隨著資訊科技 (Information Technology) 被企業廣泛應用於提供產品及服務的流程中，尤其是人工智慧浪潮來襲，如何有效的導入人工智慧 (Artificial Intelligence) 幫助組織完成數位轉型並提高組織效率成了企業培養競爭優勢的關鍵因素之一。有鑑於數位轉型 (Digital Transformation) 以及人工智慧的快速發展，企業開始利用內部擁有的科技以及人才來實踐組織欲達成之轉型目標；然而人工智慧隨之而來的轉型並非有科技及人員就能輕鬆完成的，其具體轉型歷程以及行動軌跡在醫療產業中少被人提及且深入研究。
為了探討此議題，本研究採質性分析方法中的個案研究法，以全國具領導地位且具一定規模的醫學中心「中國醫藥大學附設醫院 (China Medical University Hospital, CMUH)」 作為本研究之研究個案，探討其如何利用人工智慧來達成醫療敏捷。本研究依據中國醫藥大學附設醫院在達成提供給病患更加敏捷的醫療服務所經歷的人機互動過程，將其轉型歷程分為三個階段：「數據奠定期」探討院方如何建構資訊科技基礎建設、「數據訓練期」聚焦院方如何進一步利用人工智慧完成下階段目標、以及「數據應用期」說明成果的落地應用如解決數據孤島問題，針對每一階段依序分析中國醫藥大學附設醫院在每個階段中的行動過程。本研究的貢獻為深入分析現象以歸納出情境中的脈絡，進而產出一套有助於幫助企業推動轉型的流程架構，為面臨相同課題的企業提供參考。

As information technology has been widely applied by firms in the delivery of products and services, especially with the rise of artificial intelligence, effectively utilizing AI has become a key factor for organizations to achieve digital transformation and improve operational efficiency. In response to the rapid development of digital transformation and AI, firms have begun to utilize their technologies to pursue transformation goals. However, AI-driven transformation cannot be easily accomplished simply by possessing technologies and human resources. In particular, the specific transformation process and action trajectories of AI adoption in the healthcare industry remain under explored.
To explore this issue, this study adopts qualitative case study approach and selects China Medical University Hospital as the case. This study investigates how the hospital utilize artificial intelligence to achieve healthcare agility, focusing on the interactions between technology and organizational members, and how can data silo problems be solved through actions. Based on socio-technical interaction process by China Medical University Hospital in pursuing agile healthcare services, this study categorizes the transformation process into three stages: (1) Data Foundation Stage, (2) Data Training Stage, and (3) Data Application Stage. This study is going to point out the action processes undertaken by the hospital within each stage.
The contribution of this study lies in its in-depth analysis of the phenomenon to identify the underlying mechanisms, thereby developing a framework that could assist organizations in actualizing digital transformation and provide reference for organizations facing similar changes.

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