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Burstedde, Alexander & Jurek Tiedemann (2025): Digitalisierung der Wirtschaft in Deutschland: Kompetenzbarometer: Fachkräftesituation in Digitalisierungsberufen – Beschäftigungsaufbau und Fachkräftemangel bis 2028. Eine Studie im Projekt (Nr. 3/19) „Entwicklung und Messung der Digitalisierung der Wirtschaft am Standort Deutschland“ im Auftrag des Bundesministeriums für Wirtschaft und Klimaschutz (BMWK). Köln, 28 S.

Abstract

"Digitalisierungsberufe sind für den Erfolg der digitalen Transformation von essenzieller Bedeutung. Sie beschreiben Kompetenzprofile, die benötigt werden, um neue digitale Schlüsseltechnologien zu entwickeln und herzustellen oder durch vertiefte technische Kenntnisse und Fertigkeiten deren Nutzung und Verbreitung zu realisieren. Das beinhaltet nicht nur Kompetenzen in Informatik, sondern auch in Elektronik und anderen Bereichen. Diese Studie beschreibt die potenzielle Entwicklung von Beschäftigung und Fachkräftelücke bis 2028, wenn sich die Trends der Jahre 2017 bis 2023 weiter fortsetzen würden." (Textauszug, IAB-Doku)

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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))

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Büchel, Jan, Barbara Engels & Jan Engler (2025): Cybersicherheit: Kompetenzen gefragter denn je. (IW-Kurzberichte / Institut der Deutschen Wirtschaft Köln 2025,39), Köln, 3 S.

Abstract

"Cyberangriffe treffen deutsche Unternehmen immer stärker – und die reagieren. Zwischen 2019 und 2024 hat sich die Zahl der Online-Stellenanzeigen, in denen Cybersicherheitskompetenzen gefordert werden, von 117.000 auf 203.000 deutlich erhöht. Kompetenzen rund um digitale Sicherheit sind für eine funktionierende Wirtschaft und Verwaltung zentral geworden." (Autorenreferat, IAB-Doku)

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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)

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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))

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Caselli, Mauro, Andrea Fracasso, Arianna Marcolin & Sergio Scicchitano (2025): Technological innovations and workers’ job insecurity: the moderating role of human resource strategies. In: Journal of industrial and business economics, Jg. 52, H. 1, S. 153-176. DOI:10.1007/s40812-024-00329-w

Abstract

"In this paper, we empirically assess the impact of firms’ technological innovations on the workers’ perceived probability of job loss. We take advantage of a unique dataset based on a large and representative cross-sectional survey covering several characteristics of Italian workers and their firms. We find that a firm ’s technological adoption reduces job insecurity among its surviving workers, and the effect is stronger when the innovation makes tasks simpler and their execution more precise. We also find that the relationship between technological innovation and job insecurity is moderated by human resource strategies, such as training programs, labor-saving automation and dismissal plans adopted after the introduction of the innovation. Thus, workers’ perceptions of job insecurity vary significantly across innovative firms, and firms’ human resource strategies act as arelevant moderating factors." (Author's abstract, IAB-Doku) ((en))

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Caselli, Mauro, Andrea Fracasso, Sergio Scicchitano, Silvio Traverso & Enrico Tundis (2025): What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment. In: Research Policy, Jg. 54, H. 1. DOI:10.1016/j.respol.2024.105135

Abstract

"This work investigates the impact that changes in the local exposure to robots had on changes in Italian employment over the period 2011–2018. It contributes to the debate by providing novel and granular evidence on the impact of robot adoption on new activity-based groups of occupations and by focusing on the overlap between the functional similarities of robot applications and occupations. This framework, consistently centered on workers ’ and robots’ activities, reveals highly heterogeneous effects of robotization, ranging from positive to negative across different groups of occupations, thereby supporting a nuanced and granular reading of this debated phenomenon. In particular, the local share of robot operators increases where the increase in robot adoption is larger, while the local share of workers using intensively their torso decreases." (Author's abstract, IAB-Doku, © 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))

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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))

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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))

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Chueri, Juliana & Marius R. Busemeyer (2025): Different status, same demands? The social policy preferences of platform workers in OECD countries. In: Competition and Change, S. 1-18. DOI:10.1177/10245294251318440

Abstract

"Platform work has introduced a new dimension of precarity in the labor market, as platform workers face high labor market risks and have limited access to social protection. The expansion of this employment status raises the question of whether platform workers have distinct social policy preferences from workers with similar socioeconomic backgrounds who are not employed in the platform economy. This paper empirically examines how and under what circumstances the social policy preferences of platform workers differ from those of other workers. We find that platform workers are more likely to demand more compensatory labor market policies than regular workers. Also, they are more likely to demand more social investment-type policies than regular and atypical workers who do not engage in the platform economy. We also find evidence for contextual effects: whereas welfare state generosity is associated with weaker demand from platform workers for compensatory labor market policies, it is associated with higher support for social investment. Our results suggest that the expansion of platform work will fuel demands for welfare expansion, specifically focusing on social investment." (Author's abstract, IAB-Doku) ((en))

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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))

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De Vera, Micole & Javier Garcia‐Brazales (2025): Establishment size and the task content of jobs: evidence from 46 countries. In: Economica, Jg. 92, H. 366, S. 548-579. DOI:10.1111/ecca.12563

Abstract

"Using a mix of household- and employer-based survey data from 46 countries, we provide novel evidence that workers in larger establishments perform more non-routine analytical tasks, even within narrowly defined occupations. Moreover, workers in larger establishments rely more on the use of information and communication technologies to perform these tasks. We also document a 15% raw wage premium that workers in larger establishments enjoy relative to their counterparts in smaller establishments. A mediation analysis shows that our novel empirical facts on the task content of jobs are able to explain 5–20% of the establishment size wage premium, a similar fraction to what can be explained by selection of workers on education, gender and age." (Author's abstract, IAB-Doku) ((en))

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Di Battista, Attilio, Sam Grayling, Ximena Játiva, Till Leopold, Ricky Li, Shuvasish Sharma & Saadia Zahidi (2025): Future of Jobs Report 2025. Insight Report. (The future of jobs report), Cologny/Geneva, 289 S.

Abstract

"Over the past decade, the World Economic Forum’s bi-annual Future of Jobs Report has followed evolving technological, societal and economic trends to understand occupational disruption and identify opportunities for workers to transition to the jobs of the future. As we enter 2025, the landscape of work continues to evolve at a rapid pace. Transformational breakthroughs, particularly in generative artificial intelligence (GenAI), are reshaping industries and tasks across all sectors. These technological advances, however, are converging with a broader array of challenges, including economic volatility, geoeconomic realignments, environmental challenges and evolving societal expectations. In response, this fifth edition of the Future of Jobs Report expands its focus, offering a comprehensive analysis of the interconnected trends shaping the global labor market. Central to the report is a unique dataset derived from an extensive survey of global employers. This year’s edition captures the perspectives of over 1,000 employers – representing more than 14 million workers across 22 industry clusters and 55 economies – providing unparalleled insights into the emerging jobs landscape for the 2025-2030 period. These perspectives are further enriched by research collaborations and data partnerships with ADP, Coursera, Indeed and LinkedIn, whose innovative data and analysis complement the survey findings." (Text excerpt, IAB-Doku) ((en))

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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))

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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))

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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))

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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))

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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))

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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))

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Eiffe, Franz Ferdinand, Sara Riso, Elena Biaggi, Jasper van Loo & Grigorios Miliadis (2025): SME digitalisation in the EU: Trends, policies and impacts. (Eurofound research report / European Foundation for the Improvement of Living and Working Conditions), Luxembourg, 78 S. DOI:10.2806/8684886

Abstract

"This report discusses the digital transformation of small and medium-sized enterprises (SMEs) in the European Union, highlighting its importance for their competitiveness and the EU’s economy. The report explores the degreeof digitalisation in SMEs in the EU, including the adoption of digital technologies, e-commerce and e-business practices. It also examines the impact of the COVID-19 pandemic on SMEs’ digitalisation and identifieskey challenges, including lack of infrastructure, financing and digital skills. In addition, the report reviews policy frameworks and support measures related to digitalisation and the development of digital skills in SMEs. Furthermore, it presents an empirical analysis of how digital technology use is related to job quality at the workplace level." (Author's abstract, IAB-Doku) ((en))

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Einhoff, Jan, Isabella López Trejos & Caroline Paunov (2025): Cross-country skills-technology policy debates through large language models. (OECD science, technology and industry working papers 2025,20), Paris, 43 S. DOI:10.1787/d5f669be-en

Abstract

"Language models, this paper conducts a cross-country comparative innovation policy analysis of skills-technology policy debates across seven OECD member countries (Austria, Canada, Finland, Germany, Korea, Sweden, and the United Kingdom). Results highlight the dominance of STEM (science, technology, engineering and mathematics) and digital skills in these policy debates, the relative neglect of green skills, and the emphasis on soft skills across all technology fields. The analysis also identifies common policy instruments, which include collaborative platforms and direct financial support. Overall, the paper shows how large language models can help policy analysts identify patterns and gaps in extensive policy texts that nonetheless critically demands expert oversight and careful interpretation." (Author's abstract, IAB-Doku) ((en))

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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))

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Engberg, Erik, Mark Hellsten, Farrukh Javed, Magnus Lodefalk, Radka Sabolová, Sarah Schroeder & Aili Tang (2025): Artificial intelligence, hiring and employment: job postings evidence from Sweden. In: Applied Economics Letters, S. 1-6. DOI:10.1080/13504851.2025.2497431

Abstract

"This paper investigates the impact of artificial intelligence (AI) on hiring and employment, using the universe of job postings published by the Swedish Public Employment Service from 2014 to 2022 and full-population administrative data for Sweden. We exploit a detailed measure of AI exposure according to occupational content and find that establishments exposed to AI are more likely to hire AI workers. Survey data further indicate that AI exposure aligns with greater use of AI services. Importantly, rather than displacing non-AI workers, AI exposure is positively associated with increased hiring for both AI and non-AI roles. In the absence of substantial productivity gains that might account for this increase, we interpret the positive link between AI exposure and non-AI hiring as evidence that establishments are using AI to augment existing roles and expand task capabilities, rather than to replace non-AI workers." (Author's abstract, IAB-Doku) ((en))

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Engel, Sonja (2025): Kassensturz. Daten, Fakten und Erfahrungen aus der Arbeitswelt des Berliner Einzelhandels. Branchenbericht. Berlin, 45 S.

Abstract

"Dieser Branchenbericht nimmt die Beschäftigung und die Beschäftigten des Berliner Einzelhandels genauer in den Blick. Der Bericht soll Anregung sein für Gespräche – zwischen Kolleg:innen, Arbeitnehmenden, Betriebsräten und Arbeitgebenden, sowie Akteur:innen, die sich in verschiedenen Positionen und in unterschiedlichen (politischen) Institutionen mit dieser Branche befassen. Es werden Daten und Statistiken analysiert, Fakten zusammengetragen und Perspektiven verschiedener Akteur:innen der Branche dargestellt. Er bietet Informationen über die aktuelle Situation und gibt einen Überblick über die Entwicklungen und Trends der vergangenen Jahre, präsentiert Einblicke in die Arbeitsbedingungen der Beschäftigten und die Herausforderungen, mit denen die Branche zu kämpfen hat. Auch der Onlinehandel und die Digitalisierung der Arbeit sowie die Frage des Fachkräftemangels werden genauer betrachtet. Für einen Gastbeitrag konnten wir Sarah Kuhn und Dr. Holger Seibert vom Institut für Arbeitsmarkt- und Berufsforschung (IAB) Berlin-Brandenburg gewinnen, die einen Exkurs zum Thema der Ersetzbarkeit von Tätigkeiten im Einzelhandel durch digitale Technologien präsentieren. Diese Publikation beruht dabei auf der Auswertung verschiedener Quellen: Offizielle Statistiken und Analysen, die von der Bundesagentur für Arbeit und weiteren Institutionen erhoben und veröffentlicht werden, sind eben - so betrachtet worden wie Ergebnisse wissenschaftlicher Untersuchungen und Umfrageergebnisse und Einschätzungen der Sozialpartner. Die Vereinte Dienstleistungsgewerkschaft (ver.di) und die von ihr geleisteten Sonderauswertungen der Daten des DGB-Index für Gute Arbeit liefern wichtige Erkenntnisse für das Verständnis des Arbeitsalltags der Arbeitnehmenden. Der Handelsverband Deutschland (HDE) trägt mit seinen Befragungen und Datenaufbereitungen die Perspektive der Unternehmen und Betriebe bei. Darüber hinaus kommen weitere Akteur:innen zu Wort, mit denen Hintergrundgespräche und Interviews geführt wurden, oder die an den Veranstaltungen des Projekts Joboption Berlin – drei Sozialpartnerdialogen und einem Werkstattgespräch teilgenommen haben." (Textauszug, IAB-Doku)

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Enrique, Fernandez Macias, Gonzalez Vazquez Ignacio, Torrejon Perez Sergio & Nurski Laura (2025): Work in the Digital Era: How Technology is Transforming Work and Occupations. (JRC science for policy report JRC141451), Brüssel, 87 S.

