This chapter explores how organisations can strategically adapt to the integration of artificial intelligence (AI) in knowledge management (KM). It argues that successful adoption requires more than technological deployment; it demands alignment of strategy, structure, and culture to create resilient and future-ready knowledge ecosystems. Three key drivers – accelerated decision-making, knowledge democratisation, and competitive pressure – highlight the urgency of adaptation. Building on these, the chapter presents five strategies for AI-driven KM: articulating a clear vision and roadmap, investing in change management, fostering cross-functional collaboration, adopting agile methodologies, and developing robust ethical and governance frameworks. Case studies of Tesla and General Electric (GE) illustrate how AI–KM integration enables continuous learning, predictive maintenance, collaborative innovation, and sustained competitiveness. The chapter concludes that resilience – achieved through reskilling, human–AI collaboration, and future-proofed systems – is essential for navigating uncertainty and capturing the opportunities of AI in KM. Organisations that embed AI into their knowledge processes will not only adapt effectively but also lead in shaping the future of knowledge-driven performance.

Rezaei, M., Strategies for Organisational Adaptation, in Rezaei, M. (ed.), Knowledge Management in the AI Era: Evolution, Challenges, and Strategic Adaptation, Emerald Group Publishing Ltd., Leeds 2026: 175- 190. 10.1108/978-1-80686-251-120261007 [https://hdl.handle.net/10807/332986]

Strategies for Organisational Adaptation

Rezaei, Mojtaba
Primo
2026

Abstract

This chapter explores how organisations can strategically adapt to the integration of artificial intelligence (AI) in knowledge management (KM). It argues that successful adoption requires more than technological deployment; it demands alignment of strategy, structure, and culture to create resilient and future-ready knowledge ecosystems. Three key drivers – accelerated decision-making, knowledge democratisation, and competitive pressure – highlight the urgency of adaptation. Building on these, the chapter presents five strategies for AI-driven KM: articulating a clear vision and roadmap, investing in change management, fostering cross-functional collaboration, adopting agile methodologies, and developing robust ethical and governance frameworks. Case studies of Tesla and General Electric (GE) illustrate how AI–KM integration enables continuous learning, predictive maintenance, collaborative innovation, and sustained competitiveness. The chapter concludes that resilience – achieved through reskilling, human–AI collaboration, and future-proofed systems – is essential for navigating uncertainty and capturing the opportunities of AI in KM. Organisations that embed AI into their knowledge processes will not only adapt effectively but also lead in shaping the future of knowledge-driven performance.
2026
Inglese
Knowledge Management in the AI Era: Evolution, Challenges, and Strategic Adaptation
9781806862528
9781806862511
9781806862535
Emerald Group Publishing Ltd.
Rezaei, M., Strategies for Organisational Adaptation, in Rezaei, M. (ed.), Knowledge Management in the AI Era: Evolution, Challenges, and Strategic Adaptation, Emerald Group Publishing Ltd., Leeds 2026: 175- 190. 10.1108/978-1-80686-251-120261007 [https://hdl.handle.net/10807/332986]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/332986
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