This paper examines the transformative impact of AI-enhanced data platforms on knowledge management (KM) within waste management organizations, focusing on the case of Alia Servizi Ambientali SpA in Tuscany, Italy. Utilizing a qualitative case study approach that combines on-site observations, stakeholder interviews, and system data analysis, our research demonstrates that AI integration significantly optimizes operational efficiency by consolidating diverse data streams, from IoT sensors monitoring waste receptacles to vehicle fleet metrics, into a unified, high-quality repository. The platform employs a medallion architecture to ensure data quality, enabling predictive analytics that improve route optimization, reduce vehicle movements, and lower carbon emissions. Beyond these practical benefits, the study advances theoretical insights by proposing a framework that situates AI-driven KM within broader governance and ethical contexts, contrasting traditional approaches with the dynamic capabilities of AI technologies. Despite the inherent limitations of a single-case design, our findings provide a strategic blueprint for leveraging AI-enhanced data platforms in waste management. They underscore the critical role of robust governance frameworks, leadership commitment, and targeted training in aligning technological capabilities with evolving KM practices, ensuring the sustainability and scalability of digital transformation initiatives.