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<p>Artificial Intelligence (AI) is a key driver for the future transformation of production management. However, to ensure its effective implementation, it is crucial to systematically identify the most relevant application areas. Despite the growing relevance of AI, there is currently no comprehensive assessment of which production management tasks can derive the greatest benefit from the use of AI at an acceptable effort. While applications where AI supports repetitive tasks are increasingly accepted, AI is met with considerable skepticism when it comes to tasks involving social interaction, experiential knowledge, or autonomous decision-making. Final decisions are deliberately kept under human responsibility, reflecting concerns about loss of control and devaluation of human expertise. This highlights the current barriers of AI in replicating human-centered work. Identifying these production management tasks is not trivial, as there are many interdependencies and multi-criteria dependencies in the decision-making process. The subjective perception of production managers and their trust in AI also play an important role. The results clearly show that the tasks of production controlling, process design, financing and investment, operational production management and order management and fulfillment offer great potential to have these tasks performed by an AI with a good effort-benefit ratio. Our results underscore the need to evaluate AI performance on these tasks in direct comparison with humans. Future research should develop simulative environments to test and evaluate AI-adoption.</p>

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From human to machine: high-impact tasks for AI in production management – an expert study to reshape decision-making

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月8日

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  • Luisa Stracke,
  • Peter Burggräf,
  • Carl René Sauer,
  • Maximilian Schütz,
  • Joshua Kaiser

摘要

Artificial Intelligence (AI) is a key driver for the future transformation of production management. However, to ensure its effective implementation, it is crucial to systematically identify the most relevant application areas. Despite the growing relevance of AI, there is currently no comprehensive assessment of which production management tasks can derive the greatest benefit from the use of AI at an acceptable effort. While applications where AI supports repetitive tasks are increasingly accepted, AI is met with considerable skepticism when it comes to tasks involving social interaction, experiential knowledge, or autonomous decision-making. Final decisions are deliberately kept under human responsibility, reflecting concerns about loss of control and devaluation of human expertise. This highlights the current barriers of AI in replicating human-centered work. Identifying these production management tasks is not trivial, as there are many interdependencies and multi-criteria dependencies in the decision-making process. The subjective perception of production managers and their trust in AI also play an important role. The results clearly show that the tasks of production controlling, process design, financing and investment, operational production management and order management and fulfillment offer great potential to have these tasks performed by an AI with a good effort-benefit ratio. Our results underscore the need to evaluate AI performance on these tasks in direct comparison with humans. Future research should develop simulative environments to test and evaluate AI-adoption.