Abstract

"This report provides a comprehensive analysis of the impact of digital technologies on work and occupations in Europe, critically reassessing dominant narratives of mass unemployment and job polarisation. The report synthesises work done by the JRC Employment team over the last years. Drawing on a wide range of empirical research, the report introduces an analytical framework distinguishing three main vectors of change: automation, the replacement of labour by machines; digitisation, the increasing use of digital tools in work processes; and platformisation, the use of digital platforms for coordinating work. Contrary to widespread fears, our research finds that the impact of automation, such as industrial robots, on net employment levels in recent decades has been modest and often positive. While specific tasks are automated, this has primarily boosted productivity and led to a reallocation of labour rather than a net destruction of jobs. The most profound transformation stems from digitisation. This process, while enhancing efficiency, has fundamentally altered work organisation by enabling unprecedented levels of standardisation, monitoring, and managerial control. This creates a central paradox: while employment shifts away from routine occupations, work processes within many non-routine professional roles are becoming increasingly routinised and subject to digital control, impacting worker autonomy and job quality. Finally, the report identifies the rise of platformisation, not just in the gig economy, but as a logic of algorithmic management and surveillance extending into traditional workplaces. This trend is reshaping the nature of workplace control across the economy. Analysis of occupational structures reveals that job upgrading, rather than job polarisation, has been the most common pattern of change across the EU, driven largely by the growth of high-skilled service sector jobs. The report concludes that the primary impact of the digital era on work is a qualitative transformation in its nature, focusing on coordination, control, and job quality. The effects of technology are not deterministic; they are strongly mediated by institutional frameworks, with regulation and collective bargaining playing a crucial role in shaping outcomes for workers in the digital age." (Author's abstract, IAB-Doku) ((en))

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Fitzenberger, Bernd & Christian Kagerl (2025): Arbeitsmarkt im Wandel: Deutschland muss die Transformation annehmen, um seine Produktivität und Wettbewerbsfähigkeit zu stärken. (IAB-Forschungsbericht 12/2025), Nürnberg, 21 S. DOI:10.48720/IAB.FB.2512

Abstract

"Der deutsche Arbeitsmarkt zeigt sich trotz wirtschaftlicher Schwäche und der wiederkehrenden Bezeichnung von Deutschland als „krankem Mann Europas“ überraschend robust. Die Beschäftigungsquote liegt mit 77,4 Prozent weiterhin auf einem hohen Niveau, doch die Zahl der offenen Stellen ist seit ihrem Höchststand 2022 deutlich gesunken, während die Arbeitslosenquote steigt. Besonders betroffen sind Langzeitarbeitslose und Personen ohne schulischen oder beruflichen Abschluss. Gleichzeitig bleibt der Fachkräftemangel eine zentrale Herausforderung, da viele Stellen nicht besetzt werden können. Die Koexistenz von steigender Arbeitslosigkeit und unbesetzten Stellen bleibt ein entscheidendes Problem für die Bewältigung des wirtschaftlichen Wandels. Eine der größten strukturellen Schwächen ist das stagnierende Produktivitätswachstum. Während die Produktivität in den 2000er-Jahren noch stieg, stagniert sie seit den 2010er-Jahren weitgehend. Besonders problematisch ist die wachsende Diskrepanz zwischen der Produktivität pro Arbeitsstunde und der Produktivität pro Arbeitnehmer, wovon sich letztere deutlich schlechter entwickelt. Die Gründe hierfür sind vielfältig: Neben einer zunehmenden Teilzeitarbeit und einem Beschäftigungszuwachs in Sektoren mit niedriger Produktivität – etwa im Gesundheits- und Bildungsbereich – verhindern geringe Investitionen in Digitalisierung und technologische Innovationen, aber auch in Aus- und Weiterbildung, eine stärkere Produktivitätssteigerung. Besonders das produzierende Gewerbe, das lange das Rückgrat der deutschen Wirtschaft bildete, gerät zunehmend unter Druck. Die Industrieproduktion liegt noch immer unter dem Vorkrisenniveau, während die Beschäftigung in der jüngeren Vergangenheit stagnierte und aktuell rückläufig ist. Besonders die Automobilbranche steht vor großen Herausforderungen: Neben der sinkenden Nachfrage nach Elektroautos machen chinesische Wettbewerber den deutschen Herstellern zunehmend Konkurrenz. Auch Maschinenbau und Metallindustrie kämpfen mit strukturellen Problemen. Zudem belasten hohe Energiepreise und eine schwächelnde Exportnachfrage – insbesondere aus China – die deutsche Industrie. Trotz der wirtschaftlichen Schwäche und den Unsicherheiten über die zukünftige Entwicklung mangelt es weiterhin an Fachkräften. Vor allem kleinere Betriebe und das Bau- sowie das Gastgewerbe haben Schwierigkeiten, qualifizierte Arbeitskräfte zu finden. Eine Ursache hierfür ist die geringe Mobilität auf dem Arbeitsmarkt. Während Transformationen üblicherweise mit einer Umschichtung von Arbeitsplätzen verbunden sind, zeigt sich dieser Effekt in Deutschland bislang kaum. Die hohe Nutzung von Kurzarbeitergeld während der Pandemie hat die Beschäftigung stabilisiert, könnte jedoch den Anpassungsprozess verzögert haben, wenngleich hierfür belastbare empirische Belege fehlen. Deutschland muss die Digitalisierung und die Dekarbonisierung annehmen und nutzen, um seine Wettbewerbsfähigkeit zu erhalten. Besonders Berufe mit geringen Qualifikationsanforderungen sind durch Automatisierung bedroht. Gleichzeitig entstehen neue Beschäftigungsmöglichkeiten im Bereich der grünen Technologien. Der Wandel erfordert jedoch gezielte Investitionen in Weiterbildung und Umschulungen, um Beschäftigte auf die neuen Anforderungen vorzubereiten. Doch genau hier zeigen sich große Defizite. Die betriebliche Weiterbildung ist nach einem pandemiebedingten Einbruch noch nicht auf das Vorkrisenniveau zurückgekehrt, und die Zahl neu abgeschlossener Ausbildungsverträge liegt seit 2020 jedes Jahr unter einer halben Million. Zudem verschlechtern sich die schulischen Leistungen, was langfristig die Qualifikationsbasis der Erwerbsbevölkerung schwächen könnte. Deutschland steht damit vor einer großen Herausforderung: Die alternde Erwerbsbevölkerung verschärft den Fachkräftemangel, während Produktivitätsschwäche und Wettbewerbsverlust die wirtschaftliche Dynamik hemmen. Die Verbesserung der digitalen Kompetenzen und die Förderung der beruflichen Mobilität werden für die Steigerung der Arbeitsproduktivität und die Sicherung des Wirtschaftswachstums von entscheidender Bedeutung sein. Um den Wandel erfolgreich zu gestalten, sind massive Investitionen in Digitalisierung, Dekarbonisierung und Bildung dringend erforderlich. Nur wenn das Land der Aus- und Weiterbildung Priorität einräumt und sich dem Wandel stellt, kann es gut bezahlte Arbeitsplätze sichern und seine Position als Europas größte Volkswirtschaft behaupten." (Autorenreferat, IAB-Doku)

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Fontanelli, Luca, Mattia Guerini, Raffaele Miniaci & Angelo Secchi (2025): Predictive AI and productivity growth dynamics: Evidence from French firms. In: Journal of Economic Behavior & Organization, Jg. 240. DOI:10.1016/j.jebo.2025.107336

Abstract

"While artificial intelligence (AI) adoption holds the potential to enhance business operations through improved forecasting and automation, its relation with average productivity growth remain highly heterogeneous across firms. This paper shifts the focus and investigates the impact of predictive AI on the volatility of firms’ productivity growth rates. Using firm-level data from the 2019 French ICT survey, we provide robust evidence that AI use is associated with increased volatility. This relationship persists across multiple robustness checks, including analyses balancing AI users and other firms based on key observables. To propose a possible mechanisms underlying this relation, we compare firms that purchase AI from external providers (“AI buyers”) and those that develop AI in-house (“AI developers”). Our results show that heightened volatility is concentrated among AI buyers, whereas firms that develop AI internally experience no such association. Finally, we find that the AI-volatility link among “AI buyers” is mitigated in firms with a higher share of ICT engineers and technicians, suggesting that AI’s successful integration requires complementary human capital." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))

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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))

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Fouarge, Didier, Marie-Christine Fregin, Simon Janssen, Mark Levels, Raymond Montizaan, Pelin Özgül, Nicholas Rounding & Michael Stops (2025): How AI-Augmented Training Improves Worker Productivity. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 18224), Bonn, 29 S., App.

Abstract

"We analyze the impact of AI-augmented training on worker productivity in a financial services company. The company introduced an AI tool that provides performance feedback on call center agents to guide their training. To estimate causal effects, we exploit the staggered roll out of the AI-tool. The AI-augmented training reduces call handling time by 10 percent. We find larger effects for short-tenured workers because they spend less time putting clients on hold. But the AI-augmented training also improves communication style with relatively stronger effects for long-tenured agents, and we find slightly positive effects on customer satisfaction." (Author's abstract, IAB-Doku) ((en))

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Freiling, Thomas, Matthias Kohl, Christoph Krause & Bastian Steinmüller (2025): Berufsorientierung und Weiterbildung in der digitalen Transformation. Neue Qualifizierungsansätze für die Metall- und Elektroindustrie. Bielefeld: wbv Media, 221 S. DOI:10.3278/9783763978311

Abstract

"Die Publikation untersucht die Auswirkungen gesellschaftlicher und technologischer Transformationsprozesse auf die berufliche Orientierung und Qualifizierung. Im Fokus stehen die Herausforderungen, die durch Digitalisierung, Automatisierung und den Einsatz von Künstlicher Intelligenz entstehen, insbesondere in der Metall- und Elektroindustrie. Es werden innovative Bildungsangebote vorgestellt, die darauf abzielen, Fachkräfte, Auszubildende und Jugendliche optimal auf die dynamischen Anforderungen der modernen Arbeitswelt vorzubereiten. Der Band gliedert sich in mehrere Kapitel, die zunächst die aktuellen Veränderungen in der Arbeitswelt analysieren. Anschließend werden pädagogische Konzepte für eine zeitgemäße Berufsorientierung präsentiert. Ein weiterer Schwerpunkt liegt auf der Entwicklung von Qualifizierungsmodulen, die in enger Zusammenarbeit mit regionalen Unternehmen konzipiert wurden, um den spezifischen Bedürfnissen der Praxis gerecht zu werden. Die Publikation richtet sich an Bildungsforscher:innen, Pädagog:innen, Ausbilder:innen sowie Entscheidungsträger:innen in Unternehmen und Bildungseinrichtungen, die sich mit der Gestaltung zukunftsorientierter Bildungsangebote befassen." (Verlagsangaben, IAB-Doku)

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Friedrich, Teresa Sophie, Carlotta Hesener & Basha Vicari (2025): Trotz fortschreitender Digitalisierung der Arbeitsplätze stagniert die Homeoffice-Nutzung. In: IAB-Forum – Grafik aktuell H. 12.06.2025, 2025-06-07. DOI:10.48720/IAB.FOO.GA.20250612.01

Abstract

"Die Digitalisierung auf dem deutschen Arbeitsmarkt hat durch die Covid-19 Pandemie einen „Boost“ erfahren. Dieser ging vor allem mit dem sprunghaften Anstieg der Nutzung von Homeoffice sowie von digitaler Kommunikation und Kollaboration einher. Während allerdings die Nutzung digitaler Technologien am Arbeitsplatz in den letzten Jahren weiter vorangeschritten ist, gilt dies nicht für die Nutzung von Homeoffice. Hier scheint der Scheitelpunkt weitgehend erreicht zu sein." (Autorenreferat, IAB-Doku)

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Friedrich, Martin, Ines Helm, Julia Lang & Christoph Müller (2025): Lieferdienste in Deutschland: Solo-Selbstständigkeit hat zwischen 2018 und 2021 stark abgenommen (Serie "Beschäftigung in der Gig-Ökonomie"). In: IAB-Forum H. 04.06.2025, 2025-06-04. DOI:10.48720/IAB.FOO.20250604.01

Abstract

"Über Solo- und Scheinselbstständigkeit bei Online-Lieferdiensten wird in der Öffentlichkeit häufig mit Sorge um die soziale Absicherung der dort tätigen Plattformarbeiter*innen diskutiert. Während sich die Erwerbstätigkeit in der Lieferdienstbranche zwischen 2012 und 2021 verdoppelt hat, hat der Anteil der Solo-Selbstständigen deutlich abgenommen. Im Jahr 2021 waren mehr als 95 Prozent der Lieferdienstfahrer*innen abhängig beschäftigt." (Autorenreferat, IAB-Doku)

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Friedrich, Martin, Ines Helm, Julia Lang & Christoph Müller (2025): Algorithmisches Management bei App-basierten Lieferdiensten: Fast die Hälfte der betroffenen Gig-Worker fühlt sich dadurch überwacht. In: IAB-Forum H. 23.09.2025. DOI:10.48720/IAB.FOO.20250923.01

Abstract

"Arbeit auf digitalen Plattformen zeichnet sich durch den Einsatz von algorithmischem Management aus. Eine Befragung zeigt, wie Gig-Worker bei App-basierten Lieferdiensten diese Praxis wahrnehmen. Die überwiegende Mehrheit der Gig-Worker gibt an, dass ihre Lieferdienstplattform digitale Arbeitsmittel beispielsweise einsetzt, um ihnen Aufgaben automatisch zuzuweisen und ihren Standort zu verfolgen. Fast die Hälfte der Betroffenen fühlt sich dadurch überwacht." (Autorenreferat, IAB-Doku)

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Friedrich, Martin, Ines Helm, Ramona Jost, Julia Lang & Christoph Müller (2025): App-basierte Lieferdienste in Deutschland: Warum Menschen Gig-Work aufnehmen und meist schnell wieder beenden (Serie: „Beschäftigung in der Gig-Ökonomie“). In: IAB-Forum H. 16.04.2025. DOI:10.48720/IAB.FOO.20250416.01

Abstract

"App-basierte Lieferdienste haben sich in den letzten Jahren rasant ausgebreitet. Das hat auch die öffentliche Diskussion um schlechte Arbeitsbedingungen der dort beschäftigten Gig-Worker angefacht. Allerdings gibt es bisher wenige gesicherte Erkenntnisse darüber, was Menschen zur Aufnahme von Gig-Jobs bewegt. Über die Gründe zur Beendigung dieser meist kurzen Jobs ist ebenfalls wenig bekannt. Das IAB bringt mit Ergebnissen einer neuen Befragung Licht in dieses Dunkel." (Autorenreferat, IAB-Doku)

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Garcia-Lazaro, Aida, Jorge Mendez-Astudillo, Susan Lattanzio, Charles Larkin & Linda Newnes (2025): The digital skill premium: Evidence from job vacancy data. In: Economics Letters, Jg. 250. DOI:10.1016/j.econlet.2025.112294

Abstract

"This paper examines the relationship between digital skills demand and posted wages in the UK using novel vacancy data. Digital skills — classified into basic, intermediate, and advanced using an XGBoost model — are linked to significant wage premiums. Within occupations, they are associated with 5.8% higher wages, with advanced and intermediate skills increasing wages by up to 8.9% when listed in job postings. Each additional digital skill increases wages by 1%, rising to 1.6% for advanced and intermediate skills. Artificial intelligence (AI) and cybersecurity skills yield particularly high returns, increasing wages by 8.6%–9.7% when listed and by 4.8%–5.4% per additional skill." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))

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Gerold, Stefanie, Katarzyna Gruszka, Karin Sardadvar, Hendrik Theine & Anna Pillinger (2025): Outsourcing Domestic Work in the Crisis of Social Reproduction: Platform‐Mediated Cleaning and the Role of Clients. In: New Technology, Work and Employment, S. 1-12. DOI:10.1111/ntwe.70015

Abstract

"Amid the crisis of social reproduction, outsourcing domestic work has become increasingly appealing, with labour platforms offering new avenues to do so. This article explores the largely overlooked perspective of clients using platform-mediated cleaning services, focusing on Helpling in Germany. Drawing on a multi-method study, we examine clients’ motivations for hiring cleaners through platforms and their perceptions of working conditions. We also analyse interactions between clients and cleaners, and how these are shaped by the platform. Our findings suggest that platforms like Helpling are attractive because of their convenience and their promise of an allegedly legal alternative to informal arrangements. While some clients express concerns over precarious working conditions, others justify them through market logic or assumptions about cleaners’ backgrounds. The platform infrastructure helps mediate trust, yet personal relations between clients and cleaners limit the platform's strategy of delegating management and control mechanisms to clients." (Author's abstract, IAB-Doku) ((en))

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Gerpott, Fabiola H. & Stephan A. Jansen (2025): Die Arbeit. Wie wir sie mit KI neu erfinden … und was für uns übrig bleibt. Hamburg: brand eins books, 124 S.

