Artificial Intelligence and Knowledge Management: A Systematic Literature Review
DOI:
https://doi.org/10.54097/71afqq29Keywords:
Artificial Intelligence, Knowledge Management, Knowledge Discovery, Knowledge SharingAbstract
Against the global backdrop of widespread informatization and intelligent transformation, artificial intelligence (AI) technology, with its advanced data processing and analytical capabilities, is fundamentally reshaping knowledge management models across industries. As a core approach to enhancing organizational innovation capacity and market competitiveness, the integration of knowledge management with artificial intelligence has emerged as a prominent research hotspot in both academic research and practical application. Exploring the disruptive impact of AI on enterprise knowledge management will also become a critical trend in future research. This paper systematically reviews extant research on AI and knowledge management, and synthesizes relevant literature across multiple core dimensions, including knowledge discovery, knowledge flow, knowledge sharing, and knowledge innovation.
Downloads
References
[1] Taherdoost, H., & Madanchian, M. (2023). Artificial intelligence and knowledge management: Impacts, benefits, and implementation. Computers, 12(4), 72. https://doi.org/10.3390/computers12040072
[2] Lee, C.-P., Lee, G.-G., & Lin, H.-F. (2007). The role of organizational capabilities in successful e-business implementation. Business Process Management Journal, 13(5), 677–693. https://doi.org/10.1108/14637150710782370
[3] Storey, V. C. (2025). Knowledge management in a world of generative AI: Impact and implications. ACM Transactions on Management Information Systems, 16(3), 1–14. https://doi.org/10.1145/3721126
[4] Panda, M., & Puri, R. (2025). Understanding the role of artificial intelligence in knowledge management systems: A systematic review using the antecedent, consequences and intervention framework. Journal of Work-Applied Management, 18(1), 81–103. https://doi.org/10.1108/JWAM-08-2024-0125
[5] Kovačić, M., Mutavdžija, M., Buntak, K., et al. (2022). Using artificial intelligence for creating and managing organizational knowledge. Tehnički vjesnik, 29(4), 1413–1418. https://doi.org/10.17559/TV-20211220103459
[6] Mittal, A., Singh, S., & Rajest, S. S. (2023). Role of artificial intelligence in knowledge management: An empirical study of industry experts using stepwise multiple regression. International Journal of Electronic Finance, 12(4), 403–422. https://doi.org/10.1504/IJEF.2023.133695
[7] Hossein, M. J., David, A., Ali, E., et al. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87–99. https://doi.org/10.1016/j.bushor.2022.09.003
[8] Liu, Y., Ying, Z., Ying, Y., et al. (2024). Artificial intelligence orientation and internationalization speed: A knowledge management perspective. Technological Forecasting and Social Change, 205, 123517. https://doi.org/10.1016/j.techfore.2024.123517
[9] Lea, I., Chiara, N., Francesca, V., et al. (2024). Supporting the implementation of AI in business communication: The role of knowledge management. Journal of Knowledge Management, 28(1), 85–95. https://doi.org/10.1108/JKM-01-2023-0064
[10] Piad-Morffis, A., Gutiérrez, Y., Almeida-Cruz, Y., et al. (2020). A computational ecosystem to support ehealth knowledge discovery technologies in Spanish. Journal of Biomedical Informatics, 109, 103517. https://doi.org/10.1016/j.jbi.2020.103517
[11] Guodong, L., Zhang, Q., Ding, Y., et al. (2020). Research on service discovery methods based on knowledge graph. IEEE Access, 8, 138934–138943. https://doi.org/10.1109/ACCESS.2020.3012642
[12] Linsel, A., Bär, K., Haas, J., et al. (2020). GeoReVi: A knowledge discovery and data management tool for subsurface characterization. SoftwareX, 12, 100597. https://doi.org/10.1016/j.softx.2020.100597
[13] Abe, N., Liu, H., & Wang, K. (2021). Innovations and perspectives in data mining and knowledge discovery. Frontiers in Big Data, 3, 637906. https://doi.org/10.3389/fbigd.2020.637906
