生成式人工智慧(Generative AI, GAI)技術於近年快速發展，為企業虛擬團隊協作帶來嶄新可能。然而，實務上企業在導入GAI時，往往面臨技術落差、制度配套與組織接受度等多重挑戰，相關關鍵成功因素之系統性探討亦仍付之闕如。本研究旨在建構企業導入GAI於虛擬團隊協作之關鍵成功因素評估架構，並進一步探討各因素之相對重要性，以提供企業推動GAI策略之實務參考。
本研究首先透過文獻回顧與專家訪談，彙整初步因素構面，並引入GAI輔助工具，進行因素語意擴展與結構補強。接續由專家針對整合後的因素進行篩選與確認，形成完整評估層級架構。研究採用層級分析法(Analytic Hierarchy Process)進行問卷設計與實證分析，共回收十五份之業界專家的有效問卷，完成因素權重計算與排序。
研究結果顯示，「模型可信度」、「模型資料品質」與「需求導向」為前三大關鍵成功因素，說明專家特別關注模型的正確性與穩定性、訓練資料的品質與完整性，以及應用情境的契合程度。其次為「主管支持」、「整合能力」與「應用場景支援能力」。本研究依據因素權重進行分群，將19項關鍵因素分為核心、支持與配套三層級，並結合專家訪談觀點，提出導入規劃、現況診斷、共識建立等三大應用方向，並發展「GAI應用成熟度評估表」，提供企業自評導入階段、辨識關鍵差距與規劃策略節奏的具體工具。整體而言，本研究不僅補足GAI於企業虛擬團隊協作場域中關鍵成功因素之理論探討，亦提供企業在實務推動上的具體操作依據，期能作為未來組織導入GAI之規劃參考。

Generative Artificial Intelligence (GAI) has advanced rapidly in recent years, offering new opportunities for virtual team collaboration in enterprises. However, organizations face challenges such as technological gaps, insufficient institutional support, and low organizational acceptance. This study aims to develop an evaluation framework for key success factors (KSFs) in GAI adoption for virtual team collaboration and to assess their relative importance, providing practical guidance for enterprises.
Preliminary KSF dimensions were identified through literature review and expert interviews, then refined using GAI-assisted tools for semantic expansion and structural enhancement. Experts reviewed and validated the integrated list to establish a complete hierarchical framework. The Analytic Hierarchy Process was applied to design questionnaires, collect responses from fifteen industry experts, and calculate factor weights and rankings.
Results show that model reliability, data quality, and demand orientation are the top three KSFs, followed by managerial support, integration capability, and application scenario adaptability. Based on weights, the 19 factors were grouped into core, supportive, and complementary tiers. Three application directions—implementation planning, current state assessment, and consensus building—were proposed, along with a GAI Application Maturity Assessment Table to help organizations evaluate adoption stages, identify gaps, and plan strategies. This study provides a theoretical framework and practical tools to support effective GAI implementation in virtual team collaboration.

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