Abstract

"Wie wird sich die Arbeitswelt im Zeitalter der künstlichen Intis zwischen dem Menschen und seinen neuen Maschinen – für andere Arbeit, andere Arbeitsteilungen, andere Führung und andere Bildung. Neben Studien aus der Wissenschaft bietet das Buch konkrete Handlungsempfehlungen für ein neues «Human Machine Resource Management», das nicht nur das Personalmanagement, sondern jeden von uns zu einer anregenderen und sinnstiftenderen Arbeit nutzen kann. Und es lädt dazu ein, an der Zukunft der Arbeit aktiv mitzuarbeiten. Zentrale Themen sind unter anderem die ethischen Implikationen, wenn Entscheidungen an Maschinen delegiert werden, die Auswirkungen auf die Diversität und Leistungsfähigkeit der Belegschaft sowie die Neugestaltung von Arbeitsräumen und HR-Prozessen." (Verlagsangaben, IAB-Doku)

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Giebel, Marek & Alexander Lammers (2025): The Impact of a New Workplace Technology on Employees. In: Oxford Bulletin of Economics and Statistics, Jg. 87, H. 5, S. 1003-1024. DOI:10.1111/obes.12674

Abstract

"How does the implementation of a new technology affect workers? Using detailed worker-level data for Germany, we analyse the impact of new technologies on non-monetary working conditions such as overtime, training and perceived labor intensity. We show that the strongest effects arise in the first year of their implementation. These effects diminish after the introduction period. We further provide evidence that the impact of technology adoption varies across diverse occupational and industrial contexts. Workers in occupations with a higher task substitution potential show stronger increases in overtime, training measures and labor intensity. Analyzing industry characteristics, we find that employees exposed to a new technology react more strongly in industries with higher business dynamics in terms of organisational capital and R&D investment. Extending these considerations to information and communication technology (ICT) usage, we show that new technologies exert stronger effects in industries with high investment in ICT equipment or low investment in software." (Author's abstract, IAB-Doku) ((en))

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Giering, Oliver & Stefan Kirchner (2025): Artificial intelligence and autonomy at work: empirical insights from Germany. In: Journal for labour market research, Jg. 59. DOI:10.1186/s12651-025-00401-5

Abstract

"Artificial intelligence (AI) is a prominent topic regarding the digitalisation of work and its diffusion is expected to radically change job quality. Overall, there exists a large discrepancy between discursive expectations and quantitative empirical evidence. In this article, we use a novel module from the German Socio-Economic Panel to examine the overall prevalence of AI at work, the determinants that increase the likelihood of AI use, and its association with autonomy. The results show that 38% of German workers use AI, and AI use is associated with the use of specific digital technologies. Workers in high-level, non-routine occupations are more likely to use AI, particularly in comparison to manual workers. Moreover, the association between AI and autonomy is merely superficial and cannot be properly evaluated without considering workplace preconditions." (Author's abstract, IAB-Doku) ((en))

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Giuliani, Giovanni Amerigo & Rebecca Paraciani (2025): Contextualizing inequalities in the gig economy: evidence from online cleaning platforms in five European cities. In: The international journal of sociology and social policy, S. 1-20. DOI:10.1108/ijssp-12-2024-0619

Abstract

"Purpose: This paper explores the impact of national contexts on the profile of workers in the gig economy, with a specific focus on online cleaning platforms. The study aims to understand how national contexts influence the gender and ethnic composition of workers on domestic cleaning platforms, examining the intersectional effects of gender and ethnicity in platform-based work. Design/methodology/approach: Focusing on the case of the Yoopies platform operating in five Western European cities – Berlin, Copenhagen, Paris, Rome and Stockholm – this exploratory research is based on an original dataset that combines platform-based data directly collected from Yoopies with national-level data provided by Eurostat. Hypotheses were tested using simple correlation analysis to assess cross-country differences. Findings: The study shows that national contexts play an important role in shaping the gender and ethnic composition of workers on online cleaning platforms. Specifically, it identifies how structural features of the offline labor market influence the gendering and racialization of these platforms, highlighting variations across countries. The research also finds evidence of intersectional effects, where gender and ethnicity intersect to shape the profile of platform workers. Originality/value: This paper contributes to the growing literature on domestic work in the digital platform economy by providing a comparative perspective on cross-country differences in the composition of the platform workforce. It highlights the importance of national offline labor market characteristics in contributing to shaping platform-mediated work and provides new insights into the intersectionality of gender, ethnicity, and work in the gig economy. The findings contribute to both platform economy research and labor market studies, offering implications for policy and future research on the dynamics of digital work." (Author's abstract, IAB-Doku, © Emerald Group) ((en))

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Giuntella, Osea, Johannes Konig & Luca Stella (2025): Artificial intelligence and the wellbeing of workers. In: Scientific Reports, Jg. 15, H. 1. DOI:10.1038/s41598-025-98241-3

Abstract

"This study explores the relationship between artificial intelligence (AI) and workers’ well-being and healthusing longitudinal survey data from Germany (2000–2020). Using a measure of occupational exposure to AI, we explore an event study design and a difference-in-differences approach to compare AI-exposed and non-exposed workers. Before AI became widely available, there is no evidence of differential pre­trends in workers’ well-being and health. We findno evidence of a sizeable negative impact of AI on workers’ well-being and mental health. If anything, there is evidence of an improvement in health status and health satisfaction, which may be explained by the decline in job physical intensity. Overall, our results are consistent with the lack of negative effects of AI on the labor markets." (Author's abstract, IAB-Doku) ((en))

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Gmyrek, Pawel, Christoph Lutz & Gemma Newlands (2025): A technological construction of society: Comparing GPT-4 and human respondents for occupational evaluation in the UK. In: BJIR, Jg. 63, H. 1, S. 180-208. DOI:10.1111/bjir.12840

Abstract

"Despite initial research about the biases and perceptions of large language models (LLMs), we lack evidence on how LLMs evaluate occupations, especially in comparison to human evaluators. In this paper, we present a systematic comparison of occupational evaluations by GPT-4 with those from an in-depth, high-quality and recent human respondents survey in the UK. Covering the full ISCO-08 occupational landscape, with 580 occupations and two distinct metrics (prestige and social value), our findings indicate that GPT-4 and human scores are highly correlated across all ISCO-08 major groups. At the same time, GPT-4 substantially under- or overestimates the occupational prestige and social value of many occupations, particularly for emerging digital and stigmatized or illicit occupations. Our analyses show both the potential and risk of using LLM-generated data for sociological and occupational research. We also discuss the policy implications of our findings for the integration of LLM tools into the world of work." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Gmyrek, Pawel, Janine Berg, Karol Kamiński, Filip Konopczyński, Agnieszka Ładna, Balint Nafradi, Konrad Rosłaniec & Marek Troszyński (2025): Generative AI and jobs. A refined global index of occupational exposure. (ILO working paper / International Labour Organization 140), Geneva, 72 S. DOI:10.54394/hetp0387

Abstract

"This study updates the ILO’s 2023 Global Index of Occupational Exposure to Generative AI (GenAI), incorporating recent advances in the technology and increasing user familiarity with GenAI tools. Using a representative sample from the 29,753 tasks in the Polish occupational classification system and a survey of 1,640 people employed in each 1-digit ISCO-08 groups, we collect 52,558 data points regarding perceive potential of automation for 2,861 tasks. We then compare this input with a survey and several rounds of Delphi-style discussions among a smaller group of international experts. Based on this process, we create a repository of knowledge about task automation that goes beyond national specificities and use it to develop an AI assistant able to predict scores for tasks in the technical documentation of ISCO-08. Our 2025 scores are presented in a revised framework of four progressively increasing exposure gradients, with a new set of global estimates of employment shares exposed to GenAI. Clerical occupations continue to have the highest exposure levels. Additionally, some strongly digitized occupations have increased exposure, highlighting the expanding abilities of GenAI regarding specialized tasks in professional and technical roles. Globally, one in four workers are in an occupation with some GenAI exposure. 3.3% of global employment falls into the highest exposure category, albeit with significant differences between female (4.7%) and male employment (2.4%). These differences increase with countries’ income (9.6% female vs 3.5% male in Gradient 4in HICs), and so does the overall exposure (11% of total employment in LICs vs 34% in HICs). As most occupations consist of tasks that require human input, transformation of jobs is the most likely impact of GenAI. Linking our refined index with national micro data enables precise projections of such transformations, offering a foundation for social dialogue and targeted policy responses to manage the transition." (Author's abstract, IAB-Doku) ((en))

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Golboyz, Mark (2025): Governing the Digital Transition: The Moderating Effect of Unemployment Benefits on Technology‐Induced Employment Outcomes. In: Social Inclusion, Jg. 13. DOI:10.17645/si.10114

Abstract

"The digital transition shapes work in numerous ways. For instance, by affecting employment structures. To ensure that the digital transition results in better employment opportunities in terms of socio-economic status, labor markets have to be guided appropriately. The European Pillar of Social Rights can be the political framework to foster access to employment and tackle inequalities that result from the digital transition. Current research primarily examines scenarios of occupational upgrading and employment polarisation. In the empirical literature, there is no consensus on which of these developments prevail. Findings vary between countries and across different study periods. Accordingly, this article provides a theoretical explanation for the conditions under which occupational upgrading and employment polarization become more likely. Further, this article examines how the use of information and communication technology (ICT) capital in the production of goods and services affects the socio-economic status of individuals and, more importantly, whether unemployment benefits moderate this effect. Methodologically, the article uses multilevel maximum likelihood regression models with an empirical focus on 12 European countries and 19 industries. The analysis is based on data from the European Labour Force Survey (EU-LFS), the European Union Level Analysis of Capital, Labour, Energy, Materials, and Service Inputs (EU-KLEMS) research project, and the Comparative Welfare Entitlements Project (CWEP). The results of the article indicate that generous unemployment benefits are associated with occupational upgrading. This implies that educational and vocational labor market policies need to be developed to prevent the under-skilled from being left behind and to enable these groups to benefit from the digital transition. Consequently, it is not only the extent to which work involves routine tasks or the skills of workers that determine how technological change affects employment, but also social rights shape employment through unemployment benefits." (Author's abstract, IAB-Doku) ((en))

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Greenan, Nathalie, Dario Guarascio & Jelena Reljic (2025): AI and the labour market: opening the black box. In: Eurasian business review, Jg. 15, H. 4, S. 925-951. DOI:10.1007/s40821-025-00324-8

Abstract

"This work aims at discussing some of the main (open) questions about the labour impact of AI technologies. First, we provide an in-depth literature review focusing on concepts and measurement approaches and distinguishing between up (invention and knowledge creation), mid (technological innovation and development) and downstream (adoption and diffusion) components of the AI value chain. Second, we summarise the six articles included in the Special Issue ‘AI and labor markets: opening the black box’, distinguishing between contributions focusing on AI exposure, occupations and skill demand; the relationship between AI and automation technologies and their impact on income distribution; and, finally, the effect on organisational structures, management practices, and power dynamics within workplaces. Our analysis emphasises that AI’s employment effects are neither predetermined nor uniform, but shaped by implementation contexts, organisational choices, and institutional frameworks. We find that heterogeneity matters at multiple levels—across countries, sectors, firms, and demographic groups—challenging deterministic narratives and highlighting the need for adaptive policy responses that recognise these asymmetries." (Author's abstract, IAB-Doku) ((en))

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Greenan, Nathalie & Silvia Napolitano (2025): Does the Technological Transformation of Firms Go Along With More Employee Control Over Working Time? Empirical Findings From an EU-Wide Combined Dataset. In: Review of Political Economy, Jg. 37, H. 2, S. 500-522. DOI:10.1080/09538259.2024.2445096

