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
-
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))
-
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))
-
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))
-
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))
-
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))
-
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
-
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))
-
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))
-
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))
-
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))
-
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))
-
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
-
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))
-
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)
-
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))
-
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))
-
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
-
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))
-
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))
-
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))
-
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))
-
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)
-
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))
-
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
„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)
-
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)
-
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
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))
-
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))
-
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))
-
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))
-
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))
-
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)
-
Literaturhinweis
Machine learning for labor market matching (2026)
Zitatform
Mühlbauer, Sabrina & Enzo Weber (2026): Machine learning for labor market matching. In: Machine learning with applications, Jg. 23, 2026-02-03. DOI:10.1016/j.mlwa.2026.100861
Abstract
"This paper develops a large-scale machine learning framework to improve labor market matching using rich administrative data. Matching is defined as a job seeker entering employment in a specific occupational field. We exploit comprehensive employment biographies from Germany, covering individual characteristics and job-related information, to estimate employment probabilities across occupations and generate personalized job recommendations. The contribution lies in demonstrating why machine learning methods are particularly well suited for administrative labor market data and outperform traditional statistical approaches. We compare logit, ordinary least squares (OLS), k-nearest neighbors, and random forest (RF). RF consistently achieves the highest predictive performance. Its advantage is rooted in key methodological properties: RF builds an ensemble of decision trees trained on bootstrap samples, introduces random feature selection at each split, and aggregates predictions through majority voting. This enables RF to capture nonlinear relationships and complex interactions, remain robust in high-dimensional settings, and reduce overfitting — features that are particularly relevant for heterogeneous and imbalanced administrative data. Compared to conventional models, RF better exploits the full informational content of employment histories, especially when estimating on all employment spells rather than restricting the sample to unemployment-to-employment transitions. The sample comprises approximately 55 million spells, representing about 6 percent of the German workforce from 2012 to 2018. Our results suggest that ML-based matching, relative to standard statistical approaches, could hypothetically reduce the unemployment rate by up to 0.3 percentage points, highlighting the practical relevance of RF-based decision support for labor market policy." (Author's abstract, IAB-Doku, © Elsevier) ((en))
-
Literaturhinweis
How local labour market skill relatedness and size moderate the impacts of automation (2026)
Zitatform
Njekwa Ryberg, Peter (2026): How local labour market skill relatedness and size moderate the impacts of automation. In: Regional Studies, Jg. 60, H. 1. DOI:10.1080/00343404.2025.2598031
Abstract
"This paper examines how local labour market skill relatedness and size moderate the impacts of automation on occupations across Swedish local labour markets. Using administrative data and a spatially explicit risk of automation measure that accounts for regional differences in occupational task contents, it finds a negative association between automation and employment growth and wage income growth for non-metropolitan occupations between 2011 and 2021. Skill relatedness and labour market size mitigate these negative relationships. In contrast, no negative associations are found for metropolitan occupations. Due to their higher shares of non-automatable tasks, they are more resilient to adverse automation effects." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Human-centred digital transitions and skill mismatches in European workplaces (2026)
Zitatform
Pouliakas, Konstantinos & Giulia Santangelo (2026): Human-centred digital transitions and skill mismatches in European workplaces. (CEDEFOP working paper series / European Centre for the Development of Vocational Training 2026,01), Luxembourg, 163 S. DOI:10.2801/9894877
Abstract
"New digital and artificial intelligence technologies are fast reshaping skill requirements in the EU labour market, fostering skill mismatches. There are marked concerns about the potentially adverse consequences of automation and AI on employment, as well as the lagging competitiveness of EU economies as individuals’ upskilling or reskilling is failing to adapt. To deepen understanding of how digitalisation is affecting the nature of work and skill mismatches in EU labour markets, Cedefop carried out the second wave of the European skills and jobs survey in 2021. In this special edition of Cedefop’s working paper series, ten original, short contributions have been drafted in which researchers explore in depth, for the first time, the ESJS2 microdata. The publication presents a wealth of focused and robust empirical analyses, covering a wide range of different issues on how the digital transition is affecting jobs, skills and training in Europe." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Mehr Arbeit, weniger Jobs? Konsequenzen der KI-Technologieeinführung: Teil des Zeitgesprächs "Arbeitszeit im Wandel - Wie sich Wohlstand trotz sinkenden Arbeitskräfteangebots sichern lässt" (2026)
Zitatform
Pusch, Toralf, Muhamed Kudic & Akua Franziska Agyepong (2026): Mehr Arbeit, weniger Jobs? Konsequenzen der KI-Technologieeinführung. Teil des Zeitgesprächs "Arbeitszeit im Wandel - Wie sich Wohlstand trotz sinkenden Arbeitskräfteangebots sichern lässt". In: Wirtschaftsdienst, Jg. 106, H. 4, S. 296-300. DOI:10.2478/wd-2026-0072
Abstract
"Steigt durch die zunehmende Einführung von Künstlicher Intelligenz (KI) die Arbeitsbelastung? Und sind Arbeitsplätze bedroht? Daten der WSI-Betriebsrätebefragung zeigen, dass sich KI in ihrer Wirkung – zumindest in der frühen Einführungsphase – von anderen digitalen Technologien zu unterscheiden scheint. Statt einer bei anderen Technologien häufiger auftretenden Arbeitsverdichtung berichteten viele Betriebsräte eher von Arbeitsentlastung, und nach einem Beobachtungszeitraum von zwei Jahren zeigte sich per Saldo ein leichter Stellenaufbau." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
KI in der Pflege zwischen Anspruch und Realität: Empfehlungen für die Praxis aus dem Projekt ETAP (2026)
Sarwary, Hares; Wielga, Jenny; Enste, Peter;Zitatform
Sarwary, Hares, Jenny Wielga & Peter Enste (2026): KI in der Pflege zwischen Anspruch und Realität: Empfehlungen für die Praxis aus dem Projekt ETAP. (Forschung aktuell / Institut Arbeit und Technik 2026-03), Gelsenkirchen, 11 S. DOI:10.53190/fa/202603
Abstract
"Die Implementierung von digitalen Innovationen ist in der stationären Altenpflege mit vielen Herausforderungen verbunden, für die sich unterschiedliche Lösungsoptionen aufzeigen lassen. Eine stabile IT-Infrastruktur und Interoperabilität sind zentral, um einen nachhaltigen Nutzen zu schaffen und Insellösungen zu vermeiden. Kontinuierliche und praxisnahe Schulungsangebote für Pflege- und IT-Personal müssen Teil einer langfristig angelegten Digitalisierungsstrategie in Einrichtungen werden. Transparente Kommunikation innerhalb der Einrichtung ist ein entscheidender Faktor, um Erwartungen zu steuern und Vertrauen aufzubauen." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
"Die KI ist auf dem Arbeitsmarkt noch gar nicht wirklich angekommen" (2026)
Zitatform
Schmelmer, Julian; Britta [interviewte Person] Matthes (sonst. bet. Pers.) (2026): "Die KI ist auf dem Arbeitsmarkt noch gar nicht wirklich angekommen". In: Zeit-Campus H. 2.
Abstract
"Nach der Uni konkurrieren Absolvent:innen auch mit KI-Modellen um Jobs. Eine Arbeitsmarktforscherin erklärt, wie sie sich behaupten können" (Autorenreferat, IAB-Doku, © ZEIT-Campus)
Weiterführende Informationen
Online-Zugang möglicherweise kostenpflichtig -
Literaturhinweis
Chancen künstlicher Intelligenz für die Deckung des Fachkräftebedarfs im Mittelstand (2026)
Schneider, Sebastian; Becker, Felix; Löher, Jonas; Brink, Siegrun; Icks, Annette;Zitatform
Schneider, Sebastian, Siegrun Brink, Jonas Löher, Annette Icks & Felix Becker (2026): Chancen künstlicher Intelligenz für die Deckung des Fachkräftebedarfs im Mittelstand. (IfM-Materialien / Institut für Mittelstandsforschung Bonn 312), Bonn, 32 S.
