個人電腦產業訂閱制的策略適應：AI賦能的商業模式轉型

Abstract

隨著數位轉型加速，訂閱制逐漸成為相較於傳統「擁有導向」商業邏輯的有力替代選項，尤其在軟體與媒體產業中展現顯著成效。然而，在以硬體為主體的產業中－特別是個人電腦產業－導入訂閱模式仍面臨諸多挑戰，包括根深蒂固的產品思維、分散的通路結構與服務整合能力不足等結構性障礙。本研究旨在探討個人電腦產業實施訂閱制的策略可行性，並分析在何種條件下，人工智慧能成為具支援性的轉型助力。研究以商業模式圖為架構，結合跨產業分析，提出轉型原則，並將其調整以因應個人電腦產業的結構限制，進一步探討模組化人工智慧工具是否能提升執行的可行性。本研究不將人工智慧視為通用解方，而是定位為條件式的支援層，當與組織準備度與數位成熟度相符時，可在顧客關係、營收模式與價值主張等面向發揮強化作用。最終建構出一套轉型框架，包含人工智慧強化的商業模式圖、SWOT/TOWS 分析工具，以及依產業情境設計的分階段實施路徑。研究指出，儘管結構性挑戰仍然存在，人工智慧在適當條件與策略對齊下，確實具有支援個人電腦產業導入訂閱制的潛力。

As digital transformation accelerates, subscription models have emerged as compelling alternatives to traditional ownership-based logic, particularly in software and media sectors. However, their adoption in hardware-centric industries—especially the personal computer (PC) sector—remains constrained by entrenched product mindsets, fragmented distribution channels, and limited service integration. This study investigates the strategic feasibility of subscription transformation in the PC industry and examines whether—and under what conditions—Artificial Intelligence (AI) can act as a supportive enabler. Drawing on the Business Model Canvas (BMC) and cross-industry analysis, the research identifies key transformation principles, adapts them to the structural barriers of the PC sector, and explores how modular AI tools may enhance implementation feasibility. Rather than treating AI as a universal solution, the study frames it as a conditional support layer that can strengthen specific BMC domains—particularly customer relationships, revenue models, and value propositions—when aligned with organizational readiness and digital maturity. The proposed framework includes an AI-enabled BMC, SWOT/TOWS analysis, and a phased deployment roadmap that incorporates segment targeting and AI capability assessment. Overall, the study suggests that while structural constraints remain significant, AI may offer targeted support for subscription transformation—when deployed under appropriate conditions and strategic alignment.