Abstract

"We investigate the links between the technological transformation of firms and employee control over working time. We conduct EU-wide analysis at the meso-level by relating information from the European Company Survey 2019 (Eurofound and Cedefop) with the Labour Force Survey ad hoc module 2019 (Eurostat). This dataset allows analysing the technological transformation of firms as a relationship between three types of investments (in R&D, digital technologies and learning capacity of the organisation) that spur innovation outputs. We then study the consequences of the technological transformation on the spread of unfavourable working time arrangements, distinguishing between individual and organisation-oriented arrangements. Our model considers the direct effects of investments in Digital technologies adoption and use and Learning capacity of the organisation and the mediating role of firms' innovation strategies. Results indicate that the Learning capacity of the organisation is directly associated with more individual-oriented working time flexibility, but entails higher organisation-oriented working time flexibility. The effect of Digital technologies adoption and use depends instead on firms' innovation strategy: product innovation leads to more employee control over working time, while marketing innovation has the opposite outcome. Process and organisational innovations yield mixed consequences buffering employees from organisation-oriented working time flexibility in more time-constrained work environments." (Author's abstract, IAB-Doku) ((en))

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Griesbach, Kathleen (2025): Space and Inequality in Precarious Work: Thinking With and Beyond Platforms. In: Sociology Compass, Jg. 19, H. 3. DOI:10.1111/soc4.70026

Abstract

"Platform-based gig work illustrates a broader erosion of the spatial boundaries of work. While geographers have long theorized space as an integral part of capitalist work processes and social life, sociological research has often treated space as a backdrop for work processes rather than an active process shaping the social world, contemporary work, inequality, and resistance. However, important work in urban and rural sociology emphasizes the central role place plays in social life and inequality. This review synthesizes insights on space, place, and inequality and identifies key spatial continuities between platform labor and other forms of precarious work. I find common throughlines across disciplines: the intertwining of space, place, and social relations and the relevance of space and place for understanding inequality. Next, I relate spatial theories of capitalist development to contemporary precarious work. Finally, I suggest 3 promising avenues for incorporating space into research on contemporary work and inequality today: analyzing how existing inequalities intersect with the spatial features of new and enduring work structures; examining how contemporary work processes are reshaping rural and urban geographies; and identifying the spatial practices of contemporary organizing and resistance." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Guarascio, Dario, Alessandro Piccirillo & Jelena Reljic (2025): Robots vs. Workers: Evidence From a Meta‐Analysis. In: Journal of Economic Surveys, Jg. 39, H. 5, S. 2254-2271. DOI:10.1111/joes.12699

Abstract

"This study conducts a meta-analysis to assess the effects of robotization on employment and wages, synthesizing the evidence from 33 studies (644 estimates) on employment and a subset of 19 studies (195 estimates) on wages. The results challenge the alarmist narrative about the risk of widespread technological unemployment, suggesting that the overall relationship between robotization and employment or wages is minimal. However, the effects are far from uniform, with adverse outcomes observed in specific contexts, such as the United States, manufacturing sectors, and middle-skilled occupations. The analysis also identifies a publication bias favoring negative wage effects, though correcting for this bias confirms the negligible impact of robotization." (Author's abstract, IAB-Doku) ((en))

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Guarascio, Dario, Jelena Reljic & Roman Stöllinger (2025): Diverging paths: AI exposure and employment across European regions. In: Structural Change and Economic Dynamics, Jg. 73, S. 11-24. DOI:10.1016/j.strueco.2024.12.010

Abstract

"This study explores exposure to artificial intelligence (AI) technologies and employment patterns in Europe. First, we provide a thorough mapping of European regions focusing on the structural factors—such as sectoral specialisation, R&D capacity, productivity and workforce skills—that may shape diffusion as well as economic and employment effects of AI. To capture these differences, we conduct a cluster analysis which group EU regions in four distinct clusters: high-tech service and capital centres, advanced manufacturing core, southern and eastern periphery. We then discuss potential employment implications of AI in these regions, arguing that while regions with strong innovation systems may experience employment gains as AI complements existing capabilities and production systems, others are likely to face structural barriers that could eventually exacerbate regional disparities in the EU, with peripheral areas losing further ground." (Author's abstract, IAB-Doku, © 2024 The Author(s). Published by Elsevier B.V.) ((en))

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Guarascio, Dario & Jelena Reljic (2025): AI and employment in Europe. In: Economics Letters, Jg. 247. DOI:10.1016/j.econlet.2025.112183

Abstract

"This paper contributes to the growing research on AI's labor market impact by presenting novel evidence on the heterogeneous employment effects of AI across EU countries from 2012 to 2022. While concerns persist about AI's disruptive potential, our findings show that occupations more exposed to AI technologies experience stronger employment growth, all else being equal. However, these effects are not uniform across the EU. Positive employment outcomes are concentrated in Innovation Leaders (Belgium, Denmark, Finland, the Netherlands and Sweden) and Strong Innovators (Austria, Cyprus, France, Germany, Ireland and Luxembourg), emphasizing the context-dependent nature of AI's impact. These findings reflect the uneven distribution of innovation capabilities, with a country's innovation system and ‘absorptive capacity’ playing a crucial role in fully harnessing AI's potential for employment (and economic) growth. Ultimately, this research challenges the notion of AI as universally beneficial or harmful, highlighting its asymmetric effects across countries and occupations." (Author's abstract, IAB-Doku, © 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.) ((en))

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Guo, Ya, Sizhan Cui, Zhuofei Lu & Senhu Wang (2025): Dependence and Precarity in the Gig Economy: A Longitudinal Analysis of Platform Work and Mental Distress. In: The British journal of sociology, Jg. 76, H. 5, S. 1169-1187. DOI:10.1111/1468-4446.70028

Abstract

"While there is a growing body of literature examining platform dependence and its implications for mental health, much of the research has focused on gig workers with small sample sizes. The lack of large-scale quantitative research, particularly using longitudinal representative data, limits a comprehensive understanding of the dynamic relationship between platform dependence and mental distress. This study uses nationally representative data from the UK and fixed effects models to explore the heterogeneity of gig work, specifically examining differences in mental distress between high-dependence workers (those solely engaged in gig work) and low-dependence workers (those also employed in other jobs). The findings reveal that high-dependence gig workers have greater mental distress compared to low-dependence and full-time workers, with their mental well-being similar to those with no paid work. Low-dependence gig workers have lower mental distress than those without paid work. Financial precarity and loneliness partly explain these differences, with the impact stronger for highly educated high-dependence workers and less educated low-dependence workers. These findings highlight the significance of recognizing the heterogeneity of gig work in addressing future well-being challenges in a post-pandemic economy, as well as broadening the scope of the latent deprivation model to encompass the unique dynamics of gig work." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Hacker, Winfried (2025): Auswirkungen von KI auf die Nutzer: Erhalten und Fördern der menschlichen Intelligenz bei zunehmendem Einsatz künstlicher Intelligenz - Wozu? Wie? (baua: Fokus), Dortmund, 6 S. DOI:10.21934/baua:fokus20251218

Abstract

"Die Entwicklung der KI verändert die Anforderungen an die menschliche Intelligenz: Denkleistungen können überflüssig werden. Dadurch kann eine arbeitsbedingte Dequalifizierung der Arbeitenden entstehen, denen jedoch die Kontrolle und Korrektur der KI-Ergebnisse obliegt, wofür diese Denkleistungen benötigt werden. Auswege sind die "Zusammenarbeit" von KI und Mensch sowie insbesondere einfache Maßnahmen zum Erhalten der Denkfähigkeit im Arbeitsprozess, die dargestellt werden." (Autorenreferat, IAB-Doku)

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Hall, Anja & Ana Santiago Vela (2025): Arbeiten mit Künstlicher Intelligenz, aber auch mit Köpfchen. Anforderungen an Future Skills in der Erwerbsarbeit. In: Berufsbildung in Wissenschaft und Praxis H. 4, S. 21-25.

Abstract

"Künstliche Intelligenz (KI) verändert nicht nur, was wir arbeiten, sondern auch wie. Auf Basis der BIBB/BAuA-Erwerbstätigenbefragung 2024 zeigt der Beitrag die aktuelle Verbreitung von KI auf dem Arbeitsmarkt. KI wird vor allem in kognitiv-analytischen und interaktiven Nichtroutinetätigkeiten genutzt und geht mit Anforderungen an Future Skills wie Probleme lösen, Wissenslücken schließen, kreativ sein oder überzeugen einher. Damit rücken im Kontext von KI neben fachlichen Anforderungen auch überfachliche Kompetenzen stärker in den Fokus. Berufliche Handlungskompetenz ist daher weiterhin gezielt zu fördern." (Autorenreferat, IAB-Doku)

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Hammermann, Andrea & Louisa Kürten (2025): Generative KI: Schritt halten durch gezielte Kompetenzentwicklung. (IW-Kurzberichte / Institut der Deutschen Wirtschaft Köln 2025,24), Köln, 3 S.

Abstract

"Der Einsatz von generativer Künstlicher Intelligenz (KI) transformiert die Arbeitswelt in einem rasanten Tempo. Eine wichtige Säule zur Ausschöpfung der möglichen KI-Potenziale sind das Wissen und die Anwendungskompetenz von Beschäftigten. Weiterbildung und das Lernen am Arbeitsplatz gewinnen vor diesem Hintergrund an Bedeutung." (Autorenreferat, IAB-Doku)

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Hampole, Menaka, Dimitris Papanikolaou, Lawrence D. W. Schmidt & Bryan Seegmiller (2025): Artificial Intelligence and the Labor Market. (NBER working paper / National Bureau of Economic Research 33509), Cambridge, Mass, 58 S.

Abstract

"We leverage recent advances in NLP to construct measures of workers' task exposure to AI and machine learning technologies over the 2010 to 2023 period that vary across firms and time. Using a theoretical framework that allows for a labor-saving technology to affect worker productivity both directly and indirectly, we show that the impact on wage earnings and employment can be summarized by two statistics. First, labor demand decreases in the average exposure of workers' tasks to AI technologies; second, holding the average exposure constant, labor demand increases in the dispersion of task exposures to AI, as workers shift effort to tasks that are not displaced by AI. Exploiting exogenous variation in our measures based on pre-existing hiring practices across firms, we find empirical support for these predictions, together with a lower demand for skills affected by AI. Overall, we find muted effects of AI on employment due to offsetting effects: highly-exposed occupations experience relatively lower demand compared to less exposed occupations, but the resulting increase in firm productivity increases overall employment across all occupations." (Author's abstract, IAB-Doku) ((en))

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Hausman, Naomi, Oren Rigbi & Sarit Weisburd (2025): Generative AI's Impact on Student Achievement and Implications for Worker Productivity. (CESifo working paper 11843), München, 39 S.

Abstract

"Student use of Artificial Intelligence (AI) in higher education is reshaping learning and redefining the skills of future workers. Using student-course data from a top Israeli university, we examine the impact of generative AI tools on academic performance. Comparisons across more and less AI-compatible courses before and after ChatGPT's introduction show that AI availability raises grades, especially for lower-performing students, and compresses the grade distribution, eroding the signal value of grades for employers. Evidence suggests gains in AI-specific human capital but possible losses in traditional human capital, highlighting benefits and costs AI may impose on future workforce productivity." (Author's abstract, IAB-Doku) ((en))

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Herzberg-Druker, Efrat (2025): Occupational gender segregation: what can we learn from computer use trends? In: Social forces, S. 1-22. DOI:10.1093/sf/soaf180

Abstract

"This study posits to an intricate interrelation between changes in occupational gender segregation (OGS) and the rise in computer use in the workplace in the United States. I posit that two contrasting mechanisms underpin this relation. Firstly, computerization has contributed to a more balanced gender distribution in certain professions, previously dominated by men, due to a decrease in physical tasks in occupations, thereby reducing OGS. Conversely, in other occupations, heightened computer use has increased Science, Technology, Engineering, and Mathematics (STEM) knowledge requirements, thus restricting women’s integration and reproducing OGS.My empirical analysis, utilizing fixed-effects regression models, lagged models, ordinary least squares (OLS) models, and mediation analysis on a comprehensive dataset of the United States Census, American Community Survey, and Occupational Information Network data, confirms a significant association between computer use and OGS. The physical attributes of occupations and their required STEM knowledge components emerge as critical factors. These contradictory mechanisms—one involving reduced physical demands and the other increased required STEM knowledge—ultimately maintain a stable OGS level." (Author's abstract, IAB-Doku) ((en))

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Heyer, Philipp, Kathrin Weis, Sabine Mohr & Wiebke Schmitz (2025): Alter(n) im Betrieb: Stereotype Altersbilder, Fachkräftemangel und digitale Transformation. (BIBB-Report 2025,05), Leverkusen: Verlag Barbara Budrich, 16 S.