Abstract
"Diese Studie untersucht, welchen Beitrag der Einsatz von KI zur Deckung des Fachkräftebe darfs im Mittelstand leisten kann. Anhand exemplarischer Fallbeispiele werden Treiber und Hemmnisse sowohl für den substitutiven als auch den komplementären KI-Einsatz identifiziert. Es zeigt sich: Das Potenzial von KI zur Deckung des Fachkräftebedarfs hängt von ihrer Ein satzart ab. Die Unternehmen nutzen KI derzeit vor allem substitutiv, indem einzelne Tätigkeiten übernommen und Beschäftigte entlastet werden, ohne Arbeitsplätze abzubauen. Auf diese Weise kann der KI-Einsatz Stellenbesetzungsprobleme mindern und indirekt zur Verringerung des Fachkräftemangels beitragen. Perspektivisch ist ein zunehmend komplementärer KI-Ein satz zu erwarten, der Tätigkeitsprofile sowie Qualifikationsanforderungen nachhaltig verän dert. Das kann neue Stellenbesetzungsprobleme und potenziell einen zunehmenden Fach kräftemangel nach sich ziehen." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
Where Have All the (Boomer) Routine Workers Gone? (2026)
Scotese, Carol A.;Zitatform
Scotese, Carol A. (2026): Where Have All the (Boomer) Routine Workers Gone? In: The B.E. Journal of Economic Analysis and Policy, S. 1-44. DOI:10.1515/bejeap-2024-0396
Abstract
"This paper examines the employment outcomes of a cohort of non-college educated individuals who exit employment from occupations most exposed to automation risk. The analysis employs a novel set of granular task measures estimated from the detailed job attributes in the Occupational Information Network (O*NET). The granularity enables a rich characterization of non-routine work and task mobility choices for those without a college degree. The data yield multiple types of interpersonal, decision-making, cognitive, and technical tasks. Employing the granular tasks to analyze the employment outcomes for non-college educated workers who transition out of routine work, this study finds (1) the granular measures detect abstract tasks performed intensively in a range of skill contexts, (2) when exiting routine intensive work, non-college propensity to enter abstract work is just under 65 %, and (3) approximately one-quarter of those entries are into tasks yielding average wage gains for those making that transition." (Author's abstract, IAB-Doku, © De Gruyter) ((en))
-
Literaturhinweis
Envisioning the Future of Work: From Ideas to Reforms (2026)
Zitatform
Spencer, David A. (2026): Envisioning the Future of Work: From Ideas to Reforms. In: BJIR, S. 1-11. DOI:10.1111/bjir.70035
Abstract
"Two different theoretical perspectives concerning technology and the future of work are examined. One is linked to mainstream economics, whereas the other is associated with critical (‘post-work ’) discourse. Ideas about work—its nature and impacts on well-being—matter in both perspectives. Indeed, they shape visions of a ‘better’ or ‘ideal’ future. They also influence policy responses to new technology. A critique is presented of the ways that work and its possible futures are understood. This critique is used to develop a different set of ideas about how technology might be harnessed to reduce the burden and raise the quality of work. The ability of ideas to effect reforms in and of work—ideas that have currency now and possible radical alternatives—is also assessed." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
AI Skills Improve Job Prospects: Causal Evidence from a Hiring Experiment (2026)
Zitatform
Stephany, Fabian, Ole Teutloff & Angelo Leone (2026): AI Skills Improve Job Prospects: Causal Evidence from a Hiring Experiment. (arXiv papers), 46 S. DOI:10.48550/arXiv.2601.13286
Abstract
"The growing adoption of artificial intelligence (AI) technologies has heightened interest in the labour market value of AI-related skills, yet causal evidence on their role in hiring decisions remains scarce. This study examines whether AI skills serve as a positive hiring signal and whether they can offset conventional disadvantages such as older age or lower formal education. We conduct an experimental survey with 1,700 recruiters from the United Kingdom and the United States. Using a paired conjoint design, recruiters evaluated hypothetical candidates represented by synthetically designed résumés. Across three occupations – graphic designer, officeassistant, and software engineer –, AI skills significantly increase interview invitation probabilities by approximately 8 to 15 percentage points. AI skills also partially or fully offset disadvantages related to age and lower education, with effects strongest for office assistants, where formal AI certification plays an additional compensatory role. Effects are weaker for graphic designers, consistent with more skeptical recruiter attitudes toward AI in creative work. Finally, recruiters’ own background and AI usage significantly moderate these effects. Overall, the findings demonstrate that AI skills function as a powerful hiring signal and can mitigate traditional labour market disadvantages, with implications for workers’ skill acquisition strategies and firms’ recruitment practices." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Firm Data on AI (2026)
Yotzov, Ivan; Wang, Ben Zhe ; Davis, Steven J. ; Thwaites, Gregory; Foster, Kevin M.; Bunn, Philip; Jalca, Aaron; Mizen, Paul; Barrero, Jose Maria; Meyer, Brent H.; Smietanka, Pawel; Bloom, Nicholas ; Navarrete, Michael A.;Zitatform
Yotzov, Ivan, Jose Maria Barrero, Nicholas Bloom, Philip Bunn, Steven J. Davis, Kevin M. Foster, Aaron Jalca, Brent H. Meyer, Paul Mizen, Michael A. Navarrete, Pawel Smietanka, Gregory Thwaites & Ben Zhe Wang (2026): Firm Data on AI. (NBER working paper / National Bureau of Economic Research 34836), Cambridge, Mass, 21 S., App.
Abstract
"We present the first representative international data on firm-level AI use. We survey almost 6000 CFOs, CEOs and executives from stratified firm samples across the US, UK, Germany and Australia. We find four key facts. First, around 70% of firms actively use AI, particularly younger, more productive firms. Second, while over two thirds of top executives regularly use AI, their average use is only 1.5 hours a week, with one quarter reporting no AI use. Third, firms report little impact of AI over the last 3 years, with over 80% of firms reporting no impact on either employment or productivity. Fourth, firms predict sizable impacts over the next 3 years, forecasting AI will boost productivity by 1.4%, increase output by 0.8% and cut employment by 0.7%. We also survey individual employees who predict a 0.5% increase in employment in the next 3 years as a result of AI. This contrast implies a sizable gap in expectations, with senior executives predicting reductions in employment from AI and employees predicting net job creation." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Changing Job Tasks as Risk or Chance for Employees’ Perceived Job Quality? A Longitudinal Analysis (2026)
Zitatform
Zeyer-Gliozzo, Birgit, Carolin Kunz, Jakob Schwerter & Martina Brandt (2026): Changing Job Tasks as Risk or Chance for Employees’ Perceived Job Quality? A Longitudinal Analysis. In: Kölner Zeitschrift für Soziologie und Sozialpsychologie, Jg. 78, H. 1, S. 61-86. DOI:10.1007/s11577-025-01043-8
Abstract
"In den letzten Jahrzehnten haben sich Arbeitsaufgaben erheblich verändert, was in erster Linie auf den technologischen Wandel zurückzuführen ist. Einige Tätigkeiten können von Maschinen übernommen werden, während andere an Bedeutung gewinnen. Dies kann sich auf zweierlei Weise auf die Beschäftigten auswirken: Einerseits können veränderte Tätigkeiten die wahrgenommene Arbeitsqualität verringern, beispielsweise durch kognitive Überlastung. Andererseits können Tätigkeitsveränderungen eine Chance sein, beispielsweise durch die Automatisierung unerwünschter Tätigkeiten wie schwerer körperlicher Arbeit. Diese Studie analysiert anhand von Daten des Nationalen Bildungspanels, wie sich Aufgabenänderungen auf individueller Ebene auf die Arbeitszufriedenheit als Maß für die wahrgenommene Arbeitsqualität auswirken. Fixed-Effects-Modelle zeigen, dass weniger manuelle sowie mehr analytische und autonome Tätigkeiten die Arbeitszufriedenheit signifikant verbessern, was auf positive Auswirkungen vergangener Aufgabenänderungen hindeutet. Allerdings beobachten wir auch altersbedingte Unterschiede, wobei ältere Beschäftigte eine geringere Zufriedenheit angeben, wenn sie weniger Routineaufgaben ausführen. Diese Ergebnisse liefern wertvolle Erkenntnisse über die Auswirkungen sich verändernder Arbeitsaufgaben und zeigen Bereiche auf, in denen weitere Forschung und politische Maßnahmen erforderlich sind." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education (2026)
Zitatform
(2026): OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education. (OECD digital education outlook 2026), Paris, 244 S. DOI:10.1787/062a7394-en
Abstract
"Generative AI (GenAI) is reshaping the educational landscape, beyond teaching and learning. Unlike earlier waves of education technology, much of GenAI is freely accessible and largely used beyond institutional control due to its intuitiveness and versatility. The OECD Digital Education Outlook 2026 analyses emerging research that suggests GenAI can support learning when guided by clear teaching principles. However, if designed or used without pedagogical guidance, outsourcing tasks to GenAI simply enhances performance with no real learning gains. The Outlook highlights the benefits of GenAI as a tutor, partner and assistant, and synthesises experts’ evidence and insights on the design criteria that make it work for education." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
New Technology, Older Workers: How Workplace Technology is Associated with Indicators of Job Retention (2025)
Zitatform
Abrams, Leah, Daniel Schneider & Kristen Harknett (2025): New Technology, Older Workers: How Workplace Technology is Associated with Indicators of Job Retention. In: Journal of Aging & Social Policy, S. 1-17. DOI:10.1080/08959420.2025.2523122
Abstract
"Middle-aged and older adults who are employed in precarious, high-strain jobs may face challenges to continued work, risking economic insecurity and poor wellbeing in retirement. Technology in the workplace, an under-studied aspect of work environments, could accommodate aging workers or could add stress to their jobs. This study examines how technology in sales and surveillance at work are related to job satisfaction and planned job exits among approximately 6,000 workers aged 50–69 employed in the low-wage service sector (e.g. retail, pharmacy, grocery, hardware, fast food, casual dining, delivery, and hotel). On-the-job surveillance was related to lower job satisfaction and higher reports of looking for a new job, especially when combined with sanctioning for slow speed of work. However, rewards for speed, and to a lesser extent the use of leaderboards, were associated with higher job satisfaction, demonstrating the potential of technology to enhance the work experience for older employees. The use of sales technologies was not associated with job satisfaction or intentions to look for a new job. These results provide a uniquely detailed portrait of prevailing labor market conditions for aging workers in the service sector and demonstrate how certain kinds of technology matter for older workers ’ employment." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Artificial intelligence in work design: unlocking inclusion and overcoming barriers (2025)
Adolph, Lars; Kirchhoff, Britta Marleen; Hamideh Kerdar, Sara;Zitatform
Adolph, Lars, Britta Marleen Kirchhoff & Sara Hamideh Kerdar (2025): Artificial intelligence in work design: unlocking inclusion and overcoming barriers. In: Zeitschrift für Arbeitswissenschaft, Jg. 79, H. 2, S. 197-205. DOI:10.1007/s41449-025-00467-4
Abstract
"This article examines the protection goal of “exclusion prevention” and the design requirement of “design for inclusion and accessibility”, which are part of the initial considerations for a roadmap on artificial intelligence (AI) in occupational science research. The proposed roadmap systematically breaks down framework conditions, design requirements, instrumental goals and protection goals. The concept presented provides guidance for future research and can also serve as a basis for scientific policy advice. The in-depth examination of inclusion and AI takes place against the background that, on the one hand these aspects are underrepresented in occupational science research, and technological development can lead to a surge of change, particularly in the area of inclusive work design, on the other. Two expert workshops were held to answer the research question of what opportunities and risks AI technologies offer for the professional integration of people with disabilities, and what research and development needs to exist. The results show that some useful systems already exist, but that they can also have negative effects and that there is a need for further development. Practical relevance: The presented aspects of the roadmap on artificial intelligence (AI) from the perspective of occupational science research is relevant for both companies and policy actors who want to gain a systematic overview of AI in the world of work. A particular focus is on the issue of inclusive work design. In an expert workshop, it became clear that an optimistic view of the use of artificial intelligence for inclusive work design prevails both in companies or workshops employing people with disabilities and in the field of consulting. At the same time, however, development needs and potential risks were identified. The results provide an overview of the current potential uses of AI and are also of interest to companies that do not yet employ people with disabilities but are planning to do so." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Genius on Demand: The Value of Transformative Artificial Intelligence (2025)
Zitatform
Agrawal, Ajay K., Joshua S. Gans & Avi Goldfarb (2025): Genius on Demand: The Value of Transformative Artificial Intelligence. (NBER working paper / National Bureau of Economic Research 34316), Cambridge, Mass, 20 S.
