Authors : Revina Nida Nafila; Agnesia Candra Sulyani; Prasetyo Raharjo; Muhammad Subhan Iswahyudi

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/34kycrf9

Scribd : https://tinyurl.com/y2ut8njz

DOI : https://doi.org/10.5281/zenodo.14800375

Abstract : AI is increasingly becoming a transformational technology for businesses and organizations. AI may be useful to a business organization for quite wide of areas, particularly regarding organizational learning, innovation, and research. This research perform a systematic literature review of AI in organizational learning, innovation, and research relating to past research, emerging trends, keywords, and research gaps available within the field. The basis for this study has been done through research using 116 articles from Scopus, dated between 2016 and 2024. The results of the study have indicated that AI is a basic technology that enhances processes to learn, innovate, and research. Therefore, there is more automation and personalization in employee training and effectiveness in data analysis for creating innovations. This indicated how much AI intervention contributes to changing the way an enterprise learns, innovates, or simply carries out research. Based on this study, areas concerned with the measurement gaps, the technical perspective, and the ethical point of view involve increased research. Results from this study contribute to a more specific understanding of what drives the evolution of AI in the processes of organizational learning, innovation, and research and, therefore, inform academics and practitioners how to integrate AI technologies into learning, innovation, and research programs.

Keywords : Artificial Intelligence; Bibliometric Analysis; Learning; Organization; Innovation; Research; Machine Learning; Technology Adoption.

References :

1. Clark, D. (2024). Artificial Intelligence for Learning: Using AI and Generative AI to Support Learner Development (2nd ed). London: Kogan Page 
2. Otto, F., Kling, N., Schumann, C.A., & Tittmann, C. (2023). A conceptual approach to an AI based adaptive study support system for individualized higher education. iJAC, 16(2), 69-80. DOI https://doi.org/10.3991/ijac.v16i2.35699 
3. Zhai, X., Chu, X., Chai, C.S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.B., Yuan, J., & Li, Y            (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020.  Complexity, 2021(6): 1-18. DOI http://dx.doi.org/10.1155/2021/8812542 
4. Bowen, J.A., & Watson, C. E. (2024). Teaching with AI: A Practical Guide to a New Era of Human Learning. Baltimore: Johns Hopkins University Press
5. Pavitra, K. H., Agnihorti, A. (2023). Artificial Intelligence in Corporate Learning and Development: Current Trends and Future Possibilities, 2023 Second International            Conference On Smart Technologies For Smart Nation (SmartTechCon), pp. 688-693. DOI: 10.1109/SmartTechCon57526.2023.10391698   
6. Deloitte. (2024). Deloitte Human Capital Trends. Thriving Beyond Boundaries: Human Performance in a Boundaryless World. Deloitte Insights. Retrieved from https://www2.deloitte.com/us/en/insights/focus/human-capital-trends.html
7. Sahoo, S.,  Kumar, S., Donthu, N., Singh, A. K. (2024). Artificial intelligence capabilities, open innovation, and business performance – Empirical insights from multinational B2B companies. Industrial Marketing Management, 117, 28-41. DOI https://doi.org/10.1016/j.indmarman.2023.12.008 
8. Chubb, J., Cowling, P., & Reed, D. (2021). Exploring the use of AI in the research process. AI & Society, 37, 1439-1457. DOI https://doi.org/10.1007/s00146-021-01259-0 
9. Bersin, J. (2024, March). The $340 billion corporate learning industry is poised for disruption. Josh Bersin Insights. Retrieved from https://joshbersin.com/2024/03/the-340-billion-corporate-learning-industry-is-poised-for-disruption/
10. Stanford University. (2024). Human-Centered Artificial Intelligence: Artificial Intelligence Index Report. https://aiindex.stanford.edu/report/ 
11. Alawamleh, M., Shammas, N.,  Alawamleh, K., & Ismail, L. (2024). Examining the limitations of AI in business and the need for human insights using Interpretive Structural Modelling. Journal of Open Innovation: Technology, Market, and Complexity, 10(3), 1-17. DOI: https://doi.org/10.1016/j.joitmc.2024.100338
12. Ahmed, S., Priyadharshini, L., Hosen, M. S., Ng, A., Islam, S., & Manik. J. A. (2024). The Impact Of Artificial Intelligence On Business & Social Values: Benefits, Challenges, And Future Directions. Educational Administration: Theory and Practice, 30(6), 3174-3180. DOI: https://doi.org/10.53555/kuey.v30i6.6012
13. Bhatt, P., & & Muduli, A. (2022). Artificial intelligence in learning and development: a systematic literature review. European Journal of Training and Development, 47(5). DOI: http://dx.doi.org/10.1108/EJTD-09-2021-0143 
14. Harry, A, & Sayudin. (2023). Role of AI in education. Injurity: Interdisciplinary Journal and Humanity, 2(3), 260-268. DOI https://doi.org/10.58631/injurity.v2i3.52 
15. Hughes, C., Robert, L., Frady, K., Arroyos, A., (2019), Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes. Managing Technology and Middle-and Low-skilled Employees (The Changing Context of Managing People), Emerald    Publishing Limited, pp. 61-68. DOI https://doi.org/10.1108/978-1-78973-077-720191005 
16. Rao, S., Chitranshi, J., & Punjabi, N. (2020). Role of Artificial Intelligence in Employee Engagement and Retention. Journal of Applied Management- Jidnyasa, 12(2), 42–60. http://www.simsjam.net/index.php/Jidnyasa/article/view/156902
17. Maity, S. (2019). Identifying opportunities for artificial intelligence in the evolution of training and development practices. Journal of Management, 38(8), 651-663. DOI: https://doi.org/10.1108/JMD-03-2019-0069 
18. Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and          innovation management: A review, framework, and research agenda. Technological Forecasting & Social Change, 1-10. DOI https://doi.org/10.1016/j.techfore.2020.120392 
19. Kumar, V., Kumar, S., Chatterjee, S., & Mariani, M. (2024). Artificial Intelligence (AI) capabilities and the R&D performance of organizations: the moderating role of environmental dynamism. IEEE Transaction on Engineering Management, 71, 11522-11532. DOI https://doi.org/10.1109/TEM.2024.3423669 
20. Ezzaim, A., Dahbi, A., Aqqal, A., & Haidine, A. (2024). AI‑based learning style detection in adaptive learning systems: a systematic literature review. Journal of Computers in Education. DOI https://doi.org/10.1007/s40692-024-00328-9 
21. Aras, A., & Büyüközkan, G. (2023). Digital Transformation Journey Guidance: A Holistic Digital Maturity Model Based on a Systematic Literature Review Systems, 11(4), 213. DOI https://doi.org/10.3390/systems11040213