Abstract

"Against the backdrop of demographic change, age-appropriate human resources policies are becoming increasingly important. Nevertheless, negative age stereotypes continue to prevail in many firms, hindering the recruitment and further training of older employees – and thus leaving existing skilled labor potential untapped. Based on current data from the establishment survey “BIBB Establishment Panel on Training andCompetence Development,” this BIBB Report analyzes stereotypical images of age in firms as well as company characteristics that promote the employment of older people. Particular attention is given to the role of digital technologies. The results show that the perceptions of older employees vary depending on the industry, firm size, and use of technology. A positive perception is associated with higher employment rates of older people. However, older employees are less strongly represented in firms with above-average use of digital technologies. Based on these findings, it is recommended to counteract age stereotypes, provide targeted further training for older employees, and actively involve them in digital work processes. An age-appropriate human resources policy not only strengthens the supply of skilled workers, but also diversity and, ultimately, the productivity of firms." (Author's abstract, IAB-Doku) ((en))

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Humlum, Anders & Emilie Vestergaard (2025): Large Language Models, Small Labor Market Effects. (BFI Working Papers / University of Chicago, Becker Friedman Institute for Research in Economics 2025,56), Chicago, 64 S. DOI:10.2139/ssrn.5219933

Abstract

"We examine the labor market effects of AI chatbots using two large-scale adoption surveys (late 2023 and 2024) covering 11 exposed occupations (25,000 workers, 7,000 workplaces), linked to matched employer-employee data in Denmark. AI chatbots are now widespread —most employers encourage their use, many deploy in-house models, andtraining initiatives are common. These firm-led investments boost adoption, narrow demographic gaps in take-up, enhance workplace utility, and create new job tasks. Yet, despite substantial investments, economic impacts remain minimal. Using difference-in-differences and employer policies as quasi-experimental variation, we estimate precise zeros: AI chatbots have had no significant impact on earnings or recorded hours in any occupation, with confidence intervals ruling out effects larger than 1%. Modest productivity gains (average time savings of 3%), combined with weak wage pass-through, help explain these limited labor market effects. Our findings challenge narratives of imminent labor market transformation due to Generative AI." (Author's abstract, IAB-Doku) ((en))

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Högemann, Malte, Laura Hein, Jan-Oliver Britsche & Oliver Thomas (2025): Technostress and generative AI in the workplace: a qualitative analysis of young professionals. In: Frontiers in artificial intelligence, Jg. 8. DOI:10.3389/frai.2025.1728881

Abstract

"Generative artificial intelligence (GenAI) is rapidly diffusing into the workplace and is expected to substantially reshape roles, workflows, and skill requirements, particularly for young professionals as early adopters who are highly exposed to these tools. While GenAI is widely regarded as a means to increase productivity, its adoption may simultaneously introduce new challenges, including various forms of technostress. Drawing on 15 semi-structured interviews with young professionals in research and development (R&D), IT, finance, and marketing in organizations piloting or using GenAI, we conducted a structured qualitative content analysis guided by established technostress dimensions. Our findings indicate that classic technostress dimensions remain relevant but manifest differently across sectors and contexts. Moreover, additional GenAI-specific stressors emerged, such as regulatory and compliance ambiguity, data protection and copyright concerns, perceived dependency, potential skill degradation, doubts about the reliability and controllability of AI outputs, and a shift towards more monitoring and conceptual work. At the same time, participants reported techno-eustress in the form of efficiency gains, learning opportunities, and enhanced intrinsic motivation. Overall, the study extends existing technostress frameworks and underscores the importance of AI literacy, clear organizational governance, and supportive work design to mitigate negative technostress while enabling the productive use of GenAI." (Author's abstract, IAB-Doku) ((en))

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Ide, Enrique & Eduard Talamas (2025): The Impact of AI on Global Knowledge Work. (CEPR discussion paper / Centre for Economic Policy Research 20801), London, 34 S.

Abstract

"Artificial Intelligence (AI) is reshaping offshoring and globalization by automating knowledge work and altering trade patterns. We analyze this transformation in a two-region world where firms structure work 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, while the Emerging Economy focuses on routine knowledge work. We model AI as a technology that converts compute into autonomous “AI agents,” which serve as perfect substitutes for humans with a given level of knowledge. Reflecting the concentration of AI infrastructure in advanced economies, we assume that all compute is located in the Advanced Economy. We show that basic AI reduces the Advanced Economy’s net exports of problem-solving services, potentially reversing pre-AI trade patterns. In contrast, sophisticated AI increases the Advanced Economy’s net exports of problem-solving services, reinforcing existing trade patterns. We also examine the effects of restricting AI autonomy, finding that a global restriction redistributes AI’s benefits toward lower-skilled workers, while a regional restriction - such as banning autonomous AI in the Emerging Economy - does little to benefit lower-skilled workers and harms the most knowledgeable individuals in that region. Our results underscore the need for a coordinated global approach to AI regulation." (Author's abstract, IAB-Doku) ((en))

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Jaccoud, Florencia (2025): Robots & AI exposure and wage inequality: a within occupation approach. In: Eurasian business review, Jg. 15, H. 4, S. 1035-1090. DOI:10.1007/s40821-025-00306-w

Abstract

"This paper examines the linkages between occupational exposure to recent automation technologies and inequality across 19 European countries. Using data from the European Union Structure of Earnings Survey (EU-SES), a fixed-effects model is employed to assess the association between occupational exposure to artificial intelligence (AI) and to industrial robots–two distinct forms of automation–and within-occupation wage inequality. The analysis reveals that occupations with higher exposure to robots tend to have lower wage inequality, particularly among workers in the lower half of the wage distribution. In contrast, occupations more exposed to AI exhibit greater wage dispersion, especially at the top of the wage distribution. We argue that this disparity arises from differences in how each technology complements individual worker abilities: robot-related tasks often complement routine physical activities, while AI-related tasks tend to amplify the productivity of high-skilled, cognitively intensive work." (Author's abstract, IAB-Doku) ((en))

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Jacobs, Arthur & Freddy Heylen (2025): Demographic change, secular stagnation, and inequality: automation as a blessing? In: Journal of demographic economics, Jg. 91, H. 4, S. 508-548. DOI:10.1017/dem.2024.10

Abstract

"We study whether the increased adoption of available automation technologies allows economies to avoid the negative effect of aging on per capita output. We develop a quantitative theory in which firms choose to which extent they automate in response to a declining workforce and rising old-age dependency. An important element in our model is the integration of two capital types: automation capital that acts as a substitute to human labor, and traditional capital that is a complement to labor. Empirically, our model's predictions largely match data regarding automation (robotization) density across OECD countries. Simulating the model, we find that aging-induced automation only partially compensates the negative growth effect of aging in the absence of technical progress in automation technology. One reason is that automated tasks are no perfect substitutes for non-automated tasks. A second reason is that automation raises the interest rate and thus inhibits positive behavioral reactions to aging (later retirement and investment in human capital). Moreover, increased automation generates a falling net labor share of income and rising welfare inequality. We evaluate alternative policy responses to cope with this inequality." (Author's abstract, IAB-Doku) ((en))

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Janssen, Simon, Christina Langer, Markus Nagler, Nicholas Rounding, Michael Stops & Simon Wiederhold (2025): Wie lässt sich die Nachfrage nach KI- und anderen Kompetenzen auf dem Arbeitsmarkt besser messen? (ROA external reports / Researchcentrum voor Onderwijs en Arbeidsmarkt (Maastricht) 10 ai:conomics policybrief), Maastricht, 6 S.

Abstract

"Eine umfangreiche Forschungsliteratur zeigt, dass der technologische Wandel erhebliche Auswirkungen auf die Arbeitsmärkte hat, da moderne digitale Technologien die Nachfrage nach bestimmten Kompetenzen verändern. Zum einen können neue Technologien einige menschliche Tätigkeiten ersetzen. Zum anderen Seite können sie neue Tätigkeiten schaffen oder ergänzen (Acemoglu et al., 2015; Acemoglu & Restrepo, 2018, 2019, 2020). Mit der starken Verbreitung Künstlicher Intelligenz in den letzten Jahren gewinnen bestimmte Fragen in der öffentlichen Diskussion und der Forschung zunehmend an Bedeutung: Wächst die Arbeitsnachfrage nach KI-Kompetenzen auch auf dem deutschen Arbeitsmarkt? Führt die steigende Nachfrage nach KI-Kompetenzen dazu, dass andere Kompetenzen – bei niedrig-, mittel- und hochqualifizierten Arbeitskräften – weniger gefragt sind? Ziel dieses Forschungsprojekts ist es, eine belastbare Datengrundlage zu schaffen, um solche Fragen in Zukunft fundierter beantworten zu können. Die Entwicklungen bei generativer Künstlicher Intelligenz, insbesondere von Tools wie ChatGPT, hat die Diskussion über die Auswirkungen von KI auf den Arbeitsmarkt sowohl in der Wissenschaft als auch in der öffentlichen Debatte und in der Politik deutlich verstärkt. Während Computer und Software die Arbeitswelt durch die präzisere und effizientere Ausführung routinemäßiger Aufgaben verändert haben, können moderne KI-Systeme nun komplexe, nichtroutinemäßige Aufgaben übernehmen, ohne auf detaillierte Anweisungen oder wiederholende Regeln angewiesen zu sein (Brynjolfsson et al., 2025). Infolgedessen sehen viele das produktive Potenzial dieser neuen Technologie optimistisch. Andere hingegen befürchten, dass KI die Arbeitsmärkte disruptiv verändern könnte." (Autorenreferat, IAB-Doku)

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Janssen, Simon, Christina Langer, Markus Nagler, Nicholas Rounding, Michael Stops & Simon Wiederhold (2025): How can we better measure the demand for AI and other skills on the labour market? (ROA external reports / Researchcentrum voor Onderwijs en Arbeidsmarkt (Maastricht) 10 ai:conomics policybrief), Maastricht, 5 S.

Abstract

"A large body of research literature shows that technological change has a significant impact on labour markets, as modern digital technologies are changing the demand for certain skills. On the one hand, new technologies can replace some human activities. On the other hand, they can create or complement new activities (Acemoglu et al., 2015; Acemoglu & Restrepo, 2018, 2019, 2020). With the proliferation of artificial intelligence (AI) in recent years, certain questions are becoming increasingly important in public debate and research: Is the demand for AI skills also growing on the German labour market? Does the increasing demand for AI skills mean that other skills - among low, medium and highly qualified workers - are less in demand? The aim of this research project is to create a reliable data basis in order to be able to answer such questions in a more informed way in the future. Developments in generative AI, particularly tools such as ChatGPT, have significantly intensified the discussion about the impact of AI on the labour market, both in academia and in public debate and policy. While computers and software have transformed the world of work by performing routine tasks more precisely and efficiently, modern AI systems can now take on complex, non-routine tasks without relying on detailed instructions or repetitive rules (Brynjolfsson et al., 2025). As a result, many are optimistic about the productive potential of this new technology. Others, however, fear that AI could disrupt labour markets. In the course of the intensive scientific and public debate on AI, there is a growing body of literature that deals with the effects of AI on labour markets. These initially focus on specific occupations such as call centre workers (Brynjolfsson et al., 2025, Dijksman et al., 2024), consultants (Dell’ et al., 2023), writers or developers (Peng et al., 2023). However, a major challenge is to measure how the demand for and supply of skills has changed in the wake of the emergence of AI." (Autorenreferat, IAB-Doku)

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Janssen, Simon, Michael Stops, Sanne Steens, Pelin Özgül, Nicholas Rounding, Sander Dijksman, Raymond Montizaan, Mark Levels, Didier Fourage, Danique Eijkenboom, Evie Graus & Marie-Christine Fregin (2025): Artificial intelligence in the workplace: insights into the transformation of customer services. In: IAB-Forum H. 22.04.2025, 2025-04-22. DOI:10.48720/IAB.FOO.20250422.01

Abstract

"How does the use of artificial intelligence in training affect employee productivity? These and other questions were investigated as part of the long-term research project “ai:conomics” using company data from various large European companies. Initial results suggest that AI can have a positive impact on employee productivity, especially for new employees." (Author's abstract, IAB-Doku) ((en))

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Khabirpour, Neysan, Lorenzo Pelizzari, Jan Limbers, Markus Hoch, Philipp Kreuzer, Matteo Richiardi, Patryk Bronka & Costanza Pagnini (2025): Overlapping crises (re)shaping the future of regional labour markets [OVERLAP]. Main Report. Luxembourg: ESPON 2030, 101 S.

Abstract

"Europe’s labour market is entering a decade in which structural forces converge and pull unevenly on every region. First, the demographic change is steadily thinning the labour supply: by 2050, the EU’s labour force is set to decrease by 35 million people. (Secondly) This demographic transition comes at a time when Member States are increasing their efforts to achieve the decarbonization targets, and (thirdly) when they are ramping up investments to digitalise the economy. While the digital transition is accelerating demand for specialised skills faster than workers can acquire them, the green transition suggests both disruption and expansion. To deliver the REPowerEU targets, the Commission estimates that more than 3.5 million additional jobs will be needed by 2030. Explained very shortly, these interacting factors may amplify long-standing territorial disparities in age structure, industrial fabric and human-capital endowment. Understanding where labour will transform and where new demand will arise is therefore indispensable. It is precisely this spatial intelligence that the OVERLAP project supplies—by charting the possible employment trajectories of every NUTS-3 labour market – for the 2035 perspective - under a varied set of assumptions, driven by policy or shock. This is done within a scenario-driven exercise, covering ageing, green ambition and digital diffusion. In doing so, as a forward-looking exercise, the study equips policymakers with the granular evidence needed to anticipate potential shortages, target up- and reskilling investments, and steer and match transition funding to address local needs and the regions that need it most. The study starts from two overarching objectives: Compile a granular portrait of Europe’s regional labour markets by tracing demographic dynamics and their (possible) implications for employment trends, at NUTS-3 level, out to 2035. Gauge how major drivers—including population change and the twin digital-green transition—may reshape labour demand under a range of forward-looking (possible) scenarios, out to 2035. From these aims, flow the main guiding research questions: which territories and sectors are set to gain or lose employment as ageing, automation and decarbonisation unfold simultaneously? And what policy mixes can cushion vulnerable regions while helping them capture new growth niches? Addressing these questions across the ESPON space—i.e. all EU Member States plus Iceland, Liechtenstein, Norway and Switzerland—requires a geography-sensitive lens; hence results are mapped down to individual NUTS-3 regions. To deliver evidence at that resolution, the project combined a dual analytical architecture. Quantify and regionalise macro-trends: the top-down stream employs the DINOS dynamic input-output model (developed by PROGNOS) to translate demographic, technological and climate-policy shocks into sectoral employment and wage shifts, then regionalises these outputs to the full NUTS-3 grid. The macro-level modelling strategy begins with national economic aggregates, traces broad structural trends across industries, and subsequently disaggregates the resulting labour-market effects to individual regions. By working from the “whole economy” downward, this framework captures systemic interactions—such as supply-chain spill-overs—beyond the reach of purely regional models. Provide a micro-analytical perspective: in parallel, the bottom-up stream extends the SimPaths dynamic microsimulation platform—already validated for the United Kingdom as a baseline —to Greece, Hungary, Italy and, enriching the macro picture with individual life-course trajectories. This novel, regional, micro-analytical framework sheds additional light on the distributional impact of the ongoing economic and social transformations, going beyond the broad picture and simplified assumptions that had to be made in the top-down approach (macro-analyses). The dynamic framework integrates a defining feature in every simulated period: inputs from a static tax-benefit calculator (EURO-MOD), hence allowing to study to what extent tax and benefit systems can smooth out transitional dynamics. However, it is important to highlight from the onset, that this study should not be perceived as a crystal globe, as it does not cover all possible shocks or situations, but acts upon the accumulated knowledge, in order to provide some modelled scenarios that are aimed at informing and opening the forward-looking strategies, with a pre-emptive component." (Author's abstract, IAB-Doku) ((en))

