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Exploring the Productivity Impacts of Generative AI in Organizations

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Disruptive Innovation in a Digitally Connected Healthy World (I3E 2024)

Abstract

This research paper explores the impact of Generative AI (GenAI) on human productivity within organizations, focusing on the perspective of employees. Using an exploratory case-study method, we conducted semi-structured interviews with 17 participants from various roles to understand how GenAI impacts work process and productivity. Our findings suggest that these tools can automate routine tasks and enable new workers to acquire skills rapidly, but that GenAI adoption may also entail time-consuming upskilling for individuals and undermined team workflow. Furthermore, by employing a Human Resources Management (HRM) perspective, this paper contributes to the Information Systems (IS) literature by offering a nuanced understanding of the organizational impacts of GenAI, suggesting that a balanced approach seems essential to maximize the potential benefits while limiting the drawbacks of these new tools.

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References

  1. Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., Chen, L.: Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. vol. 25, ed: Taylor & Francis, pp. 277–304. (2023)

    Google Scholar 

  2. Lim, W.M., Gunasekara, A., Pallant, J.L., Pallant, J.I., Pechenkina, E.: Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. Int. J. Manage. Educ. 21(2), 100790 (2023)

    Google Scholar 

  3. Prasad Agrawal, K.: Towards adoption of Generative AI in organizational settings. J. Comput. Inf. Syst. 64, 1–16 (2023)

    Google Scholar 

  4. Liang, J.T., Yang, C., Myers, B.A.: A large-scale survey on the usability of ai programming assistants: Successes and challenges. In: Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, pp. 1–13. (2024)

    Google Scholar 

  5. Simkute, A., Tankelevitch, L., Kewenig, V., Scott, A.E., Sellen, A., Rintel, S.: Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions. arXiv preprint arXiv:2402.11364 (2024)

  6. Candelon, F., Krayer, L., Rajendran, S., Martinez, D.Z.: How People Can Create–and Destroy–Value with Generative AI. BCG Global, vol. 21, (2023)

    Google Scholar 

  7. Dhoni, P.: Unleashing the Potential: Overcoming Hurdles and Embracing Generative AI in IT Workplaces: Advantages, Guidelines, and Policies. Authorea Preprints (2023)

    Google Scholar 

  8. Cardon, P.W., Getchell, K., Carradini, S., Fleischmann, C., Stapp, J.: Generative AI in the Workplace: Employee Perspectives of ChatGPT Benefits and Organizational Policies. (2023)

    Google Scholar 

  9. Rane, N.: Role and challenges of ChatGPT, Gemini, and similar generative artificial intelligence in human resource management. Stud. Econ. Bus. Relat. 5(1), 11–23 (2024)

    Article  Google Scholar 

  10. Aral, S., Brynjolfsson, E., Wu, D.: Which came first, it or productivity? Virtuous cycle of investment and use in enterprise systems. Virtuous cycle of investment and use in enterprise systems (2020)

    Google Scholar 

  11. Bruce, D.F., et al.: Unlocking the potential of generative AI: Three key questions for government agencies. McKinsey’s Public Sector Practice, 2023. [Online]. Available: https://www.mckinsey.com/industries/public-sector/our-insights/unlocking-the-potential-of-generative-ai-three-key-questions-for-government-agencies

  12. Shook, E.D., Paul.: Work, Workforce, Workers Age of Generative AI Report. Accenture (2024)

    Google Scholar 

  13. Brynjolfsson, E., Li, D., Raymond, L.R.: Generative AI at work. In: Working Paper Series, National Bureau of Economic Research, No. 31161, issue Working Paper Series (2023)

    Google Scholar 

  14. Imai, S.: Is github copilot a substitute for human pair-programming? an empirical study. In: Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings. pp. 319–321. (2022)

    Google Scholar 

  15. Dakhel, A.M., Majdinasab, V., Nikanjam, A., Khomh, F., Desmarais, M.C., Jiang, Z.M.J.: Github copilot ai pair programmer: Asset or liability? J. Syst. Softw. 203, 111734 (2023)

    Article  Google Scholar 

  16. Ebert, C., Louridas, P.: Generative AI for software practitioners. IEEE Softw. 40(4), 30–38 (2023)

    Article  Google Scholar 

  17. Sabherwal, R., Grover, V.: The Societal Impacts of Generative Artificial Intelligence: A Balanced Perspective. J. Assoc. Inf. Syst. 25(1), 13–22 (2024)

    Google Scholar 

  18. March, S.T., Smith, G.F.: Design and natural science research on information technology. Decis. Support Syst. 15(4), 251–266 (1995)

    Article  Google Scholar 

  19. Oates, B.J., Griffiths, M., McLean, R.: Researching information systems and computing. Sage (2022)

    Google Scholar 

  20. Diefenbach, T.: Are case studies more than sophisticated storytelling?: Methodological problems of qualitative empirical research mainly based on semi-structured interviews. Qual. Quant. 43, 875–894 (2009)

    Article  Google Scholar 

  21. Armstrong, M., Taylor, S.: Armstrong's handbook of human resource management practice. Kogan Page Publishers (2020)

    Google Scholar 

  22. Takagi, S., Watari, T., Erabi, A., Sakaguchi, K.: Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: comparison study. JMIR Med. Educ. 9(1), e48002 (2023)

    Google Scholar 

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Correspondence to Benjamin Semujanga .

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Semujanga, B., Mikalef, P. (2024). Exploring the Productivity Impacts of Generative AI in Organizations. In: van de Wetering, R., et al. Disruptive Innovation in a Digitally Connected Healthy World. I3E 2024. Lecture Notes in Computer Science, vol 14907. Springer, Cham. https://doi.org/10.1007/978-3-031-72234-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-72234-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-72233-2

  • Online ISBN: 978-3-031-72234-9

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