IDEAS home Printed from https://ideas.repec.org/a/eee/bushor/v66y2023i1p87-99.html
   My bibliography  Save this article

Artificial intelligence and knowledge management: A partnership between human and AI

Author

Listed:
  • Jarrahi, Mohammad Hossein
  • Askay, David
  • Eshraghi, Ali
  • Smith, Preston

Abstract

Emerging artificial intelligence (AI) capabilities will likely pervade nearly all organizational contours and activities, including knowledge management (KM). This article aims to uncover opportunities associated with the implementation of emerging systems empowered by AI for KM. In doing so, we explicate the potential role of AI in supporting fundamental dimensions of KM: creation, storage and retrieval, sharing, and application of knowledge. We then propose practical ways to build the partnership between humans and AI in supporting organizational KM activities and provide several implications for the development and management of AI systems based on the components of people, infrastructures, and processes.

Suggested Citation

  • Jarrahi, Mohammad Hossein & Askay, David & Eshraghi, Ali & Smith, Preston, 2023. "Artificial intelligence and knowledge management: A partnership between human and AI," Business Horizons, Elsevier, vol. 66(1), pages 87-99.
    • Handle: RePEc:eee:bushor:v:66:y:2023:i:1:p:87-99
    DOI: 10.1016/j.bushor.2022.03.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0007681322000222
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.bushor.2022.03.002?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    2. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57, National Bureau of Economic Research, Inc.
    3. Canhoto, Ana Isabel & Clear, Fintan, 2020. "Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential," Business Horizons, Elsevier, vol. 63(2), pages 183-193.
    4. Vahe Tshitoyan & John Dagdelen & Leigh Weston & Alexander Dunn & Ziqin Rong & Olga Kononova & Kristin A. Persson & Gerbrand Ceder & Anubhav Jain, 2019. "Unsupervised word embeddings capture latent knowledge from materials science literature," Nature, Nature, vol. 571(7763), pages 95-98, July.
    5. Mohammad Hossein Jarrahi & Gabriela Philips & Will Sutherland & Steve Sawyer & Ingrid Erickson, 2019. "Personalization of knowledge, personal knowledge ecology, and digital nomadism," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(4), pages 313-324, April.
    6. Wanda J. Orlikowski, 2002. "Knowing in Practice: Enacting a Collective Capability in Distributed Organizing," Organization Science, INFORMS, vol. 13(3), pages 249-273, June.
    7. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sundberg, Leif & Holmström, Jonny, 2023. "Democratizing artificial intelligence: How no-code AI can leverage machine learning operations," Business Horizons, Elsevier, vol. 66(6), pages 777-788.
    2. Abdulaziz Aldoseri & Khalifa N. Al-Khalifa & Abdel Magid Hamouda, 2024. "AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact," Sustainability, MDPI, vol. 16(5), pages 1-25, February.
    3. Ekaterina Glebova, 2024. "Research Duos: Unveiling the Collaborative Essence of Research," Societies, MDPI, vol. 14(9), pages 1-12, September.
    4. wael AL-khatib, Ayman, 2023. "Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework," Technology in Society, Elsevier, vol. 75(C).
    5. Jin Zhang & Duoxun Ba, 2024. "Intelligent Development, Knowledge Breadth, and High-Tech Enterprise Innovation: The Moderating Role of Knowledge Absorptive Capacity," Sustainability, MDPI, vol. 16(18), pages 1-18, September.
    6. Rabaï Bouderhem, 2024. "Shaping the future of AI in healthcare through ethics and governance," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    7. Park, Jennifer Jihae, 2024. "Unlocking training transfer in the age of artificial intelligence," Business Horizons, Elsevier, vol. 67(3), pages 263-269.

    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. Black, J. Stewart & van Esch, Patrick, 2020. "AI-enabled recruiting: What is it and how should a manager use it?," Business Horizons, Elsevier, vol. 63(2), pages 215-226.
    2. 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.
    3. Neubert, Mitchell J. & Montañez, George D., 2020. "Virtue as a framework for the design and use of artificial intelligence," Business Horizons, Elsevier, vol. 63(2), pages 195-204.
    4. Alina Köchling & Marius Claus Wehner, 2020. "Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 795-848, November.
    5. Pham, Phuoc & Zhang, Huilan & Gao, Wenlian & Zhu, Xiaowei, 2024. "Determinants and performance outcomes of artificial intelligence adoption: Evidence from U.S. Hospitals," Journal of Business Research, Elsevier, vol. 172(C).
    6. Nick Drydakis, 2022. "Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic," Information Systems Frontiers, Springer, vol. 24(4), pages 1223-1247, August.
    7. 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.
    8. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    9. Holmström, Jonny, 2022. "From AI to digital transformation: The AI readiness framework," Business Horizons, Elsevier, vol. 65(3), pages 329-339.
    10. Black, J. Stewart & van Esch, Patrick, 2021. "AI-enabled recruiting in the war for talent," Business Horizons, Elsevier, vol. 64(4), pages 513-524.
    11. Lee, In & Shin, Yong Jae, 2020. "Machine learning for enterprises: Applications, algorithm selection, and challenges," Business Horizons, Elsevier, vol. 63(2), pages 157-170.
    12. Canhoto, Ana Isabel, 2021. "Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective," Journal of Business Research, Elsevier, vol. 131(C), pages 441-452.
    13. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    14. Campbell, Colin & Sands, Sean & Ferraro, Carla & Tsao, Hsiu-Yuan (Jody) & Mavrommatis, Alexis, 2020. "From data to action: How marketers can leverage AI," Business Horizons, Elsevier, vol. 63(2), pages 227-243.
    15. Jia-Min Lu & Hui-Feng Wang & Qi-Hang Guo & Jian-Wei Wang & Tong-Tong Li & Ke-Xin Chen & Meng-Ting Zhang & Jian-Bo Chen & Qian-Nuan Shi & Yi Huang & Shao-Wen Shi & Guang-Yong Chen & Jian-Zhang Pan & Zh, 2024. "Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    16. Verena Brinks, 2016. "Situated affect and collective meaning: A community perspective on processes of value creation and commercialization in enthusiast-driven fields," Environment and Planning A, , vol. 48(6), pages 1152-1169, June.
    17. Kariem Soliman, 2021. "Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth," EIIW Discussion paper disbei307, Universitätsbibliothek Wuppertal, University Library.
    18. Ananthan Nambiar & Tobias Rubel & James McCaull & Jon deVries & Mark Bedau, 2021. "Dropping diversity of products of large US firms: Models and measures," Papers 2110.08367, arXiv.org.
    19. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    20. Naudé, Wim & Nagler, Paula, 2022. "The Ossified Economy: The Case of Germany, 1870-2020," IZA Discussion Papers 15607, Institute of Labor Economics (IZA).

    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:eee:bushor:v:66:y:2023:i:1:p:87-99. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/bushor .

    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.