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Klaus, Dominik, Maddalena Lamura, Marcel Bilger & Barbara Haas (2025): Support and employment preferences in online platform work. A cluster analysis of German-speaking workers. In: International Journal of Social Welfare, Jg. 34, H. 1, S. e12659. DOI:10.1111/ijsw.12659

Abstract

"Online platform work is an emerging field of non-standard employment. Up to now, there has been little knowledge of the perspective of online platform workers on social protection and regulation. We provide quantitative data (n = 1727) on their needs for support and on their employment status preferences. Given the heterogeneity of German-speaking online platform workers, we have conducted a cluster analysis to group workers according to task length, hourly wage, working hours and experience on online platforms. Most of the respondents are solo-self-employed and hybrid workers. They prefer support instruments that improve their skills and income over those that aim to strengthen their rights. The majority of platform workers are in favour of working outside of platforms. The study also shows that despite the low dependence on platform income, the actual poverty risk is relatively high." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Klonek, Florian & Sharon Parker (2025): Does AI at Work Increase Stress? Text Mining Social Media About Human–AI Team Processes and AI Control. In: Journal of organizational behavior, S. 1-15. DOI:10.1002/job.70000

Abstract

"With rising use of artificial intelligence (AI) in organizations, alongside increasing mental health issues, we seek to understand how AI use affects human stress. Drawing on the automation–augmentation perspective, we propose that AI control over decision-making thwarts human autonomy and thus contributes to stress. Drawing on models of teamwork and augmentation, we expect that human–AI team processes (i.e., transition, action, and interpersonal processes) help people meet their goals and reduce stress. Finally, we argue that human–AI team processes provide an important social resource, which buffers the stress-enhancing role of AI control. To test our hypotheses, we analyzed over 2700 tweets. Using a trained large language model, validated against human ratings, we indexed key measures. Results confirm that high AI control was associated with increased stress, whereas human–AI team processes were associated with decreased stress. In support of the moderation hypothesis, two human–AI team processes (action and interpersonal) helped further reduce the stress-enhancing effect of AI control. We discuss implications for work design theory and the importance of regulating levels of AI control to protect workers' mental health." (Author's abstract, IAB-Doku) ((en))

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Knappert, Lena, Boukje Cnossen & Renate Ortlieb (2025): Inequality Regimes in Coworking Spaces: How New Forms of Organising (Re)produce Inequalities. In: Work, Employment and Society, Jg. 39, H. 1, S. 43-63. DOI:10.1177/09500170241237188

Abstract

"Coworking is a rapidly growing worldwide phenomenon. While the coworking movement emphasizes equality and emancipation, there is little known about the extent to which coworking spaces as new forms of organizing live up to this ideal. This study examines inequality in coworking spaces in the Netherlands, employing Acker’s framework of inequality regimes. The findings highlight coworking-specific components of inequality regimes, in particular stereotyped assumptions regarding ‘ideal members’ that establish the bases of inequality, practices that produce inequality (e.g. through the commodification of community) and practices that perpetuate inequality (e.g. the denial of inequality). The study provides an update of Acker’s framework in the context of coworking and speaks, more broadly, to the growing body of literature on (in)equality in emerging organizational contexts." (Author's abstract, IAB-Doku) ((en))

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Koch, Christian & Michael Stops (2025): KI Navigator #10: Wie KI dem Arbeitsmarkt hilft. In: Heise online, 2025-03-14.

Abstract

"Stellenanzeigen können viel über den Wandel des Arbeitsmarkts verraten. Künstliche Intelligenz hilft dabei, diese Daten zu interpretieren."

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Kowalik, Zuzanna, Piotr Lewandowski, Tomasz Geodecki & Maciej Grodzicki (2025): Automation in shared service centres: Implications for skills and autonomy. In: The Economic and Labour Relations Review, Jg. 36, H. 2, S. 563-581. DOI:10.1017/elr.2025.10026

Abstract

"The offshoring-fueled growth of the Central and Eastern European business services sector gave rise to shared service centers (SSCs) – quasi-autonomous entities providing routine-intensive tasks for the central organization. The advent of technologies such as intelligent process automation, robotic process automation, and artificial intelligence jeopardises SSCs’ employment model, necessitating workers’ skills adaptation. The study challenges the deskilling hypothesis and reveals that automation in the Polish SSCs is conducive to upskilling and worker autonomy. Drawing on 31 in-depth interviews, we highlight the negotiated nature of automation processes shaped by interactions between headquarters, SSCs, and their workers. Workers actively participated in automation processes, eliminating the most mundane tasks. This resulted in upskilling, higher job satisfaction, and empowerment. Yet, this phenomenon heavily depends upon the fact that automation is triggered by labor shortages, which limit the expansion of SSCs. This situation encourages companies to leverage the specific expertise entrenched in their existing workforce. The study underscores the importance of fostering employee-driven automation and upskilling initiatives for overall job satisfaction and quality." (Author's abstract, IAB-Doku) ((en))

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Krzywdzinski, Martin, Daniel Schneiß & Andrea Sperling (2025): Between control and participation: The politics of algorithmic management. In: New Technology, Work and Employment, Jg. 40, H. 1, S. 60-80. DOI:10.1111/ntwe.12293

Abstract

"Understanding the role of human management is crucial for the debate over algorithmic management—to date limited to studies on the platform economy. This qualitative case study in logistics reconstructs the actor constellations (managers, engineers, data scientists and workers) and negotiation processes in different phases of algorithmic management. It offers two major contributions to the literature: (1) a process model distinguishing three phases: goal formation, data production and data analysis, which is used to analyse (2) the politics of algorithmic management in conventional workplaces, which differ significantly from platform companies. The article goes beyond surveillance to elucidate the role of the regulatory framework, various actors' knowledge contributions to the algorithmic management system, and the power relations resulting therefrom. While the managerial goals in the examined case were not oriented towards a surveillance regime, the outcome was nevertheless a centralisation of knowledge and disempowerment of workers." (Author's abstract, IAB-Doku) ((en))

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Kudoh, Noritaka & Hiroaki Miyamoto (2025): Robots, AI, and unemployment. In: Journal of Economic Dynamics and Control, Jg. 174. DOI:10.1016/j.jedc.2025.105069

Abstract

"Do robots and artificial intelligence (AI) cause joblessness? We develop a dynamic general equilibrium model with search-matching frictions. In our model, robots substitute routine human tasks, and AI substitutes abstract human tasks. We find a cutoff level for the elasticity of substitution between routine labor input and robots, above which an increase in robot productivity leads to increased unemployment. We examine a scenario in which AI-driven automation of abstract tasks transforms high-skilled workers into unskilled ones. A substantial productivity gain through AI is required to offset the output loss associated with this labor displacement." (Author's abstract, IAB-Doku, © 2025 The Author(s). Published by Elsevier B.V.) ((en))

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Kuhlmann, Martin, Britta Matthes & Stefan Theuer (2025): Das Produktionsmodell der deutschen Automobilindustrie auf dem Prüfstand. Arbeitsstrukturen und Arbeitsanforderungen in Montagewerken im Wandel? (SOFI-Impulspapier), Göttingen, 6 S.

Abstract

"Das in den 1980er-Jahren etablierte Produktionsmodell der deutschen Automobilhersteller lässt sich beschreiben als innovations- und exportorientierte Produktion qualitativ hochwertiger Produkte auf Basis qualifizierter Arbeit, guter Bezahlung und hoher Beschäftigungssicherheit sowie starken gewerkschaftlichen Interessenvertretungen. Politische Vorgaben, wie die Umstellung auf die Produktion von Elektroautos, veränderte Wettbewerbsbedingungen sowie die weiter voranschreitende Digitalisierung haben dazu geführt, dass dieses Produktionsmodell derzeit auf dem Prüfstand steht. Getrieben durch aufkommende Zweifel an der technologischen Überlegenheit deutscher Automobilhersteller und Nachfrageschwächen beim Übergang auf Elektromobilität ist die Unsicherheit in der Branche gegenwärtig groß. In einem laufenden Forschungsprojekt untersuchen wir, inwiefern sich durch die Produktion von Elektroautos und die fortschreitende Digitalisierung Arbeitsstrukturen und Arbeitsanforderungen in den Endmontagewerken der deutschen Automobilhersteller verändert haben und ob sich arbeitsbezogen ein Wandel des deutschen Produktionsmodells abzeichnet." (Autorenreferat, IAB-Doku)

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Kuhn, Sarah & Holger Seibert (2025): Digitalisierung der Arbeitswelt: Durch künstliche Intelligenz sind inzwischen auch viele Expertentätigkeiten ersetzbar. (IAB-Regional. Berichte und Analysen aus dem Regionalen Forschungsnetz. IAB Berlin-Brandenburg 01/2025), 34 S. DOI:10.48720/IAB.REBB.2501

Abstract

"Durch neue digitale Technologien verändert sich der deutsche Arbeitsmarkt. Dies gilt besonders für das Ausmaß, in dem Berufe aktuell potenziell durch den Einsatz von Computern oder computergesteuerten Maschinen ersetzbar sind, dem so genannten Substituierbarkeitspotenzial. Es beschreibt, welcher Anteil an Tätigkeiten in einem Beruf schon heute durch den Einsatz moderner Technologien ersetzt werden könnte. Nach wie vor ist zwar das Substituierbarkeitspotenzial bei den Helfer*innen- und Fachkraftberufen am höchsten. Am stärksten gestiegen ist das Potenzial jedoch bei den Expert*innenberufen (u. a. durch generative Künstliche Intelligenz). Besonders bei den IT- und naturwissenschaftlichen Dienstleistungsberufen sind hohe Zuwachsraten zwischen 2019 und 2022 zu verzeichnen. Der vorliegende Beitrag fokussiert sich auf den Arbeitsmarkt in Brandenburg und Berlin. Wichtig zu betonen ist, dass es hier um Potenziale technischer Ersetzbarkeit geht. Ob und inwiefern die technischen Möglichkeiten auch tatsächlich umgesetzt werden, steht nicht fest. Es kann Gründe geben, die gegen eine tatsächliche Substituierung sprechen, beispielsweise weil eine Umstellung zu komplex wäre oder ethische Bedenken dem entgegenstehen. Unstrittig ist jedoch, dass auf der einen Seite einige Tätigkeiten durch die Digitalisierung wegfallen bzw. automatisiert werden, andererseits aber auch neue Tätigkeiten und Berufe entstehen. Daher kann ein hohes Substituierungspotenzial als Indikator für einen Wandel der Arbeitswelt gesehen werden." (Autorenreferat, IAB-Doku)

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Kuhn, Sarah & Holger Seibert (2025): Digitale Ersetzbarkeit im stationären Einzelhandel und im Onlinehandel. Gastbeitrag. In: ArbeitGestalten Beratungsgesellschaft mbH (Hrsg.) (2025): Kassensturz. Daten, Fakten und Erfahrungen aus der Arbeitswelt des Berliner Einzelhandels, S. 29-31, 2025-09-30.

Abstract

"Diese Analyse zeigt, dass nicht alle Beschäftigten im stationären Einzelhandel und im Onlinehandel gleichermaßen von der digitalen Transformation betroffen sind bzw. sein werden. Wichtig zu betonen ist, dass es hier um Potenziale technischer Ersetzbarkeit geht. Ob und inwiefern die technischen Möglichkeiten auch tatsächlich umgesetzt werden, hängt von verschiedenen Faktoren ab. Es kann Gründe geben, die gegen eine tatsächliche Substituierung sprechen, beispielsweise weil eine Umstellung zu komplex wäre oder ethische Bedenken dem entgegenstehen. Unstrittig ist jedoch, dass auf der einen Seite einige Tätigkeiten durch die Digitalisierung wegfallen bzw. automatisiert werden, andererseits aber auch neue Tätigkeiten und Berufe entstehen. Daher kann ein hohes Substituierungspotenzial als Indikator für einen Wandel der Arbeitswelt gesehen werden." (Autorenreferat, IAB-Doku)

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Kunze, Florian, Carolina Opitz & Ann Sophie Lauterbach (2025): Konstanzer KI-Studie 2025: Die Nutzung von Künstlicher Intelligenz in der Arbeitswelt steigt, Ungleichheiten in der Wahrnehmung bleiben weiterhin bestehen. Ergebnisbericht Juli 2025. Konstanz: KOPS Universität Konstanz, 8 S.

Abstract

"Die Nutzung von KI in der Arbeitswelt hat innerhalb eines Jahres deutlich zugenommen – gleichzeitig bleiben erhebliche Unterschiede zwischen Berufsgruppen, Bildungsniveaus und Unternehmen bestehen. In der zweiten Welle der Konstanzer KI-Studie berichten 35?% der Befragten von KI-Nutzung im Arbeitsalltag, ein Anstieg um 11 Prozentpunkte gegenüber dem Vorjahr. Trotz dieses Wachstums bleibt die Unsicherheit hoch: Ein Drittel der Beschäftigten kann weiterhin nicht einschätzen, welche Folgen KI für die eigene Arbeit haben wird. Zugleich wird der gesellschaftliche Einfluss von Automatisierung deutlich bedrohlicher wahrgenommen als die persönliche Betroffenheit. Besonders stark ist der Nutzungszuwachs in wissensintensiven Berufen, während produktionsnahe Tätigkeiten kaum aufholen. Auch die Kluft zwischen Bildungsgruppen bleibt bestehen: Beschäftigte mit hohem Bildungsabschluss nutzen KI mehr als dreimal so häufig wie jene mit niedrigem Abschluss. Zwar steigt die Bereitschaft zur Weiterbildung in allen Gruppen, strukturelle Hürden scheinen jedoch eine Angleichung zu verhindern. Auf Ebene der Organisationen verlaufen die Entwicklungen deutlich langsamer als auf individueller Ebene. Vor allem große Unternehmen investieren zunehmend in Weiterbildung und Führungskommunikation, während kleinere Organisationen kaum Veränderungen zeigen. Die Ergebnisse zeigen deutlich, dass KI ihr Potenzial nicht gleichmäßig entfaltet, sondern bestehende strukturelle Ungleichheiten eher verstärkt. Nach wie vor besteht die reale Gefahr, dass sich bestimmte Beschäftigtengruppen zunehmend vom technologischen Fortschritt abkoppeln, weil ihnen der Zugang zu KI-Nutzung, Weiterbildungsangeboten und betrieblicher Unterstützung fehlt. Daraus ergibt sich ein klarer Handlungsauftrag an Wirtschaft, Politik und Bildungseinrichtungen, um Teilhabechancen gezielt zu fördern und einer wachsenden sozialen Spaltung frühzeitig entgegenzuwirken." (Textauszug, IAB-Doku)

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Kurz, D. Heinz, Strohmaier Rita & Knell Mark (2025): Technological Change: History, Theory and Measurement. A Brief Account. (JRC working papers series on labour, education and technology 2025,03), Sevilla, 66 S.

