robot adoption lowers the unemployment rate and raises TFP and real wage growth. However, it reduces the employment ratio in manufacturing. In addition, the slight but significant positive contribution of robot adoption is observed only in the 90-percentile (top 10-percentile) of the real wage distribution. Interestingly, workers in the bottom and top tails (10- and 90-percentiles) of the wage distribution asymmetrically benefit from robotization. The industry ratio of value-added improves the labor market by reducing the unemployment rate and raising the employment ratio in manufacturing, TFP growth, and real wage growth. The information and communication technology (ICT) development also positively contributes to the employment ratio in Asia’s manufacturing, TFP growth, and real wage growth." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Nürnberger Gespräche: Deutschland 2030 - Zukunft gestalten, Chancen nutzen (2026)
Mauer, Johanna; Terzenbach, Daniel; Ries, Elisabeth; Bangerth, Julia; Schludi, Martin; Hahnenkamp, Maximilian; Gebers, Leonie; Fitzenberger, Bernd ;Zitatform
Mauer, Johanna & Martin Schludi; Daniel Terzenbach, Elisabeth Ries, Julia Bangerth, Maximilian Hahnenkamp, Leonie Gebers & Bernd Fitzenberger (sonst. bet. Pers.) (2026): Nürnberger Gespräche: Deutschland 2030 - Zukunft gestalten, Chancen nutzen. In: IAB-Forum H. 15.05.2026. DOI:10.48720/IAB.FOO.20260515.01
Abstract
"Ein Blick in die morgendliche Zeitung und die Depression scheint programmiert: Der ökonomische Abstieg Deutschlands, drohender Sozialabbau und die gefühlte Ohnmacht der deutschen Politik angesichts multipler Krisen beherrschen die Schlagzeilen. Umso erstaunlicher: Bei den traditionellen Nürnberger Gesprächen, die am 16. April 2026 im Historischen Rathaussaal stattfinden, blickten die vier geladenen Podiumsgäste durchaus mit einer Prise Zuversicht auf die Arbeitswelt im Jahr 2030. Da es in der Veranstaltung nicht zuletzt um die Job- und Zukunftschancen junger Menschen in einer sich rapide verändernden Wirtschaft ging, hatte das IAB, das die Veranstaltung gemeinsam mit der Stadt Nürnberg organisiert, erstmalig auch gezielt Vertreter*innen der jungen Generation aus Schulen und Hochschulen eingeladen. Sie wurden gebeten, die Probleme und Herausforderungen zu schildern, mit denen sie sich selbst am Arbeitsmarkt konfrontiert sehen." (Autorenreferat, IAB-Doku)
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Literaturhinweis
Gender bias in machine learning: insights from official labour statistics and textual analysis (2026)
Menis–Mastromichalakis, Orfeas ; Filandrianos, George; Stamou, Giorgos ; Parsanoglou, Dimitris ; Symeonaki, Maria ; Stamatopoulou, Glykeria ;Zitatform
Menis–Mastromichalakis, Orfeas, George Filandrianos, Maria Symeonaki, Glykeria Stamatopoulou, Dimitris Parsanoglou & Giorgos Stamou (2026): Gender bias in machine learning: insights from official labour statistics and textual analysis. In: Quality & quantity, Jg. 60, H. 1, S. 619-653. DOI:10.1007/s11135-025-02261-0
Abstract
"The interplay between technology and societal norms often reveals a troubling reality: machine learning systems not only reflect existing gender stereotypes but can also amplify and entrench them, making these biases harder to detect and address. This paper adopts an interdisciplinary approach, combining quantitative and qualitative methods with recent technological advancements, such as machine learning techniques for textual analysis and computational linguistics, to offer a new framework for understanding occupational gender bias in machine learning. The study is motivated by persistent gender inequalities in the labor market and rising concerns about gendered algorithmic bias, as outlined in the European Commission’s Gender Equality Strategy 2020–2025. Focusing on language translation technologies, the research explores how machine learning may perpetuate or amplify gender stereotypes, aiming to foster more inclusive digital systems aligned with EU strategic goals. More specifically, it investigates occupational gender segregation and its manifestations in various forms of gender bias in machine learning across English, French, and Greek. The study introduces a classification of gender biases in machine learning, providing insights into professional areas needing intervention to address gender imbalances and identifying enduring stereotypical representations in textual data. To support this, statistical analysis is conducted to explore gender variations in occupations over the past thirteen years, using official data and international classifications such as the International Standard Classification of Occupations (ISCO-08). Moreover, gendered occupational distributions are extracted from 200,920 text instances in the three languages, revealing significant discrepancies between official labour statistics and the training data." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
Artificial Intelligence and Productivity in Europe (2026)
Misch, Florian; Park, Ben; Sher, Galen; Pizzinelli, Carlo;Zitatform
Misch, Florian, Ben Park, Carlo Pizzinelli & Galen Sher (2026): Artificial Intelligence and Productivity in Europe. (CESifo working paper 12401), München, 37 S.
Abstract
"The discussion on Artificial Intelligence (AI) often centers around its impact on productivity, but macroeconomic evidence for Europe remains scarce. Using the Acemoglu (2024) approach we simulate the medium-term impact of AI adoption on total factor productivity for 31 European countries. We compile many scenarios by pooling evidence on which tasks will be automatable in the near term, using reduced-form regressions to predict AI adoption across Europe, and considering relevant regulation that restricts AI use heterogeneously across tasks, occupations and sectors. We find that the medium-term productivity gains for Europe as a whole are likely to be modest, at around 1 percent cumulatively over five years. While economically still moderate, these gains are still larger than estimates by Acemoglu (2024) for the US. They vary widely across scenarios and countries and are substantially larger in countries with higher incomes. Furthermore, we show that national and EU regulations around occupation-level requirements, AI safety, and data privacy combined could reduce Europe's productivity gains by over 30 percent if AI exposure were 50 percent lower in tasks, occupations and sectors affected by regulation." (Author's abstract, IAB-Doku) ((en))
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Literaturhinweis
KI in Betrieben: Mehr Ausbildung – aber Weiterbildung zunehmend für anspruchsvollere Tätigkeiten (2026)
Zitatform
Muehlemann, Samuel (2026): KI in Betrieben. Mehr Ausbildung – aber Weiterbildung zunehmend für anspruchsvollere Tätigkeiten. In: Ifo-Schnelldienst, Jg. 79, H. 03, S. 09-13.
Abstract
"Auf Basis des BIBB-Betriebspanels werden die Folgen der Einführung von Künstlicher Intelligenz für die betriebliche Aus- und Weiterbildung in Deutschland analysiert. Die Ergebnisse deuten darauf hin, dass KI-einführende Ausbildungsbetriebe im Durchschnitt rund 14% mehr neue Auszubildende einstellen. Das spricht für verstärkte Investitionen in den internen Kompetenzaufbau im Zuge des technologischen Wandels. Zugleich verschiebt sich die betriebliche Weiterbildung zugunsten hochqualifizierter Tätigkeiten, während Beschäftigte in Fachkraft- und einfachen Tätigkeiten seltener teilnehmen. Daraus ergibt sich das Risiko einer kumulativen Benachteiligung Geringqualifizierter. Es werden drei wirtschaftspolitische Handlungsfelder abgeleitet: die bessere Integration Jugendlicher mit geringen schulischen Qualifikationen in die duale Ausbildung, eine zielgerichtete Weiterbildungsförderung für Geringqualifizierte sowie schnellere Aktualisierungszyklen für Ausbildungsordnungen und Rahmenlehrpläne." (Autorenreferat, IAB-Doku)
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- Qualifikationsanforderungen und Berufe
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