2017年英國《經濟學人》雜誌曾提出，「世界上最寶貴的資源不再是石油，而是數據」。隨著物聯網時代來臨，工業應用領域也開始整合各種技術而掀起新一波工業革命。因為大量自動化及數據化，除了升級自動化設備、整合網通系統，監控設備產生的大數據，透過工業電腦進行分析，經由人工智能判斷邏輯產生條件，再由設備自主處理各種生產問題。除去大量勞動，專注於大數據自動化處理，即能生產更優質的產品，並且優化流程，降低企業成本。 自動化流程機器人(Robotic Process Automation)能自動的管理並執行企業大量耗費時間與人力的業務流程，可用於客戶服務、人力管理、供應鏈管理、採購、會計等範疇。物聯網(IoT)時代下的機器人自動化流程加入了認知運算等新興技術，更能進一步提升企業效率並降低成本。自動化流程機器人(Robotic Process Automation)儼然成下一個新的生產力革命。 市場研究機構IDC預測，2017年全球在認知和人工智慧系統支出將達到125億美元，和2016年相比成長達59.3%。Google母公司Alphabet公開測試無人駕駛汽車、阿里宣佈投資千億成立達摩院、百度機器人入駐肯德基等等。人工智慧(Artificial Intelligence)將顛覆商業思維、改寫商業模式。在2020年，人工智慧(Artificial Intelligence)將成為市場上真正的「主流」技術思維。IDC並且認為亞洲將在2020年成為全球第二大認知與人工智慧輸出區域。 本文探討自動化流程機器人與人工智慧之間的關聯，以及流程優化後對企業所產生的影響與變革．並且針對個案的自動化解決方案所達到的效益與後續發展進行評估與檢討，藉以提升自動化解決方案，協助企業在未來挑戰的競爭環境中創造最佳化優勢． / “The Economist” stated in 2017 that “the world’s most precious resource is no longer oil but data”. With the advent of the Internet of Things, industrial applications have begun to integrate various technologies and set off a new wave of industrial revolution. Because of a large amount of automation and data, in addition to upgrading automation soluitons, integrating netcom systems, and monitoring the big data generated by the solutions, analysis is performed through industrial computers, and conditions are generated through the logic judgment of artificial intelligence, and then the solutions autonomously handles various processes. It can produce better products, optimize the process and reduce business costs to focus on automation of big data and to save a lot of labor hiring. Robotic Process Automation can automate the management and execution of a large number of business processes that consume time and manpower, and can be used in areas such as customer service, manpower management, supply chain management, procurement, finance and accounting. The robotic automation process in the Internet of Things (IoT) era has added emerging technologies such as cognitive computing to further enhance the efficiency of enterprises and to reduce costs. Robotic Process Automation becomes the next new productivity revolution. In 2017, marketing research firm, IDC, predicts that global spendings on cognitive and artificial intelligence systems will reach US$12.5 billion, which represents a growth of 59.3% compared to 2016. Google, the parent company of Alphabet, publicly tests driverless cars, Ali announced that it has invested 100 billion to establish Daruma House, Baidu Robots has settled in Kentucky. Artificial Intelligence will disrupt business thinking and rewrite business models. In 2020, Artificial Intelligence will become the real "mainstream" technical thinking in the market. IDC also believes that Asia will become the world’s second largest cognitive and artificial intelligence output region in 2020. The article discusses the relationships between robotic process automation and artificial intelligence, and also the impact and changes after implementing the solutions. It has also evaluated and reviewed the effectiveness and following development of the automated solutions, so as to enhance the values of automation solutions and to help companies create optimal advantages in the future challenging and competitive environment.

知識管理是現代最重要的課題之一，企業轉型也在許多實務中證明對組織的成長與獲利很有幫助。然而因為轉型而創新的知識要如何管理，又是如何以知識螺旋的方式融入企業，進而幫助企業創新服務營運內容，則較少為人討論。本研究就是以此為研究動機，發展出的論文。藉由發生在Z公司轉型的過程中知識轉移發展的個案故事，來分析與印證企業在「知識管理」，與「企業轉型」兩方面的變化，如何與「知識螺旋」理論，交互影響的演變過程。 為了探討「知識轉換」的個案故事，本論文分別整理多篇「全球化」，與「知識螺旋」兩方面的重要理論文獻，設計出研究架構。本研究將個案公司企業知識的轉換過程，區分為三大階段; 而每一個歷程包含部份「共同化」、「外化」、「結合」與「內化」因子。企業知識管理上的重點之一，便是在於經理人們，如何能夠有效地調和這個「知識變換螺旋」過程，並將組織的策略資源與知識能力，藉由共同化、內化、外化與結合、轉化與學習而提昇。 經由個案資料與理論的分析與比較，主要的研究發現與結論如下：(1).在商業模式的轉型中，導入外部新資源與新知識，可讓其更迅速轉型並找到新策略。Z公司是企業轉型的最佳典範； (2). Z公司重新定位於「科技服務事業」，與轉型為「全球整合型企業」的創新商業模式，讓公司重新站上高峰；(3)個案A公司利用差異化分析，導入Z公司的經驗，建構新的能力，成就自己成為一個「全球整合型企業」。 最後，由個案故事的分析，本研究發現在「知識轉換」的螺旋中，即使是幫別的公司輔導轉型，也會對於因此學習到或是培養的新知識，經過知識的螺旋，再度轉換成企業本身的新核心能力。 關鍵字：知識螺旋、全球化、企業流程優化、委外加工、模組化、全球整合型企業、轉型、共享式服務中心 / Knowledge management is one of the most important topics in recent years. Business transformation has proved to be useful in the growth of the organization and profit. However, only few studies had focused on how to manage the innovative knowledge and how it is merged into a business through knowledge spiral and thereby helping to expand the business opportunities. This research is based on the case study of the knowledge conversion during a business transformation at company Z and analyzed the mutual effect and its relation with the knowledge spiral theory. The research structure is based on the summary of several key literatures on globalization and knowledge spiral to better understand the knowledge conversion cases. This research has divided the business transformation and knowledge conversion process in company Z into three major phases, and each phase is analyzed by four modules of knowledge transformation model, Socialization, Externalization, Combination and Internalization. One of the key points in business knowledge management is how the managers could cope with the knowledge conversion spiral process and improve the strategic resources with knowledge through the processes of socialization, externalization, internalization and combination. This research concludes that a company could introduce new external resources and knowledge during the business transformation in order to speed up the transformation process and craft a new strategy. Also, company Z repositioned itself as a service science company and then transformed with an innovative business model into a globally integrated enterprise to reclaim its glory. Finally, company A utilized gap analysis tool and introduced the transformation experiences by company Z to establish its own new expertise and become a globally integrated enterprise as well. This research also discovers that a company could also obtain new core comptetence through knowledge spiral by servicing other companies. Keywords: The Knowledge Spiral Theory, Globalization, Business Process Re-engineer, Outsource, Component Business Model, Globally Integrated Enterprise, Business Transformation, Shared Service Center