Abstract

"Technological change, an overwhelming fact in recent socioeconomic history, involves, as Joseph A. Schumpeter famously put it, “creative destruction” on a large scale: it gives rise to new goods, production methods, firms, organisations, and jobs, while rendering some received ones obsolete. Its impact extends beyond the economy and affects society, culture, politics, and the mind-set of people. While it allows solving certain problems, it causes new ones, inducing further technological change. Against this background, the paper attempts to provide a detailed, yet concise exploration of the historical evolution and measurement of technological change in economics. It touches upon various questions that have been raised since Adam Smith and by economic and social theorists after him until today living through several waves of new technologies. These questions include: (1) Which concepts and theories did the leading authors elaborate to describe and analyse the various forms of technological progress they observed? (2) Did they think that different forms of technological progress requested the elaboration of different concepts and theories – horses for courses, so to speak? (3) How do different forms of technological progress affect and are shaped by various strata and classes of society? Issues such as these have become particularly crucial in the context of the digitisation of the economy and the widespread use of AI. Finally, the paper explores the impact of emerging technologies on the established theoretical frameworks and empirical measurements of technological change, points to new measurements linked to the rise of these technologies, and evaluates their pros and cons vis-à-vis traditional approaches." (Author's abstract, IAB-Doku) ((en))

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Küstermann, Leon (2025): Upgrading jobs for all: How welfare states shape differences in life satisfaction between the winners and losers of structural change. In: Socio-economic review, Jg. 23, H. 4, S. 1895-1921. DOI:10.1093/ser/mwaf029

Abstract

"Structural economic change transforms occupational structures in a way that has benefited college-educated knowledge economy workers while creating risks for workers in routine and interpersonal service jobs. However, looking beyond economic outcomes, it is striking that differences in life satisfaction between these occupational groups in some European countries are much smaller than in others. To explain this pattern, I analyze data from the European Social Survey and the European Working Conditions Survey for twenty-five countries. I show that these life satisfaction differences are smaller in countries where jobs in “losing” occupations are designed similarly to jobs in “winning” occupations. Further, I demonstrate that both social investment and social protection reduce this life satisfaction gap by equalizing job satisfaction and job design between occupational groups. Hence, my results support the argument that welfare states achieve inclusive outcomes in the context of structural economic change through their interactions with workplaces." (Author's abstract, IAB-Doku) ((en))

Abstract

"This report examines the potential for generative AI – tools that generate text, images, video or audio, such as ChatGPT, Copilot and Midjourney – to help SMEs address labour and skill needs. It presents evidence from a representative 2024 OECD survey of over 5 000 SMEs in Austria, Canada, Germany, Ireland, Japan, Korea and the United Kingdom, on how SMEs use generative AI, how its use may be helping to address labour and skill needs, and how SMEs are preparing employees to use generative AI. The survey shows that generative AI is in use in 31% of SMEs. SMEs report that generative AI improves performance, helps compensate for skill gaps and labour shortages, and increases the need for highly-skilled workers. SMEs have concerns about copyright, legal and regulatory issues, though negative attitudes towards generative AI are rare. The findings highlight the promise of generative AI but also the need for structured policy support to close digital and skills gaps between SMEs and larger firms and to ensure that any gains from generative AI are broadly shared across the economy and the workforce." (Author's abstract, IAB-Doku) ((en))

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Leitner, Sebastian & Stella Sophie Zilian (2025): Digitalisation of jobs and gender-age segregation in digital tasks: Cross-country evidence based on ESJS2 data. (WIIW working paper 269), Wien, 37 S.

Abstract

"This paper addresses the disproportional effects of digitalisation across age by investigating (i) within-job age segregation in tasks by digital intensity; (ii) within-job age disparities in digital upskilling; (iii) age inequalities in wage returns to digital job tasks; and (iv) the role of gender in this age segregation and inequalities. The analysis is based on data of Cedefop's second wave of the European Skills and Jobs Survey (ESJS2), conducted in 2021. First results of the analysis show that even when controlling for occupation-industry job pairs apart from using other explanatory variables, age segregation and gender gaps are prevalent in the case of digital skill intensity of tasks performed in the jobs of employees, though not in the case of digital upskilling via training measures. Applying the same appropriate controls, we also find that higher within-job digital skill intensity is associated with higher hourly wages. Gender wage gaps are sizable across all skill intensity categories in addition to widening in older age groups." (Author's abstract, IAB-Doku) ((en))

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Lewandowski, Piotr & Wojciech Szymczak (2025): Automation, Trade Unions and Atypical Employment. In: Industrial Relations, S. 1-19. DOI:10.1111/irel.70017

Abstract

"We study the effect of automation technologies—industrial robots, software and databases—on the incidence of involuntary atypical employment in 13 EU countries between 2006 and 2018. Robots do not affect the total employment rate but significantly increase the involuntary atypical employment share, mainly through fixed-term work. Software and databases increase total employment and are neutral for atypical employment. Higher trade union density mitigates the robots' impact on atypical employment, while employment protection legislation plays no role. Using historical decompositions, we attribute 1–2 percentage points of a 15% average atypical employment share in our sample to automation." (Author's abstract, IAB-Doku, Published by arrangement with John Wiley & Sons) ((en))

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Logchies, Thomas, Tom Coupé & W. Robert Reed (2025): Do robots decrease humans’ wages? In: Applied Economics Letters, S. 1-5. DOI:10.1080/13504851.2025.2466748

Abstract

"While there are studies that show a positive or negative impact of robots on wages, a meta-analysis of 2,586 estimates from 52 studies in this paper finds that when one looks at the literature as a whole, there is no clear evidence of a sizable impact of robots on wages." (Author's abstract, IAB-Doku) ((en))

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Lott, Yvonne & Andreas Hövermann (2025): Computer Use and Digital Frustration in German Workplaces: Is There a Gendered Part-Time Gap? In: Work, Employment and Society, Jg. 39, H. 6, S. 1440-1462. DOI:10.1177/09500170251351265

Abstract

"The digital transformation may disproportionately disadvantage female part-time workers, as they are affected by the flexibility stigma and career penalties. In this article, we ask: Is there a gendered part-time gap in work-related computer use and digital frustration in Germany? Latent class analysis and multivariate analysis, based on data from Wave 12 (2019/20) of the German National Educational Panel Study (NEPS) Starting Cohort 6 – Adults, showed that women – and part-time working women in particular – were less likely than men to be classified as ‘advanced users’. Furthermore, part-time working women felt least well prepared for using networked digital technologies at work and were thus more at risk of experiencing digital frustration. These findings suggest that the triadic association between technology, power and masculinity postulated by feminist technology theory should be extended to include full-time work." (Author's abstract, IAB-Doku) ((en))

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Lábaj, Martin, Tomáš Oleš & Gabriel Procházka (2025): Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK. In: Eurasian business review, Jg. 15, H. 4, S. 953-1001. DOI:10.1007/s40821-025-00314-w

Abstract

"Over the past four decades, automation technologies have replaced routine tasks performed by medium-skilled workers, and contributed to increased labor market polarization. With the advent of artificial intelligence, this dynamic may have shifted, extending task substitution to non-routine tasks performed by high-skilled workers. Using textual analysis and descriptions of technology found in patent texts, we construct novel occupational exposures to robot and artificial intelligence technologies. These occupational exposures are then used to analyze changes in labor and skill demand over the last decade in the United Kingdom. We find that the middle part of the income distribution is primarily exposed to robot technology, while exposure to artificial intelligence increases monotonically across income percentiles. Second, we find that exposure to robots is strongest among high school dropouts and declines monotonically with education, while artificial intelligence automation has a limited impact on the same workers, with a pronounced exposure among college graduates. Third, our findings suggest asymmetric effects of automation technologies across skill groups. Robot automation reduces demand for low-skilled workers, while AI technology shifts demand away from high-skilled workers, with the direct effects consistently negative despite the presence of several compensating mechanisms. Fourth, despite significant effects on wage bill, we find no robust relationship between automation exposure and changes in the employment-to-population ratio. Finally, a joint estimation of the effects of robot and AI automation shows that robot automation is positively associated with an increase in demand for skilled workers, while AI automation is weakly associated with a decrease in demand for skilled workers." (Author's abstract, IAB-Doku) ((en))

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Lühr, Thomas & Tobias Kämpf (2025): Bots im Büro. Künstliche Intelligenz und der Wandel von Angestelltenarbeit in der digitalen Transformation. (Hans-Böckler-Stiftung. Study 494), Düsseldorf: Hans-Böckler-Stiftung, Düsseldorf, 98 S.

Abstract

"Mit der digitalen Transformation kommt es zu einem Schub in der Automatisierung von Arbeit. Die Einführung von Künstlicher Intelligenz führt zur grundlegenden Restrukturierung der Arbeitsinhalte und -prozesse im Büro. Damit gehen nicht nur Risiken von Funktionsverlusten bis hin zum Verlust des Arbeitsplatzes einher, sondern auch neue Machtpotenziale. Diese prägen das Bewusstsein der Angestellten wesentlich. Künstliche Intelligenz funktioniert nicht ohne Mitbestimmung - mit Mitbestimmung ergeben sich neue Ansatzpunkte für eine arbeitspolitische Vorwärtsstrategie. Die vorliegende Studie nimmt eine empirisch gestützte Analyse der Potenziale vor, die der Automatisierungsschub für die Beschäftigten und ihre Interessenvertretungen tatsächlich bietet." (Autorenreferat, IAB-Doku)

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Machovec, Christine, Michael Rieley & Emily Rolen (2025): Incorporating AI impacts in BLS employment projections: occupational case studies. In: Monthly labor review H. February. DOI:10.21916/mlr.2025.1

Abstract

"In the last few years, artificial intelligence (AI) has advanced rapidly, finding growing applications across industries and occupations. This development has generated interest in how the U.S. Bureau of Labor Statistics assesses and incorporates AI’s potential labor market impacts in its employment projections. In this article, we explain the Bureau’s approach to this type of projections work, illustrating it with several occupational case studies based on research done for the 2023–33 projections cycle. The case studies focus on selected occupations in the computer, legal, business and financial, and architecture and engineering occupational groups." (Author's abstract, IAB-Doku) ((en))

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Mak, Eric & Aloysius Siow (2025): Occupational Choice, Matching, and Earnings Inequality. In: Journal of Political Economy, Jg. 133, H. 1, S. 355-383. DOI:10.1086/732530

Abstract

"We combine classic occupational choice (Roy, 1951) and frictionless matching (Sattinger, 1979) to explain earnings by occupation and firm in a way that is consistent with the double assignment. In our model, within-firm inequality is globally non-zero whenever there is asymmetry in the revenue function or the occupational skill distribution across occupations. Occupational earnings overlap each other, and unlike the Roy Model, the distributions of potential earnings are endogenous. In line with recent empirical findings on earning decomposition, skill-biased technical change (SBTC)increases within-firm inequality mostly among high-wage firms and not among low-wagefirms." (Author's abstract, IAB-Doku) ((en))

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Malin, Christine, Jürgen Fleiß, Renate Ortlieb & Stefan Thalmann (2025): Rejected by an AI? Comparing job applicants’ fairness perceptions of artificial intelligence and humans in personnel selection. In: Frontiers in artificial intelligence, Jg. 8. DOI:10.3389/frai.2025.1671997

Abstract

"Introduction: Artificial intelligence (AI) transforms personnel selection, but the application of AI raises fairness concerns and aversion towards AI. Although job applicants may perceive the selection process as fairer when they receive an explanation for the decision, scientific knowledge about AI-related fairness perceptions in this setting is limited. This paper investigates how job applicants perceive fairness of an AI-based personnel selection process considering explanations provided. Methods: The hypotheses are based on a theoretical framework about fairness and literature on algorithm aversion. Data were collected through a vignette-style method focusing on four personnel selection scenarios (n = 921). Results: We show that provided explanations increase job applicants ’ perceptions of outcome fairness, process fairness, interpersonal treatment, and recommendation intention, irrespective of the decision being made by an AI or human. Discussion: We provide conclusions for algorithmic decision-making and discuss factors that need to be considered when adopting and designing AI so that AI is perceived as fair." (Author's abstract, IAB-Doku) ((en))

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Marczuk, Anna, Frank Multrus, Thomas Hinz & Susanne Strauss (2025): Künstliche Intelligenz (KI) im Studienalltag: Einschätzungen von Studierenden zum Einsatz von KI an deutschen Hochschulen. (DZHW-Brief 2025,02), Hannover, 15 S. DOI:10.34878/2025.02.dzhw_brief

Abstract

"Die Mehrheit der Studierenden nutzt im Wintersemester 2024/2025 KI im Studium und kennt deren Funktionsweise relativ gut. ChatGPT ist das meistgenutzte KI-Tool, dessen Nutzung seit 2023 deutlich angestiegen ist. Studierende verwenden KI am häufigsten für die Einführung in ein Thema und für Textverarbeitungen, deutlich seltener für Literaturrecherchen oder Datenanalysen. Die Mehrheit der Studierenden gibt an, dass KI die Erledigung von Aufgaben, die keinen Spaß machen oder schwierig sind, beschleunigt oder erleichtert. Seltener sind Studierende der Ansicht, dass KI die Studienleistungen verbessert. Studierende stehen KI auch kritisch gegenüber, insbesondere wegen ihrer Fehleranfälligkeit und des Risikos, von ihr abhängig zu werden. Studierende, die KI häufig nutzen, sind gegenüber KI ähnlich kritisch wie Studierende, die sie seltener nutzen. Der Einsatz von Learning Analytics wird von Studierenden eher befürwortet, wenn sie selbst dadurch unterstützt werden (etwa durch Kurs- und Literaturempfehlungen), weniger zur Unterstützung von Lehrenden (etwa bei der Benotung) oder der Hochschulverwaltung (etwa für die Studienabbruchprävention). Studierende erleben eher selten eine Unterstützung der Hochschulen bei der Nutzung von KI im Studium. An einigen Hochschulen berichten sie von Richtlinien zur Nutzung, seltener sind Schulungsangebote oder eine Integration in die Lehre. Studierende wünschen sich KI-Unterstützung beim Verfassen von Hausarbeiten, während der Einsatz durch Lehrende zur Benotung oder als Ersatz für Lerngruppen (automatisierte Lernbuddys) skeptisch gesehen wird. Eine Teildigitalisierung von Lehrveranstaltungen (Mischung aus Präsenz und online) ist für Studierende attraktiver als reine Präsenz- oder gar reine Onlineveranstaltungen." (Autorenreferat, IAB-Doku)

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Matthes, Britta (2025): Wie KI Berufe verändert und Chancen für Menschen mit Behinderungen schafft. In: Die Berufliche Rehabilitation, Jg. 39, H. 1, S. 6-15., 2025-04-04.

