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A Knowledge Management Perspective of Generative Artificial Intelligence
Citation. Alavi, M., Leidner, D. E., & Mousavi, R. (2024). A knowledge management perspective of generative artificial intelligence. Journal of the Association for Information Systems, 25(1), 1–12. https://doi.org/10.17705/1jais.00859
Summary. This editorial uses knowledge management to examine how generative AI may affect knowledge creation, storage, transfer, and application in organizations. It identifies potential gains in information processing, learning, productivity, and innovation alongside risks involving bias, overreliance, sensitive-information dissemination, intellectual property, and reduced human socialization. It argues for integrating generative-AI capabilities with human insight and ethical responsibility.
Key claims
- Generative AI can reshape organizational knowledge creation, storage, transfer, and application by changing information processing, retrieval, training, and use.
- Potential knowledge-management benefits coexist with risks of AI bias, overreliance, diminished human socialization, knowledge misapplication, sensitive-information exposure, intellectual-property problems, and ethical failures.
- Effective organizational use requires balancing AI-generated explicit knowledge with human-derived tacit knowledge and human insight.
Evidence & limitations
- Editorial conceptual analysis rather than an empirical study; the article revisits Alavi and Leidner (2001) as its knowledge-management lens and does not test the proposed opportunities or risks.
- Published in a peer-reviewed journal, but the claims are framing propositions and design considerations rather than causal estimates.