Abstract
"This paper examines how the emergence of transformative AI systems providing ``genius on demand" would affect knowledge worker allocation and labour market outcomes. We develop a simple model distinguishing between routine knowledge workers, who can only apply existing knowledge with some uncertainty, and genius workers, who create new knowledge at a cost increasing with distance from a known point. When genius capacity is scarce, we find it should be allocated primarily to questions at domain boundaries rather than at midpoints between known answers. The introduction of AI geniuses fundamentally transforms this allocation. In the short run, human geniuses specialise in questions that are furthest from existing knowledge, where their comparative advantage over AI is greatest. In the long run, routine workers may be completely displaced if AI efficiency approaches human genius efficiency." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Artificial Intelligence in the European Labour Markets (2025)
Alasalmi, Juho;Zitatform
Alasalmi, Juho (2025): Artificial Intelligence in the European Labour Markets. (DIFIS-Impuls 2026,1), Duisburg ; Bremen, 4 S.
Abstract
"This review surveys the emerging evidence regarding the effects of artificial intelligence technologies in the labour market and on labour market inequality through the lens of the theoretical framework of task-based production and the literature in the field of economics on technological change. The evidence analysed concerns the time period after the early 2010s, with an emphasis on the effects of generative AI after 2022. The focus is on research studying European labour markets. After outlining the context of routine- and skill-biased technological change and job polarisation, the existing evidence regarding AI adoption in production and its effects on productivity and employment is reviewed. The review concludes with a discussion on labour market policy that mediates the effects of AI on the distribution of productivity gains and the direction of technological change and a consideration of the effect of technological change on attitudes toward labour market policy and democracy itself." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
AI and women’s employment in Europe - Publications Office of the EU (2025)
Zitatform
Albanesi, Stefania, António Dias da Silva, Juan F. Jimeno, Ana Lamo & Alena Wabitsch (2025): AI and women’s employment in Europe - Publications Office of the EU. (Working paper series / European Central Bank 3077), Frankfurt am Main, 15 S. DOI:10.2866/9616450
Abstract
"We examine the link between the diffusion of artificial intelligence (AI) enabled technologies and changes in the female employment share in 16 European countries over the period 2011-2019. Using data for occupations at the 3-digit level, we find that on average female employment shares increased in occupations more exposed to AI. Countries with high initial female labor force participation and higher initial female relative education show a stronger positive association. While there exists heterogeneity across countries, almost all show a positive relation between changes in female employment shares within occupations and exposure to AI-enabled automation." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Zentrale Befunde zu aktuellen Arbeitsmarktthemen 2025 (2025)
Anger, Silke ; Wolter, Stefanie ; Lietzmann, Torsten ; Lehmer, Florian ; Jahn, Elke; Leber, Ute; Wolff, Joachim; Artmann, Elisabeth ; Wenzig, Claudia; Lang, Julia ; Wanger, Susanne ; Kuhn, Sarah; Vom Berge, Philipp ; Kubis, Alexander; Walwei, Ulrich ; Trenkle, Simon ; Braun, Wolfgang; Brücker, Herbert ; Stops, Michael ; Kosyakova, Yuliya ; Stepanok, Ignat ; Janssen, Simon; Roth, Duncan ; Janser, Markus ; Rauch, Angela ; Jahn, Elke J. ; Popp, Martin ; Hohmeyer, Katrin ; Müller, Dana ; Hohendanner, Christian ; Mense, Andreas ; Hiesinger, Karolin ; Zika, Gerd ; Heß, Pascal ; Weber, Enzo ; Hellwagner, Timon ; Bruckmeier, Kerstin ; Haas, Anette; Seibert, Holger; Gürtzgen, Nicole ; Ramos Lobato, Philipp; Gläser, Nina; Müller, Christoph ; Gherbaoui, Samia; Arntz, Melanie ; Gellermann, Jan; Stephan, Gesine ; Fitzenberger, Bernd ; Oberfichtner, Michael ; Dietz, Martin; Bächmann, Ann-Christin ; Dauth, Wolfgang ; Matthes, Britta ; Collischon, Matthias ; Reims, Nancy ; Christoph, Bernhard ;Zitatform
Anger, Silke, Melanie Arntz, Elisabeth Artmann, Ann-Christin Bächmann, Wolfgang Braun, Kerstin Bruckmeier, Herbert Brücker, Bernhard Christoph, Matthias Collischon, Wolfgang Dauth, Martin Dietz, Bernd Fitzenberger, Jan Gellermann, Samia Gherbaoui, Nina Gläser, Nicole Gürtzgen, Anette Haas, Timon Hellwagner, Pascal Heß, Karolin Hiesinger, Christian Hohendanner, Katrin Hohmeyer, Elke J. Jahn, Markus Janser, Simon Janssen, Stefanie Wolter, Torsten Lietzmann, Florian Lehmer, Ute Leber, Joachim Wolff, Claudia Wenzig, Julia Lang, Susanne Wanger, Sarah Kuhn, Philipp Vom Berge, Alexander Kubis, Ulrich Walwei, Simon Trenkle, Michael Stops, Yuliya Kosyakova, Ignat Stepanok, Duncan Roth, Angela Rauch, Martin Popp, Dana Müller, Andreas Mense, Gerd Zika, Enzo Weber, Holger Seibert, Philipp Ramos Lobato, Christoph Müller, Gesine Stephan, Michael Oberfichtner, Britta Matthes & Nancy Reims (2025): Zentrale Befunde zu aktuellen Arbeitsmarktthemen 2025. Nürnberg, 21 S. DOI:10.48720/IAB.GP.2505.1
Abstract
"Digitalisierung und Künstliche Intelligenz, Dekarbonisierung und demografischer Wandel werden den Arbeitsmarkt in den kommenden Jahren erheblich verändern. Gleichzeitig wird eine Deindustrialisierung Deutschlands befürchtet. Handlungsbedarf besteht beispielsweise bei der Sicherung des Arbeitskräftebedarfs – und damit verbunden bei den Themen Aus- und Weiterbildung –, bei der Reduzierung der Arbeitslosigkeit und insbesondere der Langzeitarbeitslosigkeit sowie bei der sozialen Absicherung von Solo-Selbständigen Zu all diesen und zahlreichen weiteren wichtigen Themen fasst die IAB-Broschüre „Zentrale Befunde zu aktuellen Arbeitsmarkt-Themen 2025“ die zentralen wissenschaftlichen Befunde kompakt zusammen. Sie bietet zudem Handlungsempfehlungen für die Arbeitsmarktpolitik, die aus den wissenschaftlichen Befunden abgeleitet wurden." (Autorenreferat, IAB-Doku)
Beteiligte aus dem IAB
Anger, Silke ; Wolter, Stefanie ; Lietzmann, Torsten ; Lehmer, Florian ; Leber, Ute; Wolff, Joachim; Artmann, Elisabeth ; Wenzig, Claudia; Lang, Julia ; Wanger, Susanne ; Kuhn, Sarah; Vom Berge, Philipp ; Kubis, Alexander; Walwei, Ulrich ; Trenkle, Simon ; Braun, Wolfgang; Brücker, Herbert ; Stops, Michael ; Kosyakova, Yuliya ; Stepanok, Ignat ; Janssen, Simon; Roth, Duncan ; Janser, Markus ; Rauch, Angela ; Jahn, Elke J. ; Popp, Martin ; Hohmeyer, Katrin ; Müller, Dana ; Hohendanner, Christian ; Mense, Andreas ; Hiesinger, Karolin ; Zika, Gerd ; Heß, Pascal ; Weber, Enzo ; Hellwagner, Timon ; Bruckmeier, Kerstin ; Haas, Anette; Seibert, Holger; Gürtzgen, Nicole ; Ramos Lobato, Philipp; Gläser, Nina; Müller, Christoph ; Arntz, Melanie ; Gellermann, Jan; Stephan, Gesine ; Fitzenberger, Bernd ; Oberfichtner, Michael ; Dietz, Martin; Bächmann, Ann-Christin ; Dauth, Wolfgang ; Matthes, Britta ; Collischon, Matthias ; Reims, Nancy ; Christoph, Bernhard ; -
Literaturhinweis
Computers as Stepping Stones? Technological Change and Equality of Labor Market Opportunities (2025)
Zitatform
Arntz, Melanie, Cäcilia Lipowski, Guido Neidhöfer & Ulrich Zierahn-Weilage (2025): Computers as Stepping Stones? Technological Change and Equality of Labor Market Opportunities. In: Journal of labor economics, Jg. 43, H. 2, S. 503-543., 2023-08-18. DOI:10.1086/727490
Abstract
"This paper analyzes whether technological change improves equality of labor market opportunities by increasing the returns to skills relative to the returns to parental background. We find that in Germany during the 1990s, the introduction of computer technologies improved the access to technology-adopting occupations for workers with low-educated parents, and reduced their wage penalty within these occupations. We also show that this significantly contributed to a decline in the overall wage penalty experienced by workers from disadvantaged parental back-grounds over this time period. Competing mechanisms, such as skill-specific labor supply shocks and skill-upgrading, do not explain these findings." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Abgehängt? Frauen nutzen KI beruflich viel seltener als Männer (2025)
