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<p>Generative artificial intelligence (AI) is widely discussed as a&#xa0;key enabling technology and is increasingly being used in knowledge work. However, for Germany, there is still a&#xa0;lack of robust empirical evidence on the occupational contexts in which generative AI is used intensively and those in which it is not. In this article, we address this research gap by examining the extent to which workplace characteristics (job autonomy, job demands, tasks, and managerial responsibility) are systematically associated with the adoption of generative AI among the knowledge-intensive occupational group of corporate organization and strategy. Methodologically, logistic regression models with work-related predictors and demographic control variables were employed. The analysis is based on data from the 2024 wave of the BIBB/BAuA Employment Survey. The results for the occupational group examined in this study show that, in particular, higher levels of job autonomy are significantly associated with greater adoption of generative AI.</p><p><i>Practical Relevance</i>: This article provides empirical evidence on the prevalence of generative AI and the predictors of its use. The observed usage patterns offer insights for job design by highlighting existing social inequalities in the adoption of generative AI, the work-related conditions along which digital transformation unfolds, and the areas in which AI-related competencies are likely to gain importance. Furthermore, the findings provide a&#xa0;basis for policy decisions and the development of regulatory measures.</p>

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Adoption generativer KI in der Wissensarbeit: Die Rolle von beruflicher Autonomie, Arbeitsanforderungen, Tätigkeiten und Führungsverantwortung

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月2日

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  • Tim Komorowski,
  • Thomas Süße

摘要

Generative artificial intelligence (AI) is widely discussed as a key enabling technology and is increasingly being used in knowledge work. However, for Germany, there is still a lack of robust empirical evidence on the occupational contexts in which generative AI is used intensively and those in which it is not. In this article, we address this research gap by examining the extent to which workplace characteristics (job autonomy, job demands, tasks, and managerial responsibility) are systematically associated with the adoption of generative AI among the knowledge-intensive occupational group of corporate organization and strategy. Methodologically, logistic regression models with work-related predictors and demographic control variables were employed. The analysis is based on data from the 2024 wave of the BIBB/BAuA Employment Survey. The results for the occupational group examined in this study show that, in particular, higher levels of job autonomy are significantly associated with greater adoption of generative AI.

Practical Relevance: This article provides empirical evidence on the prevalence of generative AI and the predictors of its use. The observed usage patterns offer insights for job design by highlighting existing social inequalities in the adoption of generative AI, the work-related conditions along which digital transformation unfolds, and the areas in which AI-related competencies are likely to gain importance. Furthermore, the findings provide a basis for policy decisions and the development of regulatory measures.