隨著人工智慧（AI）日益整合至職場組織中，其在人力資源管理（HRM）中的應用既帶來機會，也伴隨挑戰。儘管組織對於AI應用的興趣日益增加，現有文獻中仍明顯缺乏對最終使用者——包括員工與人資專業人士——如何看待AI代理人於人力資源管理整合與設計的研究。本研究針對此一缺口，探討員工與人資專業人士如何認知AI代理人在HR情境中的角色與設計。同時，本研究運用UTAUT與TTF理論架構，分析AI在HRM功能中有效且適切的採用方式。本研究採用九位受訪者進行半結構式訪談，並以扎根理論為基礎進行資料分析，聚焦於以下三個面向：對AI整合的期望與疑慮、促進信任與接受度的AI設計特徵、以及情感與人際需求如何影響AI代理人執行特定HR任務的適切性。研究結果顯示，參與者普遍支持在例行性、重複性或資料密集型的人資工作中導入AI，例如招募、排程與員工諮詢。然而，涉及同理心、倫理判斷或情感敏感度的任務，如績效評估或裁員，則被認為不適合完全由AI代理人執行。參與者強調在此類情境中人類介入的重要性，並指出AI設計應注重清晰溝通、降低擬人化程度，以及設定適當的使用限制與使用者控制權。本研究結論指出，儘管AI代理人可提升日常人資工作的效率，其導入過程仍須謹慎規劃。使用者偏好明確非擬人化、文字為主且透明的介面設計，這顯示過度擬人化在部分工作場域應用中可能削弱信任與清晰度。資料隱私與可解釋性亦為關鍵考量，且有效整合仰賴人資專業人員保有決策權，並接受技術與批判性思維相關訓練。值得注意的是，研究結果指出AI並非取代人資角色，而是重新塑造其職能，使其更聚焦於策略性與人際互動層面的工作。此研究期望能為組織如何負責任地導入AI提供實務建議，亦對人力資源管理與AI代理人相關文獻作出理論貢獻。

As artificial intelligence (AI) becomes increasingly integrated into organizational functions, its ap-plication in human resource management (HRM) presents both opportunities and challenges. De-spite the increasing interest in AI applications within organizations, there remains a notable gap in the literature regarding how end users, both employees and HR professionals, may perceive the integration and design of AI-enabled agents in human resource management (HRM). This study addresses this gap by exploring how employees and HR professionals perceive the role and design of AI-enabled agents in HR contexts. This study also applies the UTAUT and TTF frameworks to investigate effective and appropriate AI adoption in HRM functions. Using semi-structured inter-views with nine interviewees and a grounded theory-based analysis, the research aims to examine the following three areas: the expectations and concerns regarding AI integration, the preferred de-sign features that foster trust and acceptance, and the influence of emotional and relational demands on the suitability of AI agents for specific HR tasks. Findings reveal strong support for the use of AI in routine, repetitive, or data-intensive tasks such as recruitment, scheduling, and employee que-ries. However, tasks requiring empathy, ethical judgment, or emotional sensitivity, such as perfor-mance reviews or layoffs, were deemed unsuitable for full AI delegation. Interviewees vouched for the need for human involvement in these contexts and highlighted the importance of clear commu-nication, minimal anthropomorphism, and appropriate limits and user control in AI design. The study concludes that while AI-enabled agents can enhance efficiency in routine HR tasks, their adoption must be approached thoughtfully. Users preferred designs that were clearly artificial, text-based, and transparent, indicating that anthropomorphic features may reduce trust and clarity in cer-tain work setting contexts. Data privacy and explainability also emerged as critical concerns, and effective integration was deemed to depend on HR professionals retaining decision-making au-thority and receiving both technical and critical thinking training. Importantly, the findings suggest that AI is not replacing HR roles but reshaping them, shifting the focus toward more strategic and interpersonal responsibilities. This research provides practical implications for organizations look-ing to adopt AI responsibly and offers theoretical contributions to the HRM and AI agent literature.

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