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<p>The study analyzes the introduction of Microsoft 365 Copilot in a&#xa0;non-university research organization using a&#xa0;repeated cross-sectional employee survey. We assess usefulness, ease of use, output quality and reliability, and usefulness for typical knowledge-work activities. Administrative staff report higher usefulness and reliability, whereas scientific staff develop more positive assessments over time, especially regarding productivity and workload reduction. Copilot is widely viewed as user-friendly and technically reliable, with greatest added value for clearly structured, text-based tasks. The findings highlight learning and routinization effects when embedding generative AI into work processes and stress the need for context-sensitive implementation, role-specific training and governance to foster sustainable acceptance of generative AI in knowledge-intensive organizations.</p><p><i>Practical Relevance</i>: The study provides empirical insights into the implementation of generative AI in knowledge-intensive organizations. It shows that Microsoft 365 Copilot particularly enhances efficiency in administrative areas, while context-specific training and support measures are crucial for success in research settings. The findings help organizations design context-sensitive AI implementation strategies, foster user acceptance, and purposefully leverage the potential of AI to ensure productive human–AI interaction and create organizational value.</p>

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Generative KI in der Wissensarbeit: Wahrnehmung, Nutzen und Akzeptanz von Microsoft 365 Copilot

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月23日

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  • Carsten F. Schmidt,
  • Sophie Petzolt,
  • Wolfgang Beinhauer,
  • Ingo Weber,
  • Stefan Langer

摘要

The study analyzes the introduction of Microsoft 365 Copilot in a non-university research organization using a repeated cross-sectional employee survey. We assess usefulness, ease of use, output quality and reliability, and usefulness for typical knowledge-work activities. Administrative staff report higher usefulness and reliability, whereas scientific staff develop more positive assessments over time, especially regarding productivity and workload reduction. Copilot is widely viewed as user-friendly and technically reliable, with greatest added value for clearly structured, text-based tasks. The findings highlight learning and routinization effects when embedding generative AI into work processes and stress the need for context-sensitive implementation, role-specific training and governance to foster sustainable acceptance of generative AI in knowledge-intensive organizations.

Practical Relevance: The study provides empirical insights into the implementation of generative AI in knowledge-intensive organizations. It shows that Microsoft 365 Copilot particularly enhances efficiency in administrative areas, while context-specific training and support measures are crucial for success in research settings. The findings help organizations design context-sensitive AI implementation strategies, foster user acceptance, and purposefully leverage the potential of AI to ensure productive human–AI interaction and create organizational value.