IDEAS home Printed from https://ideas.repec.org/a/spr/jorgde/v13y2024i2d10.1007_s41469-024-00167-z.html
   My bibliography  Save this article

Moving beyond human-centric organizational designs

Author

Listed:
  • David Mortimore

    (Naval Undersea Warfare Center Division, Keyport)

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.

Suggested Citation

  • David Mortimore, 2024. "Moving beyond human-centric organizational designs," Journal of Organization Design, Springer;Organizational Design Community, vol. 13(2), pages 65-75, June.
  • Handle: RePEc:spr:jorgde:v:13:y:2024:i:2:d:10.1007_s41469-024-00167-z
    DOI: 10.1007/s41469-024-00167-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41469-024-00167-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1007/s41469-024-00167-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    2. Richard M. Burton & Børge Obel, 2018. "The science of organizational design: fit between structure and coordination," Journal of Organization Design, Springer;Organizational Design Community, vol. 7(1), pages 1-13, December.
    3. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    4. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    5. Charles C. Snow & Øystein Devik Fjeldstad & Arthur M. Langer, 2017. "Designing the digital organization," Journal of Organization Design, Springer;Organizational Design Community, vol. 6(1), pages 1-13, December.
    6. Oliver Baumann & Brian Wu, 2023. "Managerial hierarchy in AI-driven organizations," Journal of Organization Design, Springer;Organizational Design Community, vol. 12(1), pages 1-5, June.
    7. Taylor, Frederick Winslow, 1911. "The Principles of Scientific Management," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, number taylor1911.
    8. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    9. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    2. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    3. Thinley Tharchen & Raghu Garud & Rebecca L. Henn, 2020. "Design as an interactive boundary object," Journal of Organization Design, Springer;Organizational Design Community, vol. 9(1), pages 1-34, December.
    4. Ayat Sami ODEIBAT, 2021. "The Effect Of Technology Evolution On The Future Of Jobs," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 17, pages 57-67, June.
    5. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    6. Bruce Heiman & Jack Nickerson, 2002. "Towards Reconciling Transaction Cost Economics and the Knowledge-based View of the Firm: The Context of Interfirm Collaborations," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 9(1), pages 97-116.
    7. Keding, Christoph & Meissner, Philip, 2021. "Managerial overreliance on AI-augmented decision-making processes: How the use of AI-based advisory systems shapes choice behavior in R&D investment decisions," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    8. John W. Gardner & Kenneth K. Boyer & Peter T. Ward, 2017. "Achieving Time-Sensitive Organizational Performance Through Mindful Use of Technologies and Routines," Organization Science, INFORMS, vol. 28(6), pages 1061-1079, December.
    9. Markus Gmür, 2003. "Co-citation analysis and the search for invisible colleges: A methodological evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(1), pages 27-57, January.
    10. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    11. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    12. Wang, Lei & Zhou, Yahong & Chiao, Benjamin, 2023. "Robots and firm innovation: Evidence from Chinese manufacturing," Journal of Business Research, Elsevier, vol. 162(C).
    13. Shin-Cheng Yeh & Ai-Wei Wu & Hui-Ching Yu & Homer C. Wu & Yi-Ping Kuo & Pei-Xuan Chen, 2021. "Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-34, August.
    14. Christian Julmi, 2019. "When rational decision-making becomes irrational: a critical assessment and re-conceptualization of intuition effectiveness," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 291-314, April.
    15. Vlačić, Božidar & Corbo, Leonardo & Costa e Silva, Susana & Dabić, Marina, 2021. "The evolving role of artificial intelligence in marketing: A review and research agenda," Journal of Business Research, Elsevier, vol. 128(C), pages 187-203.
    16. Akter, Shahriar & Hossain, Md Afnan & Sajib, Shahriar & Sultana, Saida & Rahman, Mahfuzur & Vrontis, Demetris & McCarthy, Grace, 2023. "A framework for AI-powered service innovation capability: Review and agenda for future research," Technovation, Elsevier, vol. 125(C).
    17. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    18. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    19. Olga Lucía Anzola Morales & Diego Armando Marín Idárraga & Juan Carlos Cuartas Marín, 2017. "Fundamentación teórica de la cultura, la estructura y la estrategia de la organización. Referentes para el análisis y diseño organizacional," Books, Universidad Externado de Colombia, Facultad de Administración de Empresas, edition 1, number 45, August.
    20. Sagarika Mishra & Michael T. Ewing & Holly B. Cooper, 2022. "Artificial intelligence focus and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1176-1197, November.

    More about this item

    Keywords

    Artificial intelligence; Computational agents; Robots; AI boss; Algorithmic manager; Cognitive bias; Team performance; Organizational design;
    All these keywords.

    JEL classification:

    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jorgde:v:13:y:2024:i:2:d:10.1007_s41469-024-00167-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.