Zitatform
Arntz, Melanie, Eduard Brüll, Carola Burkert & Britta Matthes (2025): Abgehängt? Frauen nutzen KI beruflich viel seltener als Männer. In: IAB-Forum – Grafik aktuell H. 20.05.2025. DOI:10.48720/IAB.FOO.GA.20250520.01
Abstract
"Künstliche Intelligenz (KI) wird weitreichende Auswirkungen auf den Arbeitsmarkt haben. Bereits heute werden KI-Kompetenzen auf dem Arbeitsmarkt zunehmend nachgefragt. Ergebnisse unserer aktuellen Beschäftigtenbefragung zu „Digitalisierung und Wandel der Arbeit (DiWaBe)“ zeigen, dass Frauen KI bei ihrer Arbeit deutlich seltener nutzen als Männer, was die bestehenden Geschlechterungleichheiten eher verfestigen als nivellieren dürfte." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Hier finden Sie sämtliche aktuellen Grafiken -
Literaturhinweis
Digitalisierung und Wandel der Beschäftigung (DiWaBe 2.0): Eine Datengrundlage für die Erforschung von Künstlicher Intelligenz und anderer Technologien in der Arbeitswelt (2025)
Arntz, Melanie ; Baum, Myriam; Brüll, Eduard ; Wischniewski, Sascha ; Matthes, Britta ; Hartwig, Matthias; Meyer, Sophie-Charlotte ; Dorau, Ralf; Schlenker, Oliver ; Lehmer, Florian ; Tisch, Anita ;Zitatform
Arntz, Melanie, Myriam Baum, Eduard Brüll, Ralf Dorau, Matthias Hartwig, Florian Lehmer, Britta Matthes, Sophie-Charlotte Meyer, Oliver Schlenker, Anita Tisch & Sascha Wischniewski (2025): Digitalisierung und Wandel der Beschäftigung (DiWaBe 2.0): Eine Datengrundlage für die Erforschung von Künstlicher Intelligenz und anderer Technologien in der Arbeitswelt. (baua: Bericht), Dortmund, 48 S. DOI:10.21934/baua:bericht20250225
Abstract
"In Deutschland nutzt bereits mehr als die Hälfte der Beschäftigten Künstliche Intelligenz (KI) am Arbeitsplatz - überwiegend jedoch informell. Dies deutet darauf hin, dass viele Beschäftigte KI als hilfreiche Unterstützung wahrnehmen, zugleich aber die formelle Einführung seitens der Betriebe den Erwartungen der Beschäftigten hinterherhinkt. Der vorliegende Bericht präsentiert die Ergebnisse der DiWaBe 2.0-Befragung, einer repräsentativen Querschnittserhebung von rund 9.800 sozialversicherungspflichtig Beschäftigten in Deutschland, die im Jahr 2024 durchgeführt wurde. Ziel der Befragung ist es, eine Datengrundlage zu schaffen, um die Auswirkungen des technologischen Wandels - und insbesondere von KI - auf die Arbeitswelt abzuschätzen. Im Fokus stehen dabei vor allem Veränderungen von Tätigkeiten und Anforderungen am Arbeitsplatz, Arbeitsbedingungen und -organisation, Weiterbildungsaktivitäten sowie die Gesundheit der Beschäftigten. Die Ergebnisse zeigen, dass die Nutzung von KI stark von individuellen und beruflichen Faktoren wie Berufssegment, Bildung, Alter und Geschlecht abhängt. So nutzt nur knapp ein Drittel der Beschäftigten ohne Bildungsabschluss KI, während dieser Anteil bei Beschäftigten mit Hochschul-, Meister-oder Technikerabschluss fast 80 % beträgt. Erste multivariate Analysen zeigen, dass Beschäftigte, die ihre KI-Nutzung in den letzten fünf Jahren intensiviert haben, von komplexeren Tätigkeitsanforderungen berichten, insbesondere in den Bereichen Schreiben, Programmierung und Mathematik. Zudem ist eine intensivierte KI-Nutzung mit einer höheren Arbeitsautonomie, aber auch mit einer höheren Arbeitsintensität verbunden. Es zeigt sich jedoch kein statistisch signifikanter Zusammenhang zwischen der Nutzung von KI und der Gesundheit der Beschäftigten. Zudem unterscheiden sich Beschäftigte mit KI-Nutzung nicht von Nichtnutzenden hinsichtlich ihrer Teilnahme an Weiterbildung." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
Low Barriers, High Stakes: Formal and Informal Diffusion of AI in the Workplace (2025)
Arntz, Melanie ; Wischniewski, Sascha ; Dorau, Ralf; Hartwig, Matthias; Tisch, Anita ; Schlenker, Oliver ; Meyer, Sophie-Charlotte ; Brüll, Eduard ; Baum, Myriam; Matthes, Britta ;Zitatform
Arntz, Melanie, Myriam Baum, Eduard Brüll, Ralf Dorau, Matthias Hartwig, Britta Matthes, Sophie-Charlotte Meyer, Oliver Schlenker, Anita Tisch & Sascha Wischniewski (2025): Low Barriers, High Stakes: Formal and Informal Diffusion of AI in the Workplace. (Ifo working papers 422), München, 28 S.
Abstract
"Artificial intelligence (AI) is diffusing rapidly in the workplace, yet aggregate productivity gains remain limited. This paper examines the dual diffusion of AI – through both formal, employer-led and informal, employee-initiated adoption – as potential explanation. Using a representative survey of nearly 10,000 employees in Germany, we document a high extensive but low intensive margin of usage: while 64 percent use AI tools, only 20 percent use them frequently. This diffusion is strongly skill-biased and depends less on establishment and regional characteristics. While formality is associated with more frequent usage, training, AI-based supervision, and higher perceived productivity gains, it does not broaden access. These patterns suggest that widespread informal usage can coexist with limited productivity effects when complementary investments and organizational integration lag behind." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
The Impact of Aging and AI on Japan's Labor Market: Challenges and Opportunities (2025)
Asao, Kohei; Seitani, Haruki; Stepanyan, Ara; Xu, TengTeng;Zitatform
Asao, Kohei, Haruki Seitani, Ara Stepanyan & TengTeng Xu (2025): The Impact of Aging and AI on Japan's Labor Market: Challenges and Opportunities. (IMF working papers / International Monetary Fund 2025,184), Washington, DC, 17 S.
Abstract
"This paper explores the complex roles of demographic changes and technological innovation in shaping Japan's labor market. We use regression analysis to assess the impact of population aging on labor productivity and shortages. Our findings indicate that the aging workforce contributes to labor shortages and potentially weighs on labor productivity. We also investigate occupational level data to identify the complementarity and substitutability of AI in occupational tasks as well as skill transferability. Our research reveals that Japanese workers face lower exposure to AI compared to their counterparts in other advanced economies, thereby constraining AI's potential to mitigate labor shortages. Furthermore, the disparities in skill requirements across occupations with different AI exposures highlight the importance of facilitating labor mobility from displaced jobs to those in demand." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Notes on a World with Generative AI (2025)
Askitas, Nikolaos;Zitatform
Askitas, Nikolaos (2025): Notes on a World with Generative AI. (CESifo working paper 12070), München, 27 S.
Abstract
"Generative AI (GenAI) and Large Language Models (LLMs) are moving into domains once seen as uniquely human—reasoning, synthesis, abstraction, and rhetoric. Addressed to labor economists and informed readers, this paper clarifies what is truly new about LLMs, what is not, and why it matters. Using an analogy to autoregressive models from economics, we explain their stochastic nature, whose fluency is often mistaken for agency. We situate LLMs in the longer history of human–machine outsourcing, from digestion to cognition, and examine disruptive effects on white-collar labor, institutions, and epistemic norms. Risks emerge when synthetic content becomes both product and input, creating feedback loops that erode originality and reliability. Grounding the discussion in conceptual clarity over hype, we argue that while GenAI may substitute for some labor, statistical limits will preserve a key role for human judgment. The question is not only how these tools are used, but which tasks we relinquish and how we reallocate expertise in a new division of cognitive labor." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Handel im Umbruch: Transformation, Beschäftigung und Qualifizierung im Bremer Einzelhandel (2025)
Zitatform
Assmus, Josephine (2025): Handel im Umbruch. Transformation, Beschäftigung und Qualifizierung im Bremer Einzelhandel. (Reihe Arbeit und Wirtschaft in Bremen 52), Bremen: Institut Arbeit und Wirtschaft (IAW), Universität Bremen und Arbeitnehmerkammer Bremen, 29 S.
