The impact of generative AI (ChatGPT) on recruitment efficiency and candidate quality: The mediating role of process automation level and the moderating role of organizational size

Introduction The primary objective of the current paper is to understand the impact of Generative AI Tools on the recruitment process, on their effectiveness in addressing bias, enhancing efficiency, and ensuring accurate candidate evaluation and looking at the moderating role of familiarity and the mediating role of the size of the organization and level of employee. Methods A quantitative survey approach, with 469 professionals participating in an online survey, was used. Structural Equation Modelling (SEM) in Amos SPSS was used in the analysis of the relationships between Generative AI Tools, User Familiarity with AI, and key outcomes in the recruitment process. Results The study reveals a significant reduction in bias during candidate screening, attributed to the algorithmic objectivity, data driven decision making, and consistency inherent in Generative AI Tools. Efficiency gains and heightened accuracy in shortlisting candidates were also observed. However, User Familiarity with AI emerged as a moderating factor in influencing the relationship between Generative AI Tools and efficiency improvement. Discussion As a recommendation, organizations are encouraged to invest in continuous training programs to harness the full potential of Generative AI Tools in optimizing efficiency and ensuring a fair and accurate recruitment process.