AI virtual assistance in recruitment: a systematic literature review and bibliometric analysis

Abstract

Purpose This study investigates the integration of artificial intelligence (AI) into recruitment, focusing on the underexplored role of AI virtual assistants (AIVA). This study aims to evaluate how AIVA transforms recruitment practices and to provide a systematic research agenda for future applications. Design/methodology/approach The authors conducted a systematic literature review (SLR) and a bibliometric analysis (BA) to assess the use of AIVA in recruitment over the past decade, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. A structured search of the Scopus and Web of Science databases identified 5,301 publications from 2015 to June 1, 2026. After screening, the authors selected 255 papers for full-text review and BA, using R and VOSviewer. They systematically summarized and guided the exploration of current research. Findings The findings suggest that AIVA affects every phase of the recruitment process, from identifying staffing requirements to onboarding new personnel, with publications increasing significantly after 2023. The thematic analysis identified four key themes: isolated mature areas, innovation drivers, transitional uncertainties and broad foundational concepts. In addition, this SLR and BA critically examined the existing literature, highlighting advances and identifying gaps for future research. It also proposed a research agenda to guide subsequent investigations. Research limitations/implications This study is limited to publications indexed in Scopus and Web of Science, which potentially excludes relevant literature. Future research should expand to diverse data sets and explore the longitudinal impacts of AIVA adoption. Practical implications The findings provide actionable pathways for Human Resources (HR) practitioners to integrate AIVA into recruitment, thereby improving decision-making and reducing inefficiencies. Social implications AIVA adoption may improve recruitment equity, fairness, inclusivity and efficiency. Originality/value This paper uniquely synthesizes recruitment literature on AIVA through a dual SLR and BA approach. It advances theory by operationalizing broad AI research directions into domain-specific insights and offers practical implications for reducing recruitment costs, enhancing efficiency and guiding stakeholders in adopting AIVA.