Abstract
"Der Einzelhandel befindet sich in einem umfassenden Strukturwandel, der durch tiefgreifende technologische, demografische und ökonomische Veränderungen geprägt ist. Parallel dazu führen veränderte Konsummuster, zunehmende Marktvolatilität und eine Erosion der Tarifbindung zu erheblichen Anpassungsanforderungen für Beschäftigte und Betriebe. Der Einzelhandel ist dabei durch eine ausgeprägte Heterogenität hinsichtlich Betriebsgrößen, Beschäftigungsformen und Branchensegmenten gekennzeichnet und zugleich durch hohe Teilzeitquoten, einen überdurchschnittlichen Frauenanteil sowie prekäre Arbeitsverhältnisse geprägt. Der vorliegende Branchenbericht untersucht am Beispiel des Landes Bremen die Auswirkungen von Digitalisierung, demografischem Wandel und Fachkräftemangel auf die Beschäftigtenstruktur, Arbeitsprozesse und Qualifikationsanforderungen im Einzelhandel. Die Ergebnisse zeigen, dass digitale Technologien sowohl Substituierungspotenziale als auch neue Belastungsfaktoren erzeugen. Während Automatisierung und digitale Assistenzsysteme Tätigkeitsprofile verändern und physische Arbeit entlasten können, erhöhen sie zugleich den kognitiven und zeitlichen Druck. Für eine sozialverträgliche Gestaltung des Wandels sind daher erweiterte Mitbestimmungsrechte, gezielte Qualifizierungsstrategien und eine Stärkung der Tarifbindung erforderlich. Qualifizierung und Weiterbildung müssen als zentrale Handlungsfelder institutionell verankert und gleichstellungspolitisch flankiert werden, um Beschäftigungsperspektiven und Teilhabechancen - insbesondere für Frauen - im transformierten Einzelhandel langfristig zu sichern." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
The Labor Market Impact of Digital Technologies (2025)
Zitatform
Aum, Sangmin & Yongseok Shin (2025): The Labor Market Impact of Digital Technologies. (NBER working paper / National Bureau of Economic Research 33469), Cambridge, Mass, 17 S.
Abstract
"We investigate the impact of digital technology on employment patterns in Korea, where firms have rapidly adopted digital technologies such as artificial intelligence (AI), big data, and the internet of things (IoT). By exploiting regional variations in technology exposure, we find significant negative effects on high-skill and female workers, particularly those in non-IT (information technology) services. This contrasts with previous technological disruptions, such as the IT revolution and robotization, which primarily affected low-skill male workers in manufacturing. In IT services, although high-skill employment declined, vacancy postings for high-skill workers increased, implying a shift in labor demand toward newer skill sets. These findings highlight both the labor displacement and the new opportunities generated by digital transformation." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
On automation, labor reallocation and welfare (2025)
Zitatform
Auray, Stéphane & Aurélien Eyquem (2025): On automation, labor reallocation and welfare. In: Journal of Economic Dynamics and Control, Jg. 177. DOI:10.1016/j.jedc.2025.105129
Abstract
"We develop an open-economy model of endogenous automation with heterogeneous firms and labor-market reallocation to quantify the contribution of various trends to the adoption of robots in the U.S. economy. The decline in the relative price of robots is the major trend leading to automation, but interacts with other trends that either hinder (rising entry costs, rising markups) or slightly foster (rising labor productivity, declining trade costs) the adoption of robots. Taken alone, the decline in the relative price of robots produces moderate welfare gains in the long run, but less than labor productivity growth. We then exploit our model to show that a decline in the relative price of robots (i) generates small positive cross-country automation spillovers and (ii) produces inefficient labor-market reallocation since a small subsidy on robots combined with a training subsidy can generate small welfare gains. Our main conclusion is that automation can not be simply modeled as an exogenous decline in the price of robots, and must be analyzed in a broader framework taking into account trends affecting firms, such as the decline in business dynamism and the rise in markups." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))
-
Literaturhinweis
Expertise (2025)
Autor, David; Thompson, Neil;Zitatform
Autor, David & Neil Thompson (2025): Expertise. In: Journal of the European Economic Association, Jg. 23, H. 4, S. 1203-1271. DOI:10.1093/jeea/jvaf023
Abstract
"When job tasks are automated, does this augment or diminish the value of labor in the tasks that remain? We argue the answer depends on whether removing tasks raises or reduces the expertise required for remaining non-automated tasks. Since the same task may be relatively expert in one occupation and inexpert in another, automation can simultaneously replace experts in some occupations while augmenting expertise in others. We propose a conceptual model of occupational task bundling that predicts that changing occupational expertise requirements have countervailing wage and employment effects: automation that decreases expertise requirements reduces wages but permits the entry of less expert workers; automation that raises requirements raises wages but reduces the set of qualified workers. We develop a novel, content-agnostic method for measuring job task expertise, and we use it to quantify changes in occupational expertise demands over four decades attributable to job task removal and addition. We document that automation has raised wages and reduced employment in occupations where it eliminated inexpert tasks, but lowered wages and increased employment in occupations where it eliminated expert tasks. These effects are distinct from—and in the case of employment,opposite to—the effects of changing task quantities. The expertise framework resolves the puzzle of why routine task automation has lowered employment but often raised wages in routine task-intensive occupations. It provides a general tool for analyzing how task automation and new task creation reshape the scarcity value of human expertise within and across occupations." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Fehlzeiten-Report 2025: KI und Gesundheit - Möglichkeiten nutzen, Risiken bewältigen, Orientierung geben (2025)
Zitatform
Badura, Bernhard, Antje Ducki, Markus Meyer, Johanna Baumgardt & Helmut Schröder (Hrsg.) (2025): Fehlzeiten-Report 2025. KI und Gesundheit - Möglichkeiten nutzen, Risiken bewältigen, Orientierung geben. (Fehlzeiten-Report 27), Berlin: Springer, 735 S. DOI:10.1007/978-3-662-71885-8
Abstract
"Der jährlich erscheinende Fehlzeiten-Report informiert umfassend über die Entwicklung des Krankenstandes von Beschäftigten in Deutschland. Neben detaillierten Sekundäranalysen von Versichertendaten werden empirische Studienergebnisse, zeitgemäße methodische Herangehensweisen und Leuchtturmprojekte der Betrieblichen Gesundheitsförderung vorgestellt. Vor dem Hintergrund aktueller technischer Entwicklungen beleuchtet der Fehlzeiten-Report 2025 schwerpunktmäßig Chancen und Herausforderungen des Einsatzes von Künstlicher Intelligenz (KI) in der Arbeitswelt. Er bietet einen orientierenden Überblick zu den Auswirkungen des Einsatzes von KI auf die betriebliche Gesundheitsförderung, Arbeitsumgebungen, Führung und Beschäftigte in Organisationen und erörtert aus unterschiedlichen Perspektiven u.a die folgenden Fragen: - Wie kann KI so zum Einsatz gebracht werden, dass die menschlichen Fähigkeiten erweitert und gleichzeitig die Gesundheit der Beschäftigten und die individuelle Privatsphäre geschützt werden? - Wie gelingt die Entwicklung von KI-Systemen, in denen Mensch und Maschine produktiv zusammenarbeiten? - Welche wissenschaftlich fundierten Lösungsansätze zum menschen- und gesundheitszentrierten Umgang mit KI gibt es im Arbeitsschutz und der betrieblichen Gesundheitsförderung? Darüber hinaus liefert der Fehlzeiten-Report 2025 in gewohnter Qualität Daten und Analysen zu Fehlzeiten von Beschäftigten in Deutschland: - Aktuelle Statistiken zum Krankenstand in allen Branchen - Vergleichende Analysen nach Berufsgruppen, Bundesländern und Städten - Die wichtigsten für Arbeitsunfähigkeit verantwortlichen Krankheitsarten - Detaillierte Auswertungen u.a. zu Arbeitsunfällen, Langzeitarbeitsunfähigkeit, Burnout und Kinderkrankengeld. Zudem gibt es vor dem Hintergrund der aktuellen Diskussion um hohe Fehlzeiten einen Beitrag zur Einführung von Karenztagen und möglichen Effekten einer Absenkung der Lohnersatzrate." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
Robotic capital - skill complementarity (2025)
Zitatform
Battisti, Michele, Massimo Del Gatto, Antonio Francesco Gravina & Christopher F. Parmeter (2025): Robotic capital - skill complementarity. In: Macroeconomic Dynamics, Jg. 29, S. e54. DOI:10.1017/s1365100524000567
Abstract
"Relying upon an original (country-sector-year) measure of robotic capital (RK), we investigate the degree of complementarity/substitutability between robots and workers at different skill levels. We employ nonparametric methods to estimate elasticity of substitution patterns between RK and skilled/unskilled labor over the period 1995–2009. We show that: i) on average, RK exhibits less substitutability with skilled workers compared to unskilled workers, indicating a phenomenon of “RK-Skill complementarity”. This pattern holds in a global context characterized by significant heterogeneity; ii) the dynamic of “RK-Skill complementarity” has increased since the early 2000s; iii) the observed strengthening is more prominent in OECD countries, as opposed to non-OECD countries, and in the Manufacturing sector, compared to non-Manufacturing industries." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Ethical Integration in Public Sector AI. The Case of Algorithmic Systems in the Public Employment Service in Germany (2025)
Zitatform
Bauer, Bernhard, Sabrina Mühlbauer, Kerstin Schlögl-Flierl, Enzo Weber & Paula Ziethmann (2025): Ethical Integration in Public Sector AI. The Case of Algorithmic Systems in the Public Employment Service in Germany. (IAB-Discussion Paper 12/2025), Nürnberg, 32 S. DOI:10.48720/IAB.DP.2512
Abstract
