The influence of artificial intelligence on recruitment and selection practices at Inverness Consulting Group
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Date
2026-05-26
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Uganda Christian University
Abstract
Firstly, the main objective of this study is to investigate the impact of AI on the recruitment and selection process at Inverness Consulting Group. Based on this main objective, there are three main research objectives for this study, which include determining the extent of AI adoption in recruitment and selection, the impact of AI adoption on the recruitment process and finally challenges and ethical considerations concerning the use of AI in recruitment. The methodology used in this study included the use of a cross-sectional design, where both quantitative and qualitative approaches were employed. Data were obtained from 38 out of 46 selected staff members through the questionnaire while six key informants were also interviewed. The results indicate that there is a moderate level of AI adoption in recruitment and selection (mean score = 3.29), especially candidate sourcing and managerial support. Similarly, there is also a moderate positive effect of AI adoption on recruitment efficiency and effectