This study aims to examine how artificial intelligence (AI) is adopted and implemented in hearing care clinical practice by conceptualizing the process as a knowledge lifecycle. Specifically, the study explores how clinicians interpret, integrate, evaluate and sustain AI-generated insights in their everyday decision-making.
A qualitative research design was used to collect clinicians’ narratives of their lived experiences with AI-enabled hearing-care tools. Data from 17 clinicians were analyzed using the Gioia methodology to develop first-order concepts, second-order themes and aggregate dimensions.
The analysis identifies a ten-phase knowledge lifecycle model that explains how clinicians progressively engage with AI-enabled knowledge in practice, from recognizing knowledge gaps to establishing the credibility of AI insights, to legitimizing them through existing approaches, translating them into clinical workflows and continuously verifying and sustaining their use.
The study contributes to knowledge management research by conceptualizing AI adoption and implementation as a knowledge lifecycle and by showing how algorithmically generated knowledge is integrated with professional expertise in practice. The findings provide empirically grounded insights for organizations implementing AI-enabled tools in knowledge-intensive settings.