Abstract

"Es ist absehbar, dass die rasanten technologischen Entwicklungen der letzten Jahre, insbesondere die enorme Steigerung der Rechenleistung und die Entwicklung selbstlernender algorithmischer Systeme, die heute allgemein als Künstliche Intelligenz (KI) bezeichnet werden, ihre Spuren auf dem Arbeitsmarkt hinterlassen werden. Welche das genau sein werden, können wir leider aber auch nicht sagen. Denn gerade in solch disruptiven Zeiten, wie wir sie derzeit erleben, wissen wir nicht, wie schnell und in welche Richtung sich bestehende Berufe verändern, welche Berufe verschwinden und welche neu entstehen werden. Zwar können Prognosen etwas darüber sagen, wie sich die Zahl der Berufseinsteiger*innen auf die verschiedenen Berufe und Qualifikationsniveaus verteilen würde, wenn sich die Entwicklung wie in der Vergangenheit fortsetzt. Allerdings scheinen die Potenziale, die sich aus dem Einsatz von KI ergeben, bekannte Zusammenhänge in Frage zu stellen. Hinzu kommt, dass diese Prognosemodelle sehr komplex sind, um daraus sinnvolle Schlussfolgerungen für den Einzelnen zu ziehen. So lässt sich die Frage, inwiefern KI und andere digtale Technolgien auch die Beschäftigungsmöglichkeiten für Menschen mit Behinderungen erweitern könnten, damit kaum beantworten." (Textauszug, IAB-Doku)

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Matthes, Britta (2025): KI und Beratung. In: Dvb-Forum, Jg. 64, H. 1, S. 17-22., 2025-02-14.

Abstract

"Wie KI und andere digitale Technologien den Arbeitsmarkt verändern: Am IAB werden wir immer wieder danach gefragt, welche Berufe angesichts der rasanten technologischen Entwicklungen der letzten Jahre überhaupt noch Zukunft haben. Bislang hat man zur Beantwortung dieser Frage Prognosen zu Rate gezogen. Hier wurde anfangs – unter Berücksichtigung verschiedener relativ stabiler Faktoren wie dem Erwerbspersonenpotenzial, der wirtschaftlichen Entwicklung oder der zu erwartenden Migration – hochgerechnet, wie sich die Zahl der Berufsanfänger auf die verschiedenen Berufe und Qualifikationsniveaus verteilt, wenn die Entwicklung sich wie in der Vergangenheit fortsetzen würde. Schon früh wurde jedoch deutlich, dass diese Faktoren weniger stabil sind als ursprünglich angenommen. Um diese Dynamik zu berücksichtigen, wurde dieser Ansatz erweitert, indem nunmehr Projektionen erstellt werden. Dazu werden Annahmen über die Folgen bestimmter, äußerst wahrscheinlicher Ereignisse oder Verhaltensweisen getroffen, für die sich (noch) keine langfristige Zahlenbasis finden lässt. So gibt die QuBe-Projektion einen langfristigen Überblick über die voraussichtliche Entwicklung des Arbeitskräftebedarfs und -angebotes nach Qualifikationen und Berufen unter einer Reihe von Annahmen über zum Beispiel die Folgen des Klimawandels oder den Ausbau der ökologischen Landwirtschaft. Außerdem werden anhand von Abweichungen zwischen diesem Basismodell und Szenarien die absehbaren Folgen bestimmter Vorhaben oder Ereignisse, wie zum Beispiel der Maßnahmen zur Energie- und -Mobilitätswende abgeschätzt (https://www.bibb.de/de/202333.php). Allerdings sind diese Modelle sehr komplex und es stellt sich die Frage, inwieweit solche Projektionen für die Bildungs- und Berufsberatung einzelner Personen sinnvoll genutzt werden können. Hinzu kommt derzeit, dass die technologische Entwicklung derart schnell voranschreitet, dass verstärkt mit Umwälzungen auf dem Arbeitsmarkt gerechnet werden muss, die auch altbekannte Zusammenhänge in Frage stellen könnten. Für die einzelne Person steht die Frage im Raum, mit welchen Konsequenzen sie selbst rechnen muss, wenn neue Technologien zum Einsatz kommen: Reicht es aus, sich auf den aktuellen Wissensstand im eigenen Beruf zu bringen? Womit sollte man sich konkret beschäftigen, um den Anforderungen des Berufes weiterhin gewachsen zu sein? Ist es zielführender, sich beruflich neu zu orientieren?" (Textauszug, IAB-Doku, © wbv)

Zitatform

Matthes, Britta (2025): Der Einsatz Künstlicher Intelligenz allein kann die zukünftigen Fachkräfteengpässe nicht beheben. (GVG-Perspektive 19), 3 S.

Abstract

"In diesem Beitrag beleuchtet Dr. Britta Matthes, Leiterin der Forschungsgruppe „Berufe in der Transformation“ am IAB, weshalb trotz der Potenziale von Künstlicher Intelligenz Investitionen in die Weiterqualifizierung älterer Beschäftigter unabdingbar bleiben." (Autorenreferat, IAB-Doku)

Zitatform

Matysiak, Anna, Wojciech Hardy & Lucas van der Velde (2025): Structural Labour Market Change and Gender Inequality in Earnings. In: Work, Employment and Society, Jg. 39, H. 2, S. 426-448. DOI:10.1177/09500170241258953

Abstract

"Research from the US argues that women will benefit from a structural labor market change as the importance of social tasks increases and that of manual tasks declines. This article contributes to this discussion in three ways: (a) by extending the standard framework of task content of occupations in order to account for the gender perspective; (b) by developing measures of occupational task content tailored to the European context; and (c) by testing this argument in 13 European countries. Data are analyzed from the European Skills, Competences, Qualifications and Occupations database and the European Structure of Earnings Survey. The analysis demonstrates that relative to men the structural labor market change improves the earnings potential of women working in low- and middle-skilled occupations but not those in high-skilled occupations. Women are overrepresented in low-paid social tasks (e.g. care) and are paid less for analytical tasks than men." (Author's abstract, IAB-Doku) ((en))

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McGuinness, Seamus, Paul Redmond, Konstantinos Pouliakas, Lorcan Kelly & Luke Brosnan (2025): Technological Change and the Upskilling of European Workers. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 17753), Bonn, 22 S.

Abstract

"Using the second wave of the European Skills and Jobs survey, this paper measures the relationship between technological change that automates or augments workers' job tasks and their participation in work-related training. We find that 58 per cent of European employees experienced no change in the need to learn new technologies in their jobs during the 2020-21 period. Of those exposed to new digital technology, 14 per cent did not experience any change in job tasks, 10 per cent reported that new tasks had been created while 5 per cent only saw some of their tasks being displaced by new technology. The remaining 13 per cent simultaneously experienced both task displacement and task creation. Our analysis shows that employees in jobs impacted by new digital technologies are more likely to have to react to unpredictable situations, thus demonstrating a positive link between technologically driven task disruption and job complexity. We show a strong linear relationship between technologically driven job task disruption and the need for job-related training, with training requirements increasing the greater the impact of new technologies on task content." (Author's abstract, IAB-Doku) ((en))

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Milanez, Anna, Annikka Lemmens & Carla Ruggiu (2025): Algorithmic management in the workplace. New evidence from an OECD employer survey. (OECD Artificial Intelligence Papers 31), Paris, 72 S. DOI:10.1787/287c13c4-en

Abstract

"Algorithmisches Management – der Einsatz von Software, die auch künstliche Intelligenz (KI) umfassen kann, zur vollständigen oder teilweisen Automatisierung von Tätigkeiten, die bislang von menschlichen Führungskräften ausgeführt wurden – hat in den letzten Jahren zunehmend Beachtung gefunden. Einerseits kann algorithmisches Management innerhalb von Unternehmen zu Produktivitäts- und Effizienzgewinnen sowie zu konsistenteren und objektiveren Managemententscheidungen führen. Andererseits gibt es aus anderen Studien immer mehr Anzeichen für seine potenziell negativen Auswirkungen auf die Beschäftigten. Während Politikverantwortliche mit der Frage ringen, wie den Herausforderungen des algorithmischen Managements begegnet werden könnte, bedarf es weiterer Evidenz. Um dieses Ziel zu erreichen, stützt sich der vorliegende Bericht auf eine einzigartige Erhebung unter mehr als 6 000 Unternehmen in sechs Ländern: Deutschland, Frankreich, Italien, Japan, Spanien und die Vereinigten Staaten. Er bietet beispiellose Einblicke in die Prävalenz des algorithmischen Managements, seine wahrgenommenen Auswirkungen und die auf Unternehmensebene ergriffenen Maßnahmen zur Steuerung seines Einsatzes. Die Ergebnisse zeigen, dass algorithmische Management-Systeme in der Mehrzahl der untersuchten Länder bereits weit verbreitet sind. In der Wahrnehmung von Führungskräften verbessert algorithmisches Management zwar häufig die Qualität der Entscheidungen und die Zufriedenheit mit der eigenen beruflichen Situation, die Vertrauenswürdigkeit solcher Systeme gibt ihnen jedoch auch Anlass zur Sorge. Als Gründe dafür nennen sie die unklare Verantwortlichkeit, die nicht leicht nachzuvollziehende Logik der Systeme und den unzureichenden Gesundheitsschutz der Beschäftigten. Es ist dringend erforderlich, Politiklücken zu untersuchen, um den vertrauenswürdigen Einsatz algorithmischer Management-Systeme sicherzustellen." (Autorenreferat, IAB-Doku)

Zitatform

Minniti, Antonio, Klaus Prettner & Francesco Venturini (2025): AI innovation and the labor share in European regions. In: European Economic Review, Jg. 177. DOI:10.1016/j.euroecorev.2025.105043

Abstract

"This paper examines how the development of Artificial Intelligence (AI) affects the distribution of income between capital and labor, and how these shifts contribute to regional income inequality. To investigate this issue, we analyze data from European regions dating back to 2000. We find that for every doubling of regional AI innovation, the labor share declines by 0.5% to 1.6%, potentially reducing it by 0.09 to 0.31 percentage points from an average of 52%, solely due to AI. This new technology has a particularly negative impact on high- and medium-skill workers, primarily through wage compression, while for low-skill workers, employment expansion induced by AI mildly offsets the associated wage decline. The effect of AI is not driven by other factors influencing regional development in Europe or by the concentration of the AI market." (Author's abstract, IAB-Doku, © 2025 The Authors. Published by Elsevier B.V.) ((en))

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Molitor, Friederike (2025): Work arrangements in digitally mediated care and domestic work. In: Community, work & family, S. 1-20. DOI:10.1080/13668803.2025.2523863

Abstract

"As the need for care has grown, paid care and domestic work in the private home is increasingly being organized on the market. Today, digital platforms serve as intermediaries for care and domestic services but systematic research on the resulting work arrangements between workers and clients remains limited. By understanding platform-mediated care and domestic work arrangements as a (social) exchange of ‘love and money’ between workers and clients, the study explores the working conditions and the worker-client relationships that emerge. Drawing on unique survey data collected on a large digital platform in Germany in 2019, the study shows that care and domestic workers who offer their services on digital platforms often experience informal work arrangements characterized by low working hours and irregular shifts. The worker-client relationships are described as amicable more than professional. They are often built on continuity, long-termism and reliability, which are essential for a lasting relationship. This challenges the on-demand, economic logic characterising other forms of platform work." (Author's abstract, IAB-Doku) ((en))

Zitatform

Muehlemann, Samuel (2025): Artificial intelligence adoption and workplace training. In: Journal of Economic Behavior & Organization, Jg. 238. DOI:10.1016/j.jebo.2025.107206

Abstract

"As artificial intelligence (AI) reshapes business processes, firms must adapt their training strategies to cultivate a skilled workforce. Using German establishment-level panel data from 2019 to 2023, this study analyzes how firms adjust their training strategies following AI adoption. Staggered difference-in-differences analysis shows that sustained AI adoption is associated with a 14% increase in new apprenticeships among training firms (intensive margin), but is not linked to the training decision (extensive margin). AI adoption is also associated with a modest increase in continuing training, with resources shifting toward high-skilled employees. The results align with AI as an automation innovation that reduces demand for simple skills as well as an augmentation innovation that increases demand for more advanced skills. The German dual apprenticeship system appears critical for firms aiming to build a future-ready workforce in the age of AI." (Author's abstract, IAB-Doku, © 2025 The Author. Published by Elsevier B.V.) ((en))