Ethical Considerations in AI-Driven Knowledge Management: Navigating Challenges in the Modern Business Landscape

Abstract Artificial Intelligence (AI) has revolutionised the Knowledge Management (KM) landscape by enabling organisations to process vast amounts of information efficiently and strategically. Knowledge management systems (KMS) powered by AI technologies—hereafter referred to as AI-driven KMS (AI-KMS)—offer enhanced capabilities such as automation, real-time insights, data-driven decision-making and predictive analytics (Schiuma et al., 2022). These capabilities present significant opportunities for improving organisational agility and innovation (Bharadwaj et al., 2013). However, integrating AI into KM introduces complex ethical challenges, particularly concerning data privacy, algorithmic bias and transparency (Meijer & Bekkers, 2015). Addressing these concerns is essential to ensure responsible and sustainable AI deployment. This chapter explores the ethical dimensions of AI-driven KM, emphasising the importance of integrating ethical principles into the design, implementation and governance of AI-KMS. It argues that effective governance structures, robust regulatory frameworks and interdisciplinary collaboration are pivotal in mitigating ethical risks and fostering trust in AI technologies (Guandalini, 2022). By critically examining these ethical concerns, the chapter seeks to provide insights into best practices for responsible AI adoption in KM contexts. The central research questions guiding this chapter are: (1) What are the primary ethical risks associated with AI-KMS? and (2) What governance and design strategies can organisations implement to ensure ethical and effective KM?