Purpose

Artificial intelligence (AI) is a significant game changer in human resource development (HRD). The launch of ChatGPT has accelerated its progress and amplified its impact on organizations and employees. This study aims to review and examine literature on AI in HRD, using a bibliometric approach.

Design/methodology/approach

This study is a bibliometric review. Scopus was used to identify studies in the field. In total, 236 papers published in the past 10 years were examined using the VOSviewer program.

Findings

The obtained results showed that most cited documents and authors are mainly from computer sciences, emphasizing machine learning over human learning. While it was expected that HRD authors and studies would have a more substantial presence, the lesser prominence suggests several interesting avenues for explorations.

Practical implications

This study provides insights and recommendations for researchers, managers, HRD practitioners and policymakers. Prioritizing the development of both humans and machines becomes crucial, as an exclusive focus on machines may pose a risk to the sustainability of employees' skills and long-term career prospects.

Originality/value

There is a dearth of bibliometric studies examining AI in HRD. Hence, this study proposes a relatively unexplored approach to examine this topic. It provides a visual and structured overview of this topic. Also, it highlights areas of research concentration and areas that are overlooked. Shedding light on the presence of more research originating from computer sciences and focusing on machine learning over human learning represent an important contribution of this study, which may foster interdisciplinary collaboration with experts from diverse fields, broadening the scope of research on technologies and learning in workplaces.

中文翻译：

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人工智能在人力资源开发中的系统文献计量回顾：对人力资源开发研究人员、从业者和政策制定者的见解

 目的

人工智能 (AI) 是人力资源开发 (HRD) 领域的重大游戏规则改变者。 ChatGPT 的推出加速了其进展并扩大了其对组织和员工的影响。本研究旨在采用文献计量方法回顾和研究人力资源开发中人工智能的文献。

设计/方法论/途径

本研究是一项文献计量综述。 Scopus 用于识别该领域的研究。使用 VOSviewer 程序总共审查了过去 10 年发表的 236 篇论文。

 发现

获得的结果显示，被引用最多的文献和作者主要来自计算机科学领域，强调机器学习而不是人类学习。虽然预计人力资源开发的作者和研究将有更实质性的存在，但较少的突出表明了一些有趣的探索途径。

 实际影响

这项研究为研究人员、管理者、人力资源开发从业者和政策制定者提供了见解和建议。优先考虑人类和机器的发展变得至关重要，因为仅仅关注机器可能会对员工技能的可持续性和长期职业前景构成风险。

 原创性/价值

目前缺乏对人工智能在人力资源开发中的应用进行检验的文献计量研究。因此，本研究提出了一种相对未经探索的方法来研究该主题。它提供了该主题的直观且结构化的概述。此外，它还强调了研究重点领域和被忽视的领域。揭示更多源自计算机科学的研究的存在，并关注机器学习而不是人类学习，是这项研究的重要贡献，这可能会促进与不同领域的专家的跨学科合作，扩大技术和工作场所学习的研究范围。