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How Organizations Legitimize AI Led Organizational Change?

  • Gyeung-min Kim (College of Business, Ewha Womans University) ;
  • Heesun Kim (Hyundai Autoever IT Service Innovation Team)
  • Received : 2022.03.31
  • Accepted : 2022.05.23
  • Published : 2022.09.30

Abstract

AI is recognized to be a key technology for digital transformation (DT) and the value of AI is considered to determine the future of the company. However, in reality, although managers acknowledge the future value of AI and have plans to introduce it, most are not sure what to expect from AI or how to apply it to their business. This study compares two company cases to demonstrate how an organization has successfully achieved AI led organizational change while another failed. Specifically, by taking institutionalist's view, this study examines how the legitimacy enables and constrains AI led organizational changes in organization's practices, processes, and infrastructure. The results of this study indicate that for the success of AI led organizational changes, the legitimacy plays an important role by reducing the challenges from stakeholders and increasing the institutional momentum to move through the phases of the change.

Keywords

References

  1. Ashforth, B., and Gibbs, B. (1990). The double edge of organizational legitimation. Organization Science, 1(2), 177-194. https://doi.org/10.1287/orsc.1.2.177
  2. Collier, A. (1994). Critical Realism: An Introduction to Roy Bhaskar's Philosophy. Verso, London, UK.
  3. Daugherty, P., and Wilson, J. (2018). Human + Machine: Reimagining work in the age of AI. Harvard Business Review, March 20.
  4. Davenport, T., and Ronanki, R. (2018). Artificial Intelligence for the Real World. Harvard Business Review, January-February.
  5. Deephouse, D., Bundy, J., Tost, L., and Suchman, M. (2017). Organizational legitimacy: Six key questions. In R. Greenwood, C. Oliver, T. Lawrence, and R. Meyer (Eds.), The SAGE Handbook of Organizational Institutionalism. SAGE, London, 27-54.
  6. Dimaggio, P. Powell, W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American sociological review, 48, April, 147-160.
  7. Eisenhardt, K. (1989). Building Theories from Case Study Research. Academy of Management Review, 14(4), 532-555. https://doi.org/10.2307/258557
  8. Frey, B., and Osborne, M. (2013). The Future of Employment: How susceptible are jobs to computerization, Retrieved from https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf
  9. Gartner, (2021). Gartner top strategic technology trend for 2021, Retrieved from https://www.gartner.com/smarterwithgartner/gartner-top-strategic-technology-trends-for-2021
  10. Glaser, B., and Strauss, A. (1999). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine Transaction, New Brunswick, N.J.
  11. Gupta, S., Qian, X., Bhushan, B., and Luo, Z. (2019). Role of cloud ERP and Big Data on firm performance: A dynamic capability view theory perspective. Management Decision, 57(8), 1857-1882. https://doi.org/10.1108/MD-06-2018-0633
  12. Harari, Y. (2017). Homodeus: A Brief History of Tomorrow. HarperCollins, NY.
  13. Hofstede, G. (1980). Culture and Organizations. International Studies of Management & Organization, 10(4), 15-41. https://doi.org/10.1080/00208825.1980.11656300
  14. Holliday, A. (2007). Doing and Writing Qualitative Research, 2nd ed., London.
  15. Kieser, A. (1994). Why organization theory needs historical analyses: An how this should be performed. Organization Science, 5(4), 608-620. https://doi.org/10.1287/orsc.5.4.608
  16. Leigh, P. (2011). An integrative model of legitimacy judgements. Academy of Management Review, 36(4), 686-710. https://doi.org/10.5465/amr.2010.0227
  17. Lamb, R., and Kling, R. (2003). Reconceptualizing users as social actors in information systems research. MIS Quarterly, 27(2), 197-235. https://doi.org/10.2307/30036529
  18. Meyer, J., and Rowan, B. (1977). Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology, 83(2), 340-363. https://doi.org/10.1086/226550
  19. Mikalef, P., Krogstie, J., Pappas, I., and Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information and Management, 57(2), 1-15. https://doi.org/10.1016/j.im.2019.05.004
  20. Pettigrew, A. (1990). Longitudinal Field Research on Change: Theory and Practice. Organization Science, 1(3), 267-292.
  21. Porter, M., and Heppelmann, J. (2014). How smart, connected products are transforming competition. Harvard Business Review, November, 1-23.
  22. Porter, M., and Heppelmann, J. (2015). How smart, connected products are transforming companies. Harvard Business Review, October. competition 2014, 97-114.
  23. Ransbotham, S., Kiron, D. Gerbert, P., and Reeves, M. (2017). Reshaping business with artificial intelligence. MIT Sloan Management Review; Fall.
  24. Ross, J., Sebastian, I., and Beath, C. (2017). How to develop a great digital strategy. MIT Sloan Management Review, 53(2), Winter, 7-9.
  25. Sebastian, I., Moloney, K., Ross, J., Fonstad, N., Beath, C., and Mocker, M. (2017). How big old companies navigate digital transformation. MIS Quarterly Executive, 16(3), 197-213.
  26. Scott, R. (2001). Institutions and Organizations. Sage Publications.
  27. Suchman, M. C. (1995). Managing legitimacy: Strategic and institutional approaches. Academy of Management Review, 20(3), 571-610. https://doi.org/10.2307/258788
  28. Tarafdar, M., Beath, C., and Ross, J. (2019). Using AI to enhance business operations. MIT Sloan Management Review, 50(4), Summer, 37-44.
  29. Volkoff, O., and Strong, D. (2013). Critical realism and affordances: Theorizing it-associated organizational change processes. MIS Quarterly, 37(3), 819-834. https://doi.org/10.25300/MISQ/2013/37.3.07
  30. Yin, R. (1994). Case Study Research: Design and Methods, Sage Publications Inc., New York, CA.