"Dieser Artikel befasst sich mit der ethischen Gestaltung von Künstlicher Intelligenz (KI) im öffentlichen Sektor, wobei der Fokus auf den öffentlichen Arbeitsverwaltungen liegt. Während KI zunehmend zur effizienteren Gestaltung von Verwaltungsprozessen und zur Verbesserung der Dienstleistungserbringung eingesetzt wird, wirft ihre Anwendung in der Arbeitsvermittlung grundlegende Fragen hinsichtlich Fairness, Rechenschaftspflicht und demokratischer Legitimität auf. Das EU-Gesetz zur Künstlichen Intelligenz (EU AI Act) unterstreicht die Dringlichkeit der Bewältigung dieser Herausforderungen, indem es KI-Systeme, die die Arbeitsvermittlung betreffen, als risikoreich einstuft und damit strenge Schutzmaßnahmen vorschreibt, um Diskriminierung zu verhindern und Transparenz zu gewährleisten. Das zentrale Ziel dieser Studie ist es zu untersuchen, wie ethische und soziale Überlegungen systematisch in die Entwicklung und Umsetzung von KI im öffentlichen Sektor eingebunden werden können. Anhand der deutschen öffentlichen Arbeitsverwaltung als Fallstudie stellen wir den Ansatz „Embedded Ethics and Social Sciences” (EE) vor. Dieser Ansatz integriert ethische Überlegungen und den Bezug zur Praxis bereits in die Entwicklung des Modells. Qualitative Erkenntnisse aus Interviews mit Vermittlungsfachkräften verdeutlichen die soziotechnischen Herausforderungen der Umsetzung, insbesondere die Notwendigkeit, Effizienz mit dem Vertrauen der Bürger:innen in Einklang zu bringen. Auf der Grundlage dieser Erkenntnisse geben wir Empfehlungen für die Gestaltung von KI-Systemen, welche sich aus der Integration ethischer und sozialer Überlegungen in die Systementwicklung ergeben. In diesem Zusammenhang diskutieren wir Fragen der Datenethik und Bias, der Fairness und der Rolle erklärbarer KI (XAI). Unsere Analyse zeigt, dass der EE-Ansatz nicht nur die Einhaltung neuer regulatorischer Anforderungen unterstützt, sondern auch die menschliche Aufsicht, die Handlungsfähigkeit und gemeinsame Entscheidungsfindung stärken kann. So deuten die Ergebnisse darauf hin, dass ein ethisch fundiertes Design Fairness, Transparenz und Legitimität in verschiedenen Bereichen der öffentlichen Verwaltung erhöhen kann und somit zu einer verantwortungsvolleren und bürgernahen Umsetzung im digitalen Zeitalter beiträgt." (Autorenreferat, IAB-Doku)
-
Literaturhinweis
Remote work, skill upgrading, and wage inequality post-COVID (2025)
Zitatform
Bennett, Jeremy (2025): Remote work, skill upgrading, and wage inequality post-COVID. In: Economics of Innovation and New Technology, S. 1-24. DOI:10.1080/10438599.2025.2602133
Abstract
"This paper examines how the widespread shift to remote work during the COVID-19 pandemic reshaped skill development and wage inequality across occupations in the United States. Using a difference-in-differences framework and data from the Current Population Survey (CPS), American Time Use Survey (ATUS), and O*NET, we compare outcomes for remote-capable and non-remote occupations before and after the pandemic. Results show that remote-capable jobs experienced significantly higher wage growth – approximately 4–5 percent – relative to non-remote jobs, even after accounting for worker and occupational characteristics. These occupations also displayed greater gains in educational attainment and digital skill engagement, while non-remote occupations faced disruptions in access to training. The findings align with human-capital and task-based theories, suggesting that remote work intensified skill-biased technological inequality. Policy implications include the need for targeted workforce training, equitable digital infrastructure investment, and institutional support for workers in less adaptable roles. The study contributes to understanding how technological and organizational change reshape human capital formation and wage structures in the post-pandemic labor market." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Intersecting Shocks: The Combined Labor Market Impacts of Automation and Immigration (2025)
Bennett, Patrick; Johnsen, Julian Vedeler;Zitatform
Bennett, Patrick & Julian Vedeler Johnsen (2025): Intersecting Shocks: The Combined Labor Market Impacts of Automation and Immigration. (CESifo working paper 12217), München, 41 S.
Abstract
"We study how the labor market shocks of automation and immigration interact to shape workers' outcomes. Using matched employer –employee data from Norwegian administrative registers, we combine animmigration shock triggered by the European Union's 2004 enlargement with an automation shock based on the adoption of industrial robots across Europe. Although these shocks largely occur in separate industries, we show that automation reduces earnings not only in manufacturing but also in construction, where tasks overlap with robot-exposed sectors. Importantly, workers jointly exposed to automation and immigration suffer earnings losses greater than those facing either shock in isolation. These losses are driven by downward occupational mobility into low-wage services and re-sorting into lower-premium firms. Even within the Norwegian welfare system, the ability of social insurance to offset these long-run earnings declines is limited. Our findings underscore the importance of analyzing labor market shocks jointly, rather than in isolation, to fully understand their distributional consequences." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Training or Retiring? How Labor Markets Adjust to Trade and Technology Shocks (2025)
Zitatform
Bertermann, Alexander, Wolfgang Dauth, Jens Suedekum & Ludger Wößmann (2025): Training or Retiring? How Labor Markets Adjust to Trade and Technology Shocks. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 18247), Bonn, 47 S.
Abstract
"How do firms and workers adjust to trade and technology shocks? We analyze two mechanisms that have received little attention: training that upgrades skills and early retirement that shifts adjustment costs to public pension systems. We combine novel data on training participation and early retirement in German local labor markets with established measures of exposure to trade competition and robot adoption. Results indicate that negative trade shocks reduce Training - particularly in manufacturing - while robot exposure increases Training - particularly in indirectly affected services. Both shocks raise early retirement among manufacturing workers. Structural change thus induces both productivity-enhancing and productivity-reducing responses, challenging simple narratives of labor market adaptation and highlighting the scope for policy to promote adjustment mechanisms conducive to aggregate productivity." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Varieties of Gig Work: Germany’s Unique Development in the Platform-based Food Delivery Sector (2025)
Zitatform
Beyer, Jürgen & Katharina Legantke (2025): Varieties of Gig Work: Germany’s Unique Development in the Platform-based Food Delivery Sector. In: Zeitschrift für Soziologie, Jg. 54, H. 4, S. 381-399. DOI:10.1515/zfsoz-2025-2024
Abstract
"Diese Studie untersucht die Entwicklung des plattformbasierten Lebensmittelliefersektors in Deutschland und insbesondere die Gründe dafür, warum sich das in der Gig-Economy übliche Modell mit selbstständigen Kurier:innen hierzulande nicht durchgesetzt hat. Im Gegensatz zu vielen anderen Ländern stellen die großen Lebensmittellieferplattformen in Deutschland ihre Beschäftigten direkt an und gewähren ihnen Rechte sowie Sozialleistungen wie Mindestlohn, bezahlten Urlaub und Lohnfortzahlung im Krankheitsfall. Anhand einer historisch-soziologischen Fallstudie zeigt die Untersuchung, wie der frühe Einfluss von „Bringdienst.de“, das Restaurants Online-Bestellungen ermöglichte, ohne den Lieferprozess selbst zu organisieren, die Entwicklung der Branche maßgeblich geprägt hat. Ein wegweisendes Gerichtsurteil im Jahr 2020 verstärkte zudem die Bedenken hinsichtlich Scheinselbstständigkeit und führte letztlich dazu, dass die Plattformen vom Gig-Worker-Modell mit selbstständigen Kurier:innen Abstand nahmen." (Autorenreferat, IAB-Doku, © De Gruyter)
-
Literaturhinweis
The dynamics of automation adoption: Firm-level heterogeneity and aggregate employment effects (2025)
Zitatform
Bisio, Laura, Angelo Cuzzola, Marco Grazzi & Daniele Moschella (2025): The dynamics of automation adoption: Firm-level heterogeneity and aggregate employment effects. In: European Economic Review, Jg. 173. DOI:10.1016/j.euroecorev.2024.104943
Abstract
"We investigate the impact of investment in automation-related goods on adopting and non-adopting firms in the Italian economy during 2011–2019. We integrate datasets on trade activities, firms’, and workers’ characteristics for the population of Italian importing firms and estimate the effects on adopters ’ outcomes within a difference-in-differences design exploiting import lumpiness in product categories linked to automation technologies (including robots). We find a positive average adoption effect on the adopters’ employment: firms are, on average, around 3% larger in terms of employment after an automation spike. Crucially, the employment effect is heterogeneous across firms: a positive effect is predominant among small firms, which are around 5% larger five years after the spike; on the contrary, a negative displacement effect is predominant among medium and large firms, with an employment contraction at five years of around -4%. This result can shed light on one potential reason behind the mixed results in the literature, i.e. different size distribution of the samples used. We complete the framework with a 5-digit sector-level analysis showing that adopting automation technologies has an overall weak negative effect on aggregate employment, and with an analysis of the competition effects of automation, showing that non-adopters suffer a loss in sales and employment." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
-
Literaturhinweis
AI adoption in the education system: International insights and policy considerations for Italy (2025)
Zitatform
Borgonovi, Francesca, Francesca Bastagli, Maja Ochojska & Giovanni Piumatti (2025): AI adoption in the education system. International insights and policy considerations for Italy. (OECD Artificial Intelligence Papers 52), Paris, 100 S. DOI:10.1787/69bd0a4a-en
Abstract
"This paper examines how artificial intelligence (AI) can be deliberately deployed to tackle persistent disparities in primary and secondary schools and to align curricula with changing skill demands. It focuses on three priorities for Italy’s school system: preventing dropout and promoting learning, reducing the maths gender gap, supporting students with an immigrant background. Drawing on international evidence, the paper reviews how AI can support these objectives, the risks that may arise, and possible mitigation strategies. It also considers how countries are integrating AI literacy and reforming curricula in response to shifting skill needs. The paper proposes key principles and a policy roadmap to guide AI adoption in schools. Recent initiatives in OECD countries illustrate opportunities and risks associated with AI adoption in schools and potential policy options for Italy." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Beliefs about Bots: How Employers Plan for AI in White-Collar Work (2025)
Zitatform
Brull, Eduard, Samuel Maurer & Davud Rostam-Afschar (2025): Beliefs about Bots: How Employers Plan for AI in White-Collar Work. (arXiv papers), 11 S.
