Unveiling the future of artificial intelligence in talent acquisition: A bibliometric analysis of emerging trends and future directions

Artificial Intelligence (AI) is extensively reshaping organizational practices and redefining talent acquisition by automating recruitment processes and improving efficiency in candidate selection. Despite the growing research in this domain, there is a gap in comprehensive bibliometric analyses that systematically examine this domain. Thus, the current study aims to comprehend the existing literature with specific strategies for data extraction and analyze the future scope of AI in talent acquisition. With 533 articles extracted from the Scopus database, the publication trends, key contributors, and intellectual structures have been explored. The bibliometric analysis shows that the US and India are the leading contributors to the research area. Co-occurrence network analysis identified four clusters: (i) AI in recruitment and HR practices (major cluster), (ii) advanced technologies such as machine learning, deep learning, and automation, (iii) ethical and social considerations, and (iv) strategic HRM aspects like decision-making and diversity. It shows the centrality of AI-enabled recruitment and its connection with technical, social, and strategic aspects, highlighting the interdisciplinary nature of the domain. Thematic mapping confirms that AI and recruitment are the central themes and specifies the need for interdisciplinary exploration to fully understand the strategic and ethical implications. The intellectual structure demonstrates a shift in research focus from technical applications to ethical and strategic considerations in AI-driven recruitment. In conclusion, the study provides a systematic overview and offers actionable insights for researchers, HR practitioners, and policymakers to make evidence-based strategies, identify emerging trends, and facilitate responsible and strategic AI adoption in recruitment processes.