隨著國際電信聯盟提出IMT-2030願景，第六代行動通訊系統（Sixth-Generation Mobile Communication Systems, 6G）不僅延續行動通訊在傳輸速率、低延遲與連線能力上的提升，也逐漸朝向感知、資料處理、跨域連結與智慧化服務整合發展。另一方面，人工智慧（Artificial Intelligence, AI）應用逐步進入醫療照護、智慧製造、遠端控制、沉浸式體驗與公共服務等場域，不同AI應用對通訊能力、資料處理、系統整合與導入條件之需求並不相同。因此，如何判斷特定AI場域應用是否需要6G支援、是否具備導入條件與投資價值，成為值得進一步探討之議題。
本研究以「第六代行動通訊系統於人工智慧場域之應用」為主軸，透過文獻回顧、專家訪談與主題分析，整理6G系統在AI場域中的發展背景、應用機會、導入挑戰與投入評估條件。研究首先區分AI-native 6G 與6G系統於AI場域應用之差異。前者主要指AI被納入 6G 網路本身，用於網路狀態判斷、資源配置、服務品質維持與自動化管理；後者則指6G作為通訊、感知與連結基礎設施，支援AI應用於不同場域中落地。此一區分有助於避免將6G網路架構設計與AI場域應用導入混為一談。
研究結果顯示，並非所有 AI 應用皆需要 6G 支援，是否值得投入應回到應用需求、通訊必要性、組織承接能力、外部監理條件與經濟價值進行判斷。經由專家訪談與主題分析結果修正後，本研究提出四項評估構面，包含技術發展構面、組織導入條件構面、外部監理構面與經濟構面，並進一步建立前置篩選、四大構面評估、應用情境與角色調整，以及投入評估結果四個階段流程。最後，本研究以照護機器人作為示範案例進行架構套用，初步判定照護機器人目前較適合先以場域試驗方式推動，而非直接全面優先投入。本研究提出之投入評估架構，可作為未來政策規劃、產業布局與AI場域中6G相關應用導入前期判斷之參考。

With the International Telecommunication Union proposing the IMT-2030 vision, Sixth-Generation Mobile Communication Systems (6G) are expected to move beyond higher transmission speed, lower latency, and enhanced connectivity toward integrated sensing, data processing, cross-domain connection, and intelligent services. Meanwhile, Artificial Intelligence (AI) applications are increasingly being introduced into healthcare, smart manufacturing, remote control, immersive experiences, and public services. Since different AI applications have different requirements for communication capability, data processing, system integration, and implementation conditions, it is necessary to examine whether specific AI domain applications require 6G support and whether they possess investment value.
This study focuses on the application of 6G systems in AI domains. Through literature review, expert interviews, and thematic analysis, this study first distinguishes between AI-native 6G and 6G systems supporting AI domain applications. The former refers to the integration of AI into the 6G network itself for network status assessment, resource allocation, and automated management, while the latter refers to 6G serving as communication, sensing, and connectivity infrastructure to support AI applications in different domains. This distinction helps avoid conflating 6G network architecture design with the implementation of AI applications in specific domains.
The findings indicate that not all AI applications require 6G support. Whether an application is worth investing in should be assessed based on application needs, communication necessity, organizational absorptive capacity, external regulatory conditions, and economic value. Based on expert interviews and thematic analysis, this study proposes four evaluation dimensions: technological development, organizational implementation conditions, external regulatory conditions, and economic value. It further establishes a four-stage evaluation process, including preliminary screening, four-dimensional evaluation, application context and role adjustment, and investment evaluation outcomes.
Finally, this study applies the proposed framework to the case of care robots. The results show that care robots have clear care-related needs and AI application necessity, and also demonstrate value as an example of 6G systems supporting AI domain applications. However, whether they are suitable for expanded investment still depends on advanced communication necessity, technological stability, organizational absorptive capacity, external regulatory conditions, and business model feasibility. Therefore, this study preliminarily concludes that care robots are currently more suitable for field trials rather than direct full-scale priority investment. The proposed investment evaluation framework can serve as a reference for future policy planning, industrial deployment, and preliminary decision-making before introducing 6G-related applications in AI domains.

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