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As artificial intelligence (AI) becomes an integral component of knowledge management systems (KMS), organizations face a new spectrum of vulnerabilities, including fraud, misuse, and ethical threats. This chapter explores these challenges within the evolving landscape of AI-driven KMS, emphasizing the need for robust governance, transparency, and value-based alignment. By dissecting real-world use cases, the chapter reveals how AI technologies—when poorly designed or deployed—can unintentionally amplify bias, manipulate knowledge flows, or erode trust. The authors argue that the convergence of AI and knowledge management (KM) necessitates not only technical controls but also ethical foresight and interdisciplinary collaboration.

The chapter presents a multi-dimensional framework for identifying and mitigating risks in AI-powered KMS, drawing on insights from cybersecurity, ethics, information science, and organizational behavior. It highlights key domains of vulnerability—from data integrity and decision opacity to accountability gaps and policy blind spots. Finally, it offers strategic recommendations for safeguarding future KMS ecosystems, including stakeholder engagement, ethical auditing, regulatory alignment, and the cultivation of digital responsibility. The goal is to future-proof AI-enhanced knowledge infrastructures and promote resilient, trustworthy systems that empower innovation while protecting core human values.

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