Global Journal of Management and Business Research, A: Administration and Management, Volume 23 Issue 5

and related aspects of efficiency and effectiveness in decision-making. It is also indicative that the methods and techniques focussed include analytic hierarchy process, artificial neural network, fuzzy logic, and evaluation models. Resource allocation function is facilitated by the application of AI in HRM, as it contributes in an optimal, effective, and budgeted manner, the process of assigning and scheduling available resources, including the workforce. The talent evaluation function is objectively developed and driven by neural networks and the analytic hierarchy process, which brings forth a method of organizing and analysing complex decisions related to talent. Training and development are another key area that is reflected in the co-occurrence network. The second research question (RQ2) focussed on the areas of research in the domain of AI in HRM. As indicated in the VOS viewer visualization of term co- occurrence network based on title and abstract (Figure 5) suggests that the research in AI in HRM predominantly focuses on talent acquisition, resource allocation, and training and development. Top keyword analysis, as reflected in Figure 4 shows the prominent keywords used in the publications, bigger a circle, the more frequently the keyword appears in the publication set from Scopus. The top three keywords as per the analysis are Human Resources (38.87%), AI (19.03%), and Fuzzy Logic (17.41%). A brief overview of the literature on the three key areas identified, namely, resource allocation, talent acquisition, and training and development is reflected in Tables 7, 8 and 9. Figure 4: Network Visualization Map of Keywords Research on Artificial Intelligence in Human Resource Management: Trends and Prospects 37 Global Journal of Management and Business Research Volume XXIII Issue V Version I Year 2023 ( ) A © 2023 Global Journals Source: Created by Authors using VOS Viewer