AI-empowered employee recruitment: Insights from a consultancy project

The conventional employee recruitment approach is often time- and resources-consuming. Following the call for more effective- and economic recruitment, the current article describes the development and implementation of an 'artificial intelligence-built model for employee recruitment', based on a management consultancy project. The raw data for model building were gathered from the assembly-line employees and their managers in an electronics plant in Kunshan, China. The dataset comprised two parts: Part-1 data were the occupational codes and personality parameters of the top performers (responded by performers), whereas Part-2 data were the employability- and fitness parameters of the top performers (rated by the managers of performers). Top performers were defined as the employees who had the highest output of products with the lowest defect rate. Through the repetitive data-matching algorithms, the model gradually learned and identified the signs (patterns) of top performers. The model became established (workable) when it showed the capability to recognize the patterns accurately. We then applied the model to the employee recruitment practice and observed its efficacy, in which the model achieved its purpose by selecting the best-fit candidates from the pool of applicants within minutes. Compared to the conventional recruitment approach, the model saved both organizational resources and expenses, with no need for human labor. Research findings indicated a new component – the candidate factor, which should be considered in the design and implementation of AI-empowered recruitment models. The model's applicability shall be interpreted with caution, as there is no follow-up survey to examine whether the model-appointed candidates are genuine top performers. Implications on employee recruitment literature and managerial policies are discussed.

This article is part of the "Supplement: 33rd International Congress of Psychology, 21–26 July 2024, Prague, Czech Republic"