Abstract
"We provide experimental evidence on how employers adjust expectations to automation risk in high-skill, white-collar work. Using a randomized information intervention among tax advisors in Germany, we show that firms systematically underestimate automatability. Information provision raises risk perceptions, especially for routine-intensive roles. Yet, it leaves short-run hiring plans unchanged. Instead, updated beliefs increase productivity and financial expectations with minor wage adjustments, implying within-firm inequality like limited rent-sharing. Employers also anticipate new tasks in legal tech, compliance, and AI interaction, and report higher training and adoption intentions." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence (2025)
Zitatform
Brynjolfsson, Erik, Bharat Chandar & Ruyu Chen (2025): Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence. (Working Papers / Stanford Digital Economy Lab), Stanford, 57 S.
Abstract
"This paper examines changes in the labor market for occupations exposed to generative artificial intelligence using high-frequency administrative data from the largest payroll software provider in the United States. We present six facts that characterize these shifts. We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks. In contrast, employment for workers in less exposed fields and more experienced workers in the same occupations has remained stable or continued to grow. We also find that adjustments occur primarily through employment rather than compensation. Furthermore, employment declines are concentrated in occupations where AI is more likely to automate, rather than augment, human labor. Our results are robust to alternative explanations, such as excluding technology-related firms and excluding occupations amenable to remote work. These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Automation and segmentation: Downgrading employment quality among the former “insiders” of Western European labour markets (2025)
Zitatform
Buzzelli, Gregorio (2025): Automation and segmentation: Downgrading employment quality among the former “insiders” of Western European labour markets. In: International Journal of Social Welfare, Jg. 34, H. 2. DOI:10.1111/ijsw.70011
Abstract
"The literature on labor market segmentation traditionally looks at servitisation as the main structural driver behind the rise of employment precariousness, overlooking another crucial engine of the knowledge-economy transition: the Information and Communication Technologies (ICT) revolution. This paper proposes a task-based approach to complement the skill-biased framework usually applied to labor market segmentation, investigating the correlation between occupational exposure to the risk of automation and low-quality employment. The empirical analysis, based on 14 countries sampled from ESS (2002–2018), shows a strong correlation between technological replaceability and low income across all of Western Europe, especially after the Great Recession, while its association with atypical employment is mainly driven by fixed-term contracts in Central and Southern Europe and by part-time arrangements in Anglo-Saxon and Scandinavian countries. Overall, a “recalibrated” dualisation emerges in Western European labor markets, characterized by the diffusion of low labor earnings and atypical contracts among mid-skill routine workers, besides the low-skill service precariat." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
KI-Jobs in Deutschland: Stagnation statt Boom: Eine Analyse von Online-Stellenanzeigen (2025)
Büchel, Jan; Engler, Jan Felix; Mertens, Armin;Zitatform
Büchel, Jan, Jan Felix Engler & Armin Mertens (2025): KI-Jobs in Deutschland: Stagnation statt Boom. Eine Analyse von Online-Stellenanzeigen. 22 S. DOI:10.11586/2025025
Abstract
"Künstliche Intelligenz (KI) ist eine zentrale Zukunftstechnologie, die mehr Effizienz und Produktivität in Unternehmen ermöglichen kann. Vor dem Hintergrund der angespannten wirtschaftlichen Lage Deutschlands und dem vorliegenden demografiebedingten Fachkräftemangel sollten Unternehmen das Potenzial von KI nutzen, um ihre Wettbewerbsfähigkeit zu stärken. Positiv ist, dass im Jahr 2024 etwa jedes fünfte Unternehmen in Deutschland angibt, KI bereits zu nutzen. Der KI-Einsatz benötigt dabei neue Kompetenzen, beispielsweise wenn Unternehmen KI-Lösungen selbst entwickeln möchten. Auch wenn zugekaufte KI-Lösungen im Unternehmen angewendet werden, entstehen Kompetenzbedarfe. Um die Bedarfe der Unternehmen zu erfassen, hat das Institut der deutschen Wirtschaft im Auftrag der Bertelsmann Stiftung Online-Stellenanzeigen mit Bezug zu KI aus den Jahren 2019 bis 2024 analysiert." (Autorenreferat, IAB-Doku)
Weiterführende Informationen
Zusammenfassung der Studie -
Literaturhinweis
Why hours worked decline less after technology shocks? (2025)
Zitatform
Cardi, Olivier & Romain Restout (2025): Why hours worked decline less after technology shocks? In: Journal of International Economics, Jg. 157. DOI:10.1016/j.jinteco.2025.104095
Abstract
"The contractionary effect of technology shocks on hours gradually vanishes over time in OECD countries. To rationalize the decline in hours and its disappearance, we use a VAR-based decomposition of technology shocks into symmetric and asymmetric technology improvements. While hours decline dramatically when technology improves at the same rate across sectors, hours significantly increase when technology improvements occur at different rates. Because they are primarily driven by symmetric technology improvements, permanent technology shocks drive down total hours. Such a decline progressively vanishes due to the growing importance of asymmetric technology shocks. To reach these two conclusions, we simulate a two-sector model which can reproduce the contractionary effect on hours once the economy is internationally open and we allow for production factors’ mobility costs, factor-biased technological change, and home bias. To account for the vanishing decline in hours, we have to let the share of asymmetric technology shocks increase over time." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))
-
Literaturhinweis
AI and the global productivity divide: Fuel for the fast or a lift for the laggards? (2025)
Zitatform
Chaar, Tania, Francesco Filippucci, Cecilia Jona-Lasinio & Giuseppe Nicoletti (2025): AI and the global productivity divide. Fuel for the fast or a lift for the laggards? (OECD Artificial Intelligence Papers 51), Paris, 42 S. DOI:10.1787/c315ea90-en
Abstract
"Artificial Intelligence (AI) has the potential to be an important driver of productivity growth over the next decade, even if with significant cross-country heterogeneity. This paper examines the potential of AI to foster productivity growth in Low-Income Countries (LICs) and Lower-Middle-Income Countries (LMICs). LICs and LMICs risk benefiting less from AI due to low incidence of knowledge-intensive services, where gains from AI mostly occur. Additionally, barriers to AI adoption include inadequate digital infrastructure, low levels of education and skills in the workforce, limited access to financing for high AI adoption costs, and underdeveloped regulatory frameworks. At the same time, LICs and LMICs may benefit from factors such as a young workforce and international spillovers through knowledge transfers. Overall, structural weaknesses in LICs and LMICs risk outweighing these potential advantages. This underscores the need for policies that enhance capabilities for AI adoption in LICs and LMICs and help seizing long-run opportunities from the global AI economy." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
The Iceberg Index: Measuring Workforce Exposure Across the AI Economy (2025)
Chopra, Ayush; Bhattacharya, Santanu; Schwarze, Alice C.; Ahmad, Feroz; Balaprakash, Prasanna; Garg, Aditi; Salvador, DeAndrea; Wright, Teddy; Raskar, Ramesh; Paul, Ayan;Zitatform
Chopra, Ayush, Santanu Bhattacharya, DeAndrea Salvador, Ayan Paul, Teddy Wright, Aditi Garg, Feroz Ahmad, Alice C. Schwarze, Ramesh Raskar & Prasanna Balaprakash (2025): The Iceberg Index: Measuring Workforce Exposure Across the AI Economy. (arXiv papers), 21 S. DOI:10.48550/arXiv.2510.25137
Abstract
"Artificial Intelligence is reshaping America’s over $9.4 trillion labor market, with cascading effects that extend far beyond visible technology sectors. When AI automates quality control in automotive plants, consequences spread through logistics networks, supply chains, and local service economies. Yet traditional workforce metrics cannot capture these ripple effects: they measure employment outcomes after disruption occurs, not where AI capabilities overlap with human skills before adoption crystallizes. Project Iceberg addresses this gap using Large Population Models to simulate the human–AI labor market, representing 151 million workers as autonomous agents executing over 32,000 skills across 3,000 counties and interacting with thousands of AI tools. It introduces the Iceberg Index, a skills-centered metric that measures the wage value of skills AI systems can perform within each occupation. The Index captures technical exposure, where AI can perform occupational tasks, not displacement outcomes or adoption timelines. Analysis shows that visible AI adoption concentrated in computing and technology (2.2% of wage value, approximately $211 billion) represents only the tip of the iceberg. Technical capability extends far below the surface through cognitive automation spanning administrative, financial, and professional services (11.7%, approximately $1.2 trillion). This exposure is fivefold larger and geographically distributed across all states rather than confined to coastal hubs. Traditional indicators such as GDP, income, and unemployment explain less than 5% of this skills-based variation, underscoring why new indices are needed to capture exposure in the AI economy. By simulating how capabilities may spread under alternative scenarios, Project Iceberg enables policymakers and business leaders to identify exposure hotspots, prioritize training and infrastructure investments, and test interventions before committing billions to implementation. Iceberg is built with the AgentTorch framework." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Equalising the effects of automation? The role of task overlap for job finding (2025)
Zitatform
Dabed, Diego, Sabrina Genz & Emilie Rademakers (2025): Equalising the effects of automation? The role of task overlap for job finding. In: Labour Economics, Jg. 96. DOI:10.1016/j.labeco.2025.102766
Abstract
