Have a personal or library account? Click to login
Generative Artificial Intelligence as an Enabler of Organizational Ambidexterity in the Knowledge Economy Cover

Generative Artificial Intelligence as an Enabler of Organizational Ambidexterity in the Knowledge Economy

By: Sapan Tiwari,  Dharmam Buch and  Aditi Rao  
Open Access
|Mar 2026

References

  1. Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
  2. Argyris, Ch., & Schön, D. A. (1997). Organizational learning: A theory of action perspective. Reis, 77/78, 345–348. https://doi.org/10.2307/40183951
  3. Brynjolfsson, E., & McAfee, A. (2016). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
  4. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553p
  5. Davenport, T. H., & Kirby, J. (2016). Only humans need apply: winners and losers in the age of smart machines (1st ed.). Harper Business.
  6. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, Article 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
  7. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
  8. Kanitz, R., Gonzalez, K., Briker, R., & Straatmann, T. (2023). Augmenting organizational change and strategy activities: Leveraging generative artificial intelligence. The Journal of Applied Behavioral Science, 59(3), 345-363. https://doi.org/10.1177/00218863231168974
  9. March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
  10. McKinsey Global Institute. (2023). The economic potential of generative AI: The next productivity frontier. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
  11. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), Article e1000097. https://doi.org/10.1371/journal.pmed.1000097
  12. OECD. (2023). OECD digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
  13. O’Reilly, C. A., & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. https://doi.org/10.5465/amp.2013.0025
  14. Oswick, C. (2024). Generative artificial intelligence and generative conversations: Contrasting futures for organizational change? The Journal of Applied Behavioral Science, 60(2), 225-229. https://doi.org/10.1177/00218863241232412
  15. Raisch, S., & Birkinshaw, J. (2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34(3), 375–409. https://doi.org/10.1177/0149206308316058
  16. Santoni de Sio, F. (2024). Artificial intelligence and the future of work: Mapping the ethical issues. The Journal of Ethics, 28(3), 407–427. https://doi.org/10.1007/s10892-024-09493-6
  17. Teece, D. J. (2018). Dynamic capabilities as (workable) management systems theory. Journal of Management & Organization, 24(3), 359–368. https://doi.org/10.1017/jmo.2017.75
  18. UNESCO. (2022). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000381137
  19. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
  20. World Economic Forum. (2020). The future of jobs report 2020. https://www.weforum.org/publications/the-future-of-jobs-report-2020/
  21. Zavrazhnyi, K., Kulyk, A., & Antunes de Abreu, O. (2024). The innovative impact of generative artificial intelligence on digital business transformation. Economics of Systems Development, 6(2), 63–70. https://doi.org/10.32782/2707-8019/2024-2-9
DOI: https://doi.org/10.2478/mdke-2026-0003 | Journal eISSN: 2392-8042 | Journal ISSN: 2286-2668
Language: English
Page range: 40 - 53
Submitted on: Oct 27, 2025
|
Accepted on: Feb 3, 2026
|
Published on: Mar 23, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Sapan Tiwari, Dharmam Buch, Aditi Rao, published by Scoala Nationala de Studii Politice si Administrative
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.