[14] Schatz, K., Melo-Filho, C., Tropsha, A., et al. (2021). Explaining drug-discovery hypotheses using knowledge-graph patterns. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 3709–3714). IEEE. https://doi.org/10.1109/BigData52589.2021.9619447
[15] Oliveira Jr, O. N., & Oliveira, M. C. F. (2022). Materials discovery with machine learning and knowledge discovery. Frontiers in Chemistry, 10, 930369. https://doi.org/10.3389/fchem.2022.930369
[16] Shu, X., & Ye, Y. (2023). Knowledge discovery: Methods from data mining and machine learning. Social Science Research, 110, 102817. https://doi.org/10.1016/j.ssresearch.2023.102817
[17] Liu, Q. (2022). Analysis of collaborative driving effect of artificial intelligence on knowledge innovation management. Scientific Programming, 2022, 8223724. https://doi.org/10.1155/2022/8223724
[18] Malik, A., De Silva, M. T. T., Budhwar, P., et al. (2021). Elevating talents' experience through innovative artificial intelligence-mediated knowledge sharing: Evidence from an IT-multinational enterprise. Journal of International Management, 27(4), 100871. https://doi.org/10.1016/j.intman.2021.100871
[19] Olan, F., Arakpogun, E. O., Suklan, J., et al. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605–615. https://doi.org/10.1016/j.jbusres.2022.03.046
[20] Li, N., Yan, Y., Yang, Y., et al. (2022). Artificial intelligence capability and organizational creativity: The role of knowledge sharing and organizational cohesion. Frontiers in Psychology, 13, 845277. https://doi.org/10.3389/fpsyg.2022.845277
[21] Mohammed, T., Naas, S. A., Sigg, S., et al. (2022). Knowledge sharing in AI services: A market-based approach. IEEE Internet of Things Journal, 10(2), 1320–1331. https://doi.org/10.1109/JIOT.2022.3214476
[22] Binsaeed, R. H., Yousaf, Z., Grigorescu, A., et al. (2023). Knowledge sharing key issue for digital technology and artificial intelligence adoption. Systems, 11(7), 316. https://doi.org/10.3390/systems11070316
[23] Neştian, A. Ș., Tiţă, S. M., & Guţă, A. L. (2020). Incorporating artificial intelligence in knowledge creation processes in organizations. In Proceedings of the International Conference on Business Excellence (Vol. 14, No. 1, pp. 597–606). https://doi.org/10.2478/picbe-2020-0056
[24] Zhang, X., Liu, Z., Cheng, Y., et al. (2023). The impact of AIGC on organizational knowledge creation: From the perspective of adaptive structuration theory. In 2023 IEEE International Conference on Data Mining Workshops (ICDMW) (pp. 1469–1476). IEEE. https://doi.org/10.1109/ICDMW60846.2023.00194
[25] Alavi, M., Leidner, D., & Mousavi, R. (2024). Knowledge management perspective of generative artificial intelligence (GenAI). (pp. 1–12).
[26] Bai, X. J., & Li, J. J. (2020). The best configuration of collaborative knowledge innovation management from the perspective of artificial intelligence. Knowledge Management Research & Practice. https://doi.org/10.1080/14778238.2020.1814642
[27] Pai, R. Y., Shetty, A., Shetty, A. D., et al. (2022). Integrating artificial intelligence for knowledge management systems–synergy among people and technology: A systematic review of the evidence. Economic Research-Ekonomska Istraživanja, 35(1), 7043–7065. https://doi.org/10.1080/1331677X.2022.2068237
[28] Zhou, H., Erol-Kantarci, M., & Poor, H. V. (2022). Knowledge transfer and reuse: A case study of AI-enabled resource management in RAN slicing. IEEE Wireless Communications, 30(5), 160–169. https://doi.org/10.1109/MWC.001.2200087
[29] Alves, V. M., Korn, D., Pervitsky, V., et al. (2022). Knowledge-based approaches to drug discovery for rare diseases. Drug Discovery Today, 27(2), 490–502. https://doi.org/10.1016/j.drudis.2021.10.021
[30] Sahay, K. S., Goel, S., et al. (2021). Advances in secure knowledge management in the artificial intelligence era. Information Systems Frontiers, 23(4), 1–4. https://doi.org/10.1007/s12526-021-09578-1
[31] Aanchal, S., Tushar, T., Divyansh, P., et al. (2022). Knowledge management and ethical vulnerability in AI. AI and Ethics. https://doi.org/10.1007/s43681-022-00177-4
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
