本研究並非探討AI的技術發展、演算法細節或系統導入等層面，而是聚焦於台灣人力資源專業人員在AI浪潮下所面臨的結構性困境及其突破策略。研究發現，HR從業者的焦慮主要源於一種「結構性困境」：一方面，高階管理者普遍抱持「替代敘事」的認知框架，將AI視為降低人事成本與取代人力的工具，形成本研究界定之「成功即懲罰」的悖論-HR的效率提升非但未獲肯定，反而被解讀為應縮減部門編制之理由；另一方面，組織普遍缺乏AI導入之專屬預算、IT技術支援與系統性培訓資源，且數據與資訊基礎建設相對薄弱，使得AI相關應用往往僅停留在個人層級的「英雄式探索」，難以形成規模化的組織轉型。 本研究採取質性研究方法，針對金融業、製造業、服務業、物流業、零售業、製藥業等不同產業共十位HR從業人員進行深度訪談。結果顯示，HR專業人員透過「以戰養戰」的小規模實驗、個人化知識庫之建置、社群跨域學習與策略性向上溝通等具體實踐，逐步重構自身的專業價值-從傳統行政執行者，轉變為人機協作的設計者、數據脈絡的詮釋者以及科技倫理的提醒者。跨產業比較則發現：金融業以合規為優先考量，製造業聚焦於效率優化，服務業則更強調彈性與人性溫度，顯示產業特性深刻影響AI轉型路徑之差異。 本研究修正了既有「技術衝擊→角色轉型」之線性模型，提出整合「結構-能動性-專業邊界」之分析框架，同時對T型／π型能力理論進行結構性修正-強調能力建構深受組織權力與資源條件之制約，而非單純的個人學習議題。實務上，建議企業高階管理者應從「替代敘事」轉向「賦能敘事」，將AI定位為提升HR戰略價值的賦能工具；HR從業者則應主動累積小勝利、培養倫理判斷能力、建立跨領域學習網絡。唯有從結構層面突破此困境，HR方能從「被變革的對象」進化為組織數位化與人文價值的整合者。;This study does not focus on technical issues such as AI development， algorithm details， or system implementation. Instead， it investigates the structural dilemmas and breakthrough strategies faced by human resource professionals in Taiwan amid the AI wave. The study finds that HR practitioners’ anxieties stem from a “structural dilemma.” On one hand， senior managers generally hold a “substitution narrative，” viewing AI as a tool for cost reduction and labor replacement， creating a “success-as-punishment” paradox-HR‘s efficiency gains are misinterpreted as justification for downsizing. On the other hand， organizations commonly lack dedicated budgets for AI adoption， IT support， and systematic training， while data infrastructure remains weak， leaving AI applications as individual “heroic explorations” that fail to scale. Adopting a qualitative approach， this study conducted in-depth interviews with ten HR practitioners from finance， manufacturing， service， logistics， retail， and pharmaceutical industries. The findings reveal that HR professionals exercise agency through small-scale experiments (“learning by doing”)， personal knowledge base construction， community learning， and strategic upward communication. Gradually， they reconstruct their professional value—transforming from administrative executors into human-machine collaboration designers， data interpreters， and ethical reminders. Cross-industry comparisons show that finance prioritizes compliance， manufacturing focuses on efficiency optimization， and service leverages flexibility and human warmth. This study revises the linear “technology impact → role transformation” model， proposes an integrated “structure-agency-professional boundary” framework， and contextualizes T-shaped/π-shaped competency theory—emphasizing that capability building is deeply constrained by organizational power and resource conditions， rather than being a purely individual learning issue. Practically， it advises top managers to shift from a “substitution” to an “empowerment” narrative， and HR professionals to accumulate small wins， cultivate ethical judgment， and build cross-domain learning networks. Only by breaking through structural dilemmas can HR evolve from an “object of change” into an integrator of organizational digitalization and humanistic value.
