In the contemporary landscape of rapid technological advancements, organizations face the need to innovate and adapt. One critical asset that organizations possess is their accumulated knowledge base, comprising both explicit and tacit knowledge. Generative Artificial Intelligence (Gen AI) is emerging as a promising tool for facilitating the exploration, harnessing, and transformation of this organizational knowledge. Gen AI systems, equipped with natural language processing and machine learning capabilities, can sift through vast amounts of data to uncover hidden insights, generate novel ideas, and facilitate collaborative knowledge sharing. This research examines how Gen AI can help employees explore and transform embedded organization knowledge and utilize it to enhance organizational performance and effectiveness. Specifically, this proposal studies employees’ attitudes towards Gen AI augmented knowledge management systems (KMS) by investigating employee perceptions and attitudes towards Gen AI-augmented KMS, the effectiveness of AI-generated knowledge, participation in AI communities of practice (CoPs), ethical considerations, and the influence of organizational culture on the adoption of AI-driven knowledge management tools. Our research, at the intersection of knowledge management (KM) and Gen AI, is relatively scarce in the literature and aims to fill this knowledge gap through an independent sequential mixed-method investigation of employees working for an organization. We will conduct a quantitative survey study based on current KM and Gen AI literature, utilizing theories such as the resource-based view, Wenger’s communities of practice (CoP) theory, and social exchange theory. This would be followed by a qualitative study with semi-structured interviews with employees to gain additional insights into the findings of the quantitative study. This study aims to contribute to the existing literature on Gen AI and knowledge management while providing practical implications for organizational practitioners seeking to harness the transformative potential of AI-driven knowledge management systems. By understanding individual needs, preferences, and concerns, organizations can effectively tailor their AI implementation strategies, ensuring the successful integration and adoption of Gen AI-powered knowledge management systems.