IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v120y2020icp262-273.html
   My bibliography  Save this article

Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization

Author

Listed:
  • Makarius, Erin E.
  • Mukherjee, Debmalya
  • Fox, Joseph D.
  • Fox, Alexa K.

Abstract

Artificial intelligence (AI) is increasingly being adopted by organizations, yet implementation is often carried out without careful consideration of the employees who will be working along with it. If employees do not understand or work with AI, it is unlikely to bring value to an organization. The purpose of this paper is to investigate the ways in which employees and AI can collaborate to build different levels of sociotechnical capital. Accordingly, we develop a model of AI integration based on Socio-Technical Systems (STS) theory that combines AI novelty and scope dimensions. We take an organizational socialization approach to build an understanding of the process of integrating AI into the organization. Our framework underscores the importance of AI socialization as a core process in successfully integrating AI systems and employees. We conclude with a future research agenda that highlights the cognitive, relational, and structural implications of integrating AI and employees.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jbrese:v:120:y:2020:i:c:p:262-273
    DOI: 10.1016/j.jbusres.2020.07.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296320305002
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2020.07.045?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. Charles C. Manz & Greg L. Stewart, 1997. "Attaining Flexible Stability by Integrating Total Quality Management and Socio-Technical Systems Theory," Organization Science, INFORMS, vol. 8(1), pages 59-70, February.
    2. 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.
    3. Mukherjee, Debmalya & Lahiri, Somnath & Ash, Steven R. & Gaur, Ajai S., 2019. "Search motives, local embeddedness, and knowledge outcomes in offshoring," Journal of Business Research, Elsevier, vol. 103(C), pages 365-375.
    4. Brougham, David & Haar, Jarrod, 2018. "Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace," Journal of Management & Organization, Cambridge University Press, vol. 24(2), pages 239-257, March.
    5. Desouza, Kevin C. & Dawson, Gregory S. & Chenok, Daniel, 2020. "Designing, developing, and deploying artificial intelligence systems: Lessons from and for the public sector," Business Horizons, Elsevier, vol. 63(2), pages 205-213.
    6. Robert D. Dewar & Jane E. Dutton, 1986. "The Adoption of Radical and Incremental Innovations: An Empirical Analysis," Management Science, INFORMS, vol. 32(11), pages 1422-1433, November.
    7. 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.
    8. Prithwiraj Choudhury & Evan Starr & Rajshree Agarwal, 2020. "Machine learning and human capital complementarities: Experimental evidence on bias mitigation," Strategic Management Journal, Wiley Blackwell, vol. 41(8), pages 1381-1411, August.
    9. Michael Barrett & Eivor Oborn & Wanda J. Orlikowski & JoAnne Yates, 2012. "Reconfiguring Boundary Relations: Robotic Innovations in Pharmacy Work," Organization Science, INFORMS, vol. 23(5), pages 1448-1466, October.
    10. Morgan-Thomas, Anna & Dessart, Laurence & Veloutsou, Cleopatra, 2020. "Digital ecosystem and consumer engagement: A socio-technical perspective," Journal of Business Research, Elsevier, vol. 121(C), pages 713-723.
    11. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    12. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    13. Briggs, Elten & Deretti, Sandro & Kato, Heitor Takashi, 2020. "Linking organizational service orientation to retailer profitability: Insights from the service-profit chain," Journal of Business Research, Elsevier, vol. 107(C), pages 271-278.
    14. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    15. Matzner, Martin & Büttgen, Marion & Demirkan, Haluk & Spohrer, Jim & Alter, Steven & Fritzsche, Albrecht & Ng, Irene C. L. & Jonas, Julia M. & Martinez, Veronica & Möslein, Kathrin M. & Neely, Andy, 2018. "Digital Transformation in Service Management," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 2(2), pages 3-21.
    16. George P. Huber, 1991. "Organizational Learning: The Contributing Processes and the Literatures," Organization Science, INFORMS, vol. 2(1), pages 88-115, February.
    17. Michael Haenlein & Andreas Kaplan & Chee-Wee Tan & Pengzhu Zhang, 2019. "Artificial intelligence (AI) and management analytics," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(4), pages 341-343, October.
    18. Kaplan, Andreas & Haenlein, Michael, 2020. "Rulers of the world, unite! The challenges and opportunities of artificial intelligence," Business Horizons, Elsevier, vol. 63(1), pages 37-50.
    19. Hirokazu Shirado & Nicholas A. Christakis, 2017. "Locally noisy autonomous agents improve global human coordination in network experiments," Nature, Nature, vol. 545(7654), pages 370-374, May.
    20. Sigala, Marianna, 2020. "Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research," Journal of Business Research, Elsevier, vol. 117(C), pages 312-321.
    21. 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.
    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. 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. 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.
    4. Yasheng Chen & Mohammad Islam Biswas, 2021. "Turning Crisis into Opportunities: How a Firm Can Enrich Its Business Operations Using Artificial Intelligence and Big Data during COVID-19," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    5. Cristian-Mihai Vidu & Florina Pinzaru & Andreea Mitan, 2022. "What managers of SMEs in the CEE region should know about challenges of artificial intelligence’s adoption? – an introductive discussion," Nowoczesne Systemy Zarządzania. Modern Management Systems, Military University of Technology, Faculty of Security, Logistics and Management, Institute of Organization and Management, issue 1, pages 63-76.
    6. Toorajipour, Reza & Sohrabpour, Vahid & Nazarpour, Ali & Oghazi, Pejvak & Fischl, Maria, 2021. "Artificial intelligence in supply chain management: A systematic literature review," Journal of Business Research, Elsevier, vol. 122(C), pages 502-517.
    7. Carsten Østerlund & Mohammad Hossein Jarrahi & Matthew Willis & Karen Boyd & Christine T. Wolf, 2021. "Artificial intelligence and the world of work, a co‐constitutive relationship," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 128-135, January.
    8. 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.
    9. 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.
    10. Pietronudo, Maria Cristina & Croidieu, Grégoire & Schiavone, Francesco, 2022. "A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    11. Jiménez-Jiménez, Daniel & Sanz-Valle, Raquel, 2011. "Innovation, organizational learning, and performance," Journal of Business Research, Elsevier, vol. 64(4), pages 408-417, April.
    12. Berk Kaan Kuguoglu & Haiko van der Voort & Marijn Janssen, 2021. "The Giant Leap for Smart Cities: Scaling Up Smart City Artificial Intelligence of Things (AIoT) Initiatives," Sustainability, MDPI, vol. 13(21), pages 1-16, November.
    13. 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).
    14. Ana Labella-Fernández, 2021. "Archetypes of Green-Growth Strategies and the Role of Green Human Resource Management in Their Implementation," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
    15. Kinkel, Steffen & Capestro, Mauro & Di Maria, Eleonora & Bettiol, Marco, 2023. "Artificial intelligence and relocation of production activities: An empirical cross-national study," International Journal of Production Economics, Elsevier, vol. 261(C).
    16. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
    17. Eelke Wiersma, 2007. "Conditions That Shape the Learning Curve: Factors That Increase the Ability and Opportunity to Learn," Management Science, INFORMS, vol. 53(12), pages 1903-1915, December.
    18. Younès El Manzani & Mohamed Larbi Sidmou & Jean-Jack Cegarra, 2018. "Does IS0 9001 quality management system support product innovation? An analysis from the sociotechnical systems theory," Post-Print hal-03080217, HAL.
    19. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    20. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.

    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:jbrese:v:120:y:2020:i:c:p:262-273. 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/jbusres .

    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.