<![CDATA[Background: The rapid adoption of generative artificial intelligence (GenAI) technologies including large language models (LLMs) and AI-enabled knowledge systems presents a fundamental transformation of knowledge work in contemporary organizations. Little research has explored how these technologies reshape the nature of knowledge creation, organizational learning processes, and professional capabilities in emerging economy contexts. Research Objective: To develop an integrated understanding of how Generative AI transforms knowledge work within organizations operating in Banten Province, Indonesia. Research Method: This qualitative descriptive study employed multi-case inquiry involving 20 participants across 5 organizations, utilizing semi-structured interviews, organizational document analysis, and observation protocols. Thematic analysis integrated knowledge-based view, dynamic capability theory, and organizational learning frameworks. Participants: Senior managers, HR professionals, knowledge workers, digital transformation leaders, and AI implementation specialists from diverse sectors. Main Findings: GenAI transforms knowledge work through four primary mechanisms: (1) augmentation of cognitive labor, shifting employees toward higher-order thinking and judgment; (2) reorganization of knowledge creation processes enabling rapid synthesis and pattern recognition; (3) evolution of organizational learning from episodic to continuous adaptive learning; (4) emergence of new workforce competencies centered on human-AI collaboration, critical evaluation, and adaptive expertise. Novelty: This research adopts a knowledge work transformation lens rather than focusing on technological adoption or productivity metrics, grounded in human-AI collaboration theory, and situated within an emerging economy context. Practical Implications: Organizations must strategically redesign work processes, invest in adaptive workforce development, and create governance frameworks balancing efficiency gains with meaningful human contribution.]]>
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