AI Integration in Recruitment and Selection: A Qualitative Study of Pakistan

Abstract

The qualitative research explores how artificial intelligence is integrated in the recruitment and selection of different organizations in Pakistan. Being more specific to artificial intelligence-powered applications, e.g., automated applicant tracking systems, chatbot-based pre-screening, and predictive analytics. The study analyses the impact of these technologies in the process of talent acquisition and applicant assessment in the various contexts of industrial and service sectors. The data was gathered by semi-structured interviewing of human resource specialists and recruiters of various organizations and complemented with recruitment statistics and logs of the artificial intelligence system. Thematic analysis showed that there were significant benefits, such as a 50-70 percent decrease in time-to-hire across sectors, improved the matching of candidates and employment, and decreased unconscious bias. In addition to such shortcomings as high implementation costs, algorithmic ambiguity, and a weak infrastructure caused by unstable power conditions. Some of these issues encompass resistance to change as a result of cultural factors in changing the relational hiring, privacy issues when there is no strong governance, and the risk of bias when using artificial intelligence models that are trained on small local datasets. This suggests the use of a human-artificial intelligence hybrid, investing in digital infrastructure and training algorithms locally in order to maximize artificial intelligence usage. The results add to the human resource management research on the integration of technology in the emerging markets and provide practical advice to firms facing digital transformation in Pakistan.