"This paper investigates whether task overlap can equalise the distributional effects of automation for unemployed job seekers displaced from routine jobs. Using a language model, we establish a novel job-to-job task similarity measure. Exploiting the resulting job network to define job markets flexibly, we find that only the most similar jobs affect job finding. Since automation-exposed jobs overlap with other highly exposed jobs, task-based reallocation provides little relief for affected job seekers. We show that this is not true for more recent software exposure, for which task overlap lowers the inequality in job finding." (Author's abstract, IAB-Doku, © 2025 The Authors. Published byElsevier B.V.) ((en))
-
Literaturhinweis
Using Google search data to examine factory automation and its effect on employment (2025)
Zitatform
Diebold, Céline (2025): Using Google search data to examine factory automation and its effect on employment. In: Economic analysis and policy, Jg. 86, S. 1301-1328. DOI:10.1016/j.eap.2025.03.042
Abstract
"This paper revisits the link between robot adoption and employment across more than 100 European regions over a period of five years. A simple model is provided arguing that interest in robots precedes the actual deployment of robots. Thus, a novel instrument is introduced: interest in automation revealed by Google searches. This allows for a tentatively causal interpretation of the results. A small, yet significant positive aggregate effect is identified, along with heterogeneous effects across sex and educational attainment. The local effect on aggregate employment tends to be roughly twice as large as the spillover effect on neighbouring regions." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V. on behalf of The Economic Society of Australia (Queensland) Inc.) ((en))
-
Literaturhinweis
How do structural trends affect labour market shortages and mismatch? (2025)
Zitatform
Dorville, Yann, Francesco Filippucci & Luca Marcolin (2025): How do structural trends affect labour market shortages and mismatch? (OECD productivity working papers 38), Paris, 63 S. DOI:10.1787/acfb5c31-en
Abstract
"This paper examines how AI and digital technology diffusion, the green transition, globalisation and population ageing jointly affect labour market tightness across 26 OECD countries and 34 sectors. It finds that digitalisation and decarbonisation increase tightness, while ageing does so only over time. Import competition and labour-substituting AI diffusion, conversely, reduce shortages." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Macroeconomic and Labor Market Drivers of AI Adoption in Europe: A Machine Learning and Panel Data Approach (2025)
Zitatform
Drago, Carlo, Alberto Costantiello, Marco Savorgnan & Angelo Leogrande (2025): Macroeconomic and Labor Market Drivers of AI Adoption in Europe: A Machine Learning and Panel Data Approach. In: Economies, Jg. 13, H. 8. DOI:10.3390/economies13080226
Abstract
"This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to credit, export activity, gross capital formation, inflation, openness to trade, and labor market structure influence the share of firms that adopt at least one AI technology. The research covers all 28 EU members between 2018 and 2023. We employ a set of robustness checks using a combination of fixed-effects, random-effects, and dynamic panel data specifications supported by Clustering and supervised learning techniques. We find that AI adoption is linked to higher GDP per capita, healthcare spending, inflation, and openness to trade but lower levels of credit, exports, and capital formation. Labor markets with higher proportions of salaried work, service occupations, and self-employment are linked to AI diffusion, while unemployment and vulnerable work are detractors. Cluster analysis identifies groups of EU members with similar adoption patterns that are usually underpinned by stronger economic and institutional fundamentals. The results collectively suggest that AI diffusion is shaped not only by technological preparedness and capabilities to invest but by inclusive macroeconomic conditions and equitable labor institutions. Targeted policy measures can accelerate the equitable adoption of AI technologies within the European industrial economy." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Artificial intelligence and labor market outcomes: AI has created new jobs to meet digital and automation needs, and those equipped with AI capital enjoy increased employment and wages (2025)
Zitatform
Drydakis, Nick (2025): Artificial intelligence and labor market outcomes. AI has created new jobs to meet digital and automation needs, and those equipped with AI capital enjoy increased employment and wages. (IZA world of labor 514), Bonn, o. S. DOI:10.15185/izawol.514
Abstract
"AI is reshaping the labor market by creating new jobs and increasing competition for high-skilled roles, benefiting those with AI capital. While AI may boost productivity in certain jobs, it also widens the gap between high- and low-skilled employees. Less-educated employees face higher risks of displacement and reduced income. Additionally, AI introduces challenges related to workforce adaptability, trust, ethics, and transparency, which negatively impact employees' job realities. Policymakers should navigate these changes to maximize the benefits of AI while mitigating its adverse effects." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Narrowing the digital divide: Economic and social convergence in Europe’s digital transformation (2025)
Duff, Cían; Soldi, Rossella; Hyland, Marie; Cavallini, Simona; Peruffo, Eleonora; Krieg, Marielena;Zitatform
Duff, Cían, Marie Hyland, Marielena Krieg, Eleonora Peruffo, Simona Cavallini & Rossella Soldi (2025): Narrowing the digital divide. Economic and social convergence in Europe’s digital transformation. (Eurofound research report / European Foundation for the Improvement of Living and Working Conditions), Dublin, 822 S. DOI:10.2806/1764165
Abstract
"Digitalization has been on the EU policy agenda since 2000. While great strides have been made in this area over the past two decades, the digital transformation is not yet complete. This report seeks to deepen our understanding of the evolution towards a digital Europe. By applying the lens of convergence, the report assesses the progress of Member States towards the EU ’s policy targets, where Member States are growing together and wheredigital gaps are expanding. It also considers the gaps in the progress of digitalization between socioeconomic groups and regions. According to almost all indicators analysed, historically lower-performing Member States have been catching up with the digital leaders. However, at a more granular level, digitalization of businesses has been uneven and significant inequalities persist between regions and socioeconomic groups. The report shines a light on the role of digitalization in the EU’s economic convergence and considers the progress in and benefits of digitalisation for the private sector. The findings show that access is still an issue for vulnerable groups, in particular low-income households, older individuals and those with lower levels of education. Importantly, these are the groups that are more reliant on public services, and they may struggle to access e-government. While progress is being made, some groups remain at risk of being left behind in the digital transition. Considering this, the report highlights a range of policy approaches being deployed across Europe that aim to narrow the digital divide." (Author's abstract, IAB-Doku) ((en))
-
Literaturhinweis
Industrial robots and employment change in manufacturing: A decomposition analysis (2025)
Zitatform
Eder, Andreas, Wolfgang Koller & Bernhard Mahlberg (2025): Industrial robots and employment change in manufacturing: A decomposition analysis. In: Structural Change and Economic Dynamics, Jg. 74, S. 591-602. DOI:10.1016/j.strueco.2025.05.014
Abstract
"This paper examines the contribution of industrial robots to employment change in manufacturing in a sample of 17 European countries and the USA over the period 2004 to 2019. We combine index decomposition analysis (IDA) and production-theoretical decomposition analysis (PDA). First, we use IDA to decompose employment change in the manufacturing industry into changes in (aggregate) manufacturing output, changes in the sectoral structure of the manufacturing industry, and changes in labor intensity (the inverse of labor productivity) which is a composite index of labour intensity change within each of the nine sub-sectors of total manufacturing. Second, we use PDA to further decompose labor intensity change to isolate the contribution of technical efficiency change, technological change, human capital change, change in non-robot capital intensity and change in robot capital intensity to employment change. In almost all of the countries considered, labour intensity is falling in entire manufacturing, exerting a dampening effect on employment. Robotization contributes to this development by reducing labor intensities and employment in all countries and sub-sectors, though to varying degrees. Manufacturing output, in turn, grows in all countries except Greece, Spain and Italy, which increases employment and counteracts or in some countries even more than offsets the dampening effect of declining labor intensities. The structural change within manufacturing has an almost neutral effect in many countries." (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))
-
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))
-
Literaturhinweis
Cross-country skills-technology policy debates through large language models (2025)
Einhoff, Jan; López Trejos, Isabella; Paunov, Caroline;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))
-
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))
-
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)
-
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))
-
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.
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))
-
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))
-
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)
-
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)
-
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)
-
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))
-
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))
-
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))
Aspekt auswählen:
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