Moving beyond human-centric organizational designs

David Mortimore ()
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David Mortimore: Naval Undersea Warfare Center Division, Keyport

Journal of Organization Design, 2024, vol. 13, issue 2, 65-75

Abstract: Abstract Investments in artificial intelligence, autonomous robotics, and similar technical systems continue to accelerate as organizations pursue opportunities to strengthen their performance and create even greater value for stakeholders. Despite voluminous guidance and best practices on designing and operationalizing such technical systems, many organizations are not achieving their expected returns and performance levels. The problem might be a biased view of organizations as primarily human-centric systems, which can place unnecessary limits on the performance of intelligent robots, artificial intelligence, and similar technical systems. Reimagining and purposefully designing organizations as systems composed of human and non-human knowledge workers co-performing tasks for organizational goal attainment can generate more robust performance and strengthen corporate returns on investments in such sophisticated systems. Non-human knowledge workers (NHKWs) are synthetic computational agents characterized by the conjunction of four attributes—information processing power, knowledge work, task-level employment, and more comprehensive organizational integration—distinguishing them from more common artificial intelligence, autonomous robotics systems, and autonomous vehicles frameworks. More gainful employment of NHKWs, and similar systems, is primarily a design issue and one that is largely separate from the capabilities NHKWs might possess. Using an organizational technology framework, this paper offers managers and organizational designers a systematic approach that can harness NHKW capabilities more effectively, thereby producing stronger organizational performance.

Keywords: Artificial intelligence; Computational agents; Robots; AI boss; Algorithmic manager; Cognitive bias; Team performance; Organizational design (search for similar items in EconPapers)
JEL-codes: D23 L2 L22 L23 L25 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s41469-024-00167-z

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