隨著網路購物的多元化發展，與科技的日新月異，新零售時代虛實整合造就一場翻天覆地的改變。Amazon於2016年12月將「拿了就走」的快速消費體驗引進無人商店，無人商店風潮襲捲全球，然而，傳統零售業者在快速佈局通路的同時，卻忽略了優化消費者的購物體驗流程，與互聯網帶來的強大威脅。為了創造第二曲線的創新，零售業者紛紛開始轉型，並將人工智慧視為驅動新零售快速成長的關鍵技術，為虛擬通路與實體門市之間的鴻溝創造了機會。本研究採個案蒐集法進行技術預測，透過技術地圖進行盤點分析，藉此瞭解新零售的下一步發展，以及不同購物流程應導入的服務與技術應用項目。
　　本研究透過質化分析的個案研究法作為調查基礎，透過技術地圖將服務與技術應用進行拆解，並依據四個關鍵要素（服務應用、技術應用、應用類型、AI階段）將個案內容分類及盤點。根據盤點結果發現：(1) 新零售未來應朝向第四階段AI發展，提供影像／語音處理與互動應用；(2) 新零售應積極導入相關應用於購中與購後階段，提供無縫式的購物體驗流程；(3) 新零售應優先發展雲端整合平台，並導入大數據分析、雲端運算與感測技術，以蒐集購物行為數據；(4) 若要提供消費者創新的購物體驗流程，可導入影像生成技術與自然語言處理。本研究為新零售整合人工智慧的技術預測分析初探，可作為日後相關產業了解重點服務與技術應用的發展趨勢。

　　The rapid development of technology and online commerce, driven by the Online-to-Offline in the New Retail era, has created tremendous change. In December 2016, Amazon introduced the “Just Walk Out” shopping experience with the unmanned store and caught the world’s attention. Yet, traditional retailers often neglect consumer shopping experience and the powerful threat posed by online commerce. To create the innovations of the second curve, the retail industry began to transform by utilizing AI as the key driving technology to compete in the New Retail era and resulting in opportunities for virtual channels and physical stores.
　　This research uses qualitative analysis and case study to predict technology and conduct inventory analysis by using a technological roadmap, to understand the future technological development of the New Retail in different shopping processes. The services and technologies are classified into four key elements - service application, technology application, application type, and AI stage. Based on inventory analysis, it was found that: (1) There is a trend towards AI development; namely, image and voice processing, or interactive applications; (2) New retailers should focus on the purchase and post-purchase experience of consumers, to provide them with seamless shopping experience; (3) New Retailers should give priorities to the development of the cloud-integrated platform, adopt big data analysis, cloud computing, and sensor technology, to collect shopping behavioral data. (4) To develop an innovative shopping experience, image generation technology, and Natural Language Processing should be strengthened.
　　This research integrates AI and New Retail literature to provide the prediction of future technology trends. It also serves as a general understanding and guideline to relevant industries to develop their underlying key technologies accordingly.

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