AI and Human Resources in a Literature-Driven Investigation Into Emerging Trends

Abstract

Throughout the years, technology has faced many advancements, the star being the power of Artificial Intelligence (AI), which continues to strike through. This concept has rapidly gained popularity and has raised points of concern in almost every government from the European Union (EU) because of the challenges it possesses in terms of efficiency, decision-making and transparency. This paper revolves around building up an extensive literature review of the academic landscape surrounding the role of AI in Human Resources (HR) in the public sector, analyzing Web of Science publication trends and thematic patterns, spanning 12,121 publications from 2020 to 2024, where both Python and R scripts are applied to extract insights. The findings highlight the relevance of a human-centric approach to AI adoption by addressing ethical, cultural and compliance concerns, with the aid of advanced Natural Language Processing (NLP) techniques, such as Latent Dirichlet Allocation (LDA) for topic modelling and keyword co-occurrence networks for thematic exploration. Moreover, a Hugging Face Named Entity Recognition (NER) model is employed to systematically identify and categorize AI techniques within the analyzed abstracts, providing a foundation for subsequent frequency and trend analyses. The analysis brings out a steady growth in publication volume, with an average of 2,500 papers annually and a significant concentration of research within domains such as neural networks, algorithm optimization and digital transformation. Apart from the interdisciplinary focus of the subject, we aim to shed light on the importance of AI-driven HR strategies in directing administrative insufficiencies of the public sector.

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