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当前位置：人文与社会科学学刊 > 2026年8月-2卷8期 > 文章详情

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人工智能赋能人力资源管理研究综述：理论框架、实践悖论与研究缺口

Artificial Intelligence-Enabled Human Resource Management: Theoretical Perspectives, Practical Paradoxes and Open Research Questions

作者：罗子敬

单位：新余青云联合会计师事务所

卷期：2026年8月-2卷8期

通讯作者：罗子敬

DOI：10.70693/202607121395

页码：13-21

发布时间：2026-08-06

总浏览量：201

摘要

摘要：人工智能已经越过单纯的信息化辅助阶段，开始进入招聘甄选、培训开发、绩效评价、薪酬服务、员工关系与人才规划等管理环节。已有研究较充分地呈现了算法在信息处理、预测分析和个性化服务方面的潜力，但效率提升并不会自动带来公平、信任或更好的组织结果。本文在规范化检索的基础上，对2015—2026年中英文研究进行整合性述评，重点考察概念边界、研究演进、理论解释、应用情境及治理争议。梳理表明，相关研究的关注点经历了由流程电子化到预测分析、再到价值与责任治理的移动；国内成果偏重技术落地和组织转型，国外文献则较早讨论歧视、劳动控制、员工权利与问责。在此基础上，本文把技术、组织、个体、价值和结果纳入同一分析链条，并从实际管理过程归纳出五类持续存在的实践悖论：效率与公平、数据利用与隐私、自动化与人本沟通、技术更新与组织承载、量化判断与具体情境。文章认为，人工智能在人力资源管理中的价值取决于制度安排和使用方式，而非模型性能本身；对高影响人事决策实行分级管理、保留有意义的人工审查、建立解释和申诉渠道，是推进负责任应用的基本条件。

关键词

关键词：人工智能；人力资源管理；智能人力资源管理；算法治理；人机协同；研究综述

Abstract

Abstract: AI is no longer used in human resource management only to automate clerical work. Organizations also apply it to screening applicants, recommending training, drafting performance feedback, providing compensation and employee services, and planning the workforce. The literature reports faster information handling and stronger predictive support, but these improvements do not in themselves secure procedural fairness, employee trust, or better organizational results. This article reviews Chinese and international studies published between 2015 and 2026. Rather than counting topics mechanically, it compares how the field has defined AI-enabled HRM, how its questions have changed, which theories have been used, and what disputes have emerged in practice. The review finds a movement from digitizing processes, to prediction and recommendation, and then to governance of values and responsibility. Chinese research has concentrated on implementation and organizational transformation; international research addressed discrimination, labor control, rights, and accountability earlier. A five-level framework links technological conditions, organizational arrangements, individual responses, value constraints, and management outcomes. Five recurring tensions are then examined: efficiency and fairness, data use and privacy, automation and human communication, rapid technical change and organizational capacity, and quantitative indicators and contextual judgment. The article concludes that model performance alone cannot determine whether AI-enabled HRM is responsible. What matters is how outputs enter decisions, who may question them, and who remains accountable. High-impact decisions should therefore be subject to differentiated risk controls, genuine human review, understandable reasons, appeal routes, employee participation, and auditable responsibility.

Keywords

Keywords: artificial intelligence; human resource management; intelligent human resource management; algorithmic governance; human–AI collaboration; literature review

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引用本文

罗子敬. 人工智能赋能人力资源管理研究综述：理论框架、实践悖论与研究缺口[J]. 人文与社会科学学刊. 2026, 2 (8): 13-21. DOI: 10.70693/202607121395.

APA引用

罗子敬. (2026). 人工智能赋能人力资源管理研究综述：理论框架、实践悖论与研究缺口. 人文与社会科学学刊, 2 (8), 13-21. https://doi.org/10.70693/202607121395

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