This paper’s objective is to scientifically identify the present research trends for future research agenda in Human Resource Analytics (HRA) domain by conducting a comprehensive literature study. Our proposed article applied the existing SPAR-4-SLR protocol for the systematic assessment of the HRA literature. Based on search parameters including subject, function, and language, the authors discovered 226 publications from the Scopus database. We performed a systematic literature review by considering the top 60 highly cited publications and identified five key themes such as HR analytics, Training and Development, Performance Management, Big Data, AI and ML, and Human Resource Information System and Organisation Development. This study extends the HRA research by incorporating systematic assessment to build a systematic grasp of the field of study and highlights the emerging relevance of HRA for effective, objective, and transparent Human Resource Development (HRD).

Purpose: The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data. Design/methodology/approach: This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field. Findings: The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement. Research limitations/implications: In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology. Practical implications: This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance. Originality/value: This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance. © 2024, Emerald Publishing Limited.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI. Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM. Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices. Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM. Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

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