From automation to augmentation: Human resource's journey with artificial intelligence

IF 10.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Industrial Information Integration Pub Date : 2025-05-15 DOI:10.1016/j.jii.2025.100872

Maria Bastida , Alberto Vaquero García , Miguel Ángel Vazquez Taín , Marisa Del Río Araujo

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引用次数: 0

Abstract

This article examines the strategic integration of artificial intelligence (AI) in human resource management (HRM), highlighting both its opportunities and its challenges. While AI can improve HRM functions such as recruitment, performance evaluation and employee development, it also raises concerns related to algorithmic bias, technostress and resistance to change. To navigate these complexities, we present a structured two-tiered model that balances algorithmic efficiency with human-centred workforce development. Unlike previous studies that explore AI-driven human resource management in isolation, this research provides a comprehensive strategy for AI adoption that improves employee engagement, optimises HR decision-making and fosters organisational resilience.

In addition to outlining the role of AI in human resource management, we explore its practical implications, ethical considerations and associated risks, offering strategies to mitigate bias, promote transparency and foster organisational readiness for AI-driven transformation. We also emphasise the importance of pilot studies and empirical validation to assess the model's effectiveness in diverse organisational contexts. By providing a structured roadmap for AI integration, this study contributes to the ongoing discourse on how human resource management can lead, rather than simply adapt to, AI-driven workforce transformation.

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从自动化到增强：人力资源与人工智能的旅程

本文探讨了人工智能（AI）在人力资源管理（HRM）中的战略整合，突出了其机遇和挑战。虽然人工智能可以改善人力资源管理功能，如招聘、绩效评估和员工发展，但它也引发了与算法偏见、技术压力和抗拒变革相关的担忧。为了应对这些复杂性，我们提出了一个结构化的两层模型，以平衡算法效率和以人为中心的劳动力发展。与以往孤立地探索人工智能驱动的人力资源管理的研究不同，本研究为人工智能的采用提供了一个全面的战略，可以提高员工敬业度，优化人力资源决策，促进组织弹性。除了概述人工智能在人力资源管理中的作用外，我们还探讨了人工智能的实际意义、道德考虑和相关风险，并提供了减轻偏见、提高透明度和促进组织为人工智能驱动的转型做好准备的策略。我们还强调了试点研究和实证验证的重要性，以评估模型在不同组织背景下的有效性。通过提供人工智能集成的结构化路线图，本研究有助于正在进行的关于人力资源管理如何引领而不是简单地适应人工智能驱动的劳动力转型的讨论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Industrial Information Integration Decision Sciences-Information Systems and Management

CiteScore

22.30

自引率

13.40%

发文量

100

期刊介绍： The Journal of Industrial Information Integration focuses on the industry's transition towards industrial integration and informatization, covering not only hardware and software but also information integration. It serves as a platform for promoting advances in industrial information integration, addressing challenges, issues, and solutions in an interdisciplinary forum for researchers, practitioners, and policy makers. The Journal of Industrial Information Integration welcomes papers on foundational, technical, and practical aspects of industrial information integration, emphasizing the complex and cross-disciplinary topics that arise in industrial integration. Techniques from mathematical science, computer science, computer engineering, electrical and electronic engineering, manufacturing engineering, and engineering management are crucial in this context.