人工智慧技術發展迅速且應用廣泛，這讓電梯行業面臨 AI 賦能轉型的大機遇
與大挑戰，所以本文把 AI 賦能下的電梯行業轉型當作研究物件，深入研究人工智
慧技術在電梯設計、製造、安裝、運維等整個生命週期裏的應用前景與實施策略。
研究先分析電梯行業 AI 賦能轉型的背景和必要性，因為傳統電梯行業在安全性、
可靠性、效率和服務品質上有問題和局限。接下來文章系統地整理人工智慧技術在
電梯行業的主要應用領域，如智慧設計與模擬、智慧製造與品質控制、智慧安裝與
調試、智慧運行與監控、智慧維保與故障預測等並探討各領域的關鍵技術與應用案
例。
通過結合文獻研究、案例分析的方法，本研究深入剖析了電梯行業轉型中 AI
賦能的技術路徑與實施策略，在技術路徑上著重探討機器學習、電腦視覺、自然語
言處理、物聯網等人工智慧核心技術於電梯行業的具體應用場景與實現方式，並且
在實施策略方面提出涵蓋人才培養、技術研發、資料治理、標準制定以及生態構建
的系統性解決方案，給電梯企業提供推進AI賦能轉型的可操作指導建議。
研究表明，在 AI 賦能下，電梯行業轉型有著顯著的經濟和社會效益，經濟效
益方面，AI 賦能轉型能提升電梯設計效率、優化製造流程、削減運維成本並延長
設備壽命，進而增強企業的競爭力與盈利能力。社會效益方面，AI 賦能轉型可大
大提高電梯的安全性與可靠性、改善用戶體驗、節省能源消耗，助力智慧城市和綠
色建築的構建。不過研究也指出，電梯行業 AI 賦能轉型面臨諸多挑戰，如技術標
準不一、存在資料安全風險、缺乏人才儲備等，但同時也給出了相應的應對策略和
建議。
AI 賦能電梯行業轉型的全景圖被本研究系統性地探討，這是本研究的創新之
處，其涵蓋技術應用層面且深入剖析組織變革、商業模式創新等方面的問題，電梯
企業制定 AI 賦能轉型戰略時能將研究成果當作理論指導與實踐參考，政府部門制
定相關政策和行業標準時也有據可循，日後研究可更聚焦 AI 技術於特定電梯應用
場景的深度融合以及 AI 賦能轉型給電梯行業生態系統和價值鏈帶來的重塑效應，
從而為推動電梯行業高質量發展不斷提供智力支援。

With the rapid development and widespread application of artificial intelligence
technology, the elevator industry is facing significant opportunities and challenges for
intelligent transformation. This article takes the intelligent transformation of the elevator
industry empowered by AI as the research object, and deeply explores the application
prospects and implementation strategies of artificial intelligence technology in the entire
life cycle of elevator design, manufacturing, installation, operation and maintenance. The
study first analyzed the background and necessity of the intelligent transformation of the
elevator industry, pointing out the problems and limitations of the traditional elevator
industry in terms of safety, reliability, efficiency, and service quality. Subsequently, the
article systematically reviewed the main application areas of artificial intelligence
technology in the elevator industry, including intelligent design and simulation, intelligent
manufacturing and quality control, intelligent installation and debugging, intelligent
operation and monitoring, intelligent maintenance and fault prediction, and explored key
technologies and application cases in each field.
This study adopts a combination of literature research, case analysis, and expert
interviews to deeply analyze the technological path and implementation strategies of AI
empowering the intelligent transformation of the elevator industry. In terms of
technological path, the specific application scenarios and implementation methods of core
artificial intelligence technologies such as machine learning, computer vision, natural
language processing, and the Internet of Things in the elevator industry were discussed in
detail. In terms of implementation strategy, a systematic solution including talent
cultivation, technology research and development, data governance, standard setting, and
ecological construction has been proposed, providing actionable guidance and suggestions
for elevator enterprises to promote intelligent transformation.
Through research, it has been found that the intelligent transformation of the elevator
industry empowered by AI will bring significant economic and social benefits. In terms of
economic benefits, intelligent transformation can help improve elevator design efficiency,
optimize manufacturing processes, reduce operation and maintenance costs, extend
equipment lifespan, thereby enhancing enterprise competitiveness and profitability. In
terms of social benefits, intelligent transformation will significantly improve elevator safety and reliability, enhance user experience, save energy consumption, and contribute
to the construction of smart cities and green buildings. However, the study also pointed out
the challenges faced by the intelligent transformation of the elevator industry, including
inconsistent technical standards, data security risks, and insufficient talent reserves, and
proposed corresponding response strategies and suggestions.
The innovation of this study lies in the systematic exploration of the panoramic view
of AI empowering the intelligent transformation of the elevator industry, which not only
covers the technical application level, but also deeply analyzes issues such as
organizational change and business model innovation. The research results provide
theoretical guidance and practical reference for elevator enterprises to formulate intelligent
transformation strategies, and also provide a basis for government departments to
formulate relevant policies and industry standards. Future research can further focus on the
deep integration of AI technology in specific elevator application scenarios, as well as the
reshaping effect of intelligent transformation on the elevator industry ecosystem and value
chain, providing sustained intellectual support for promoting high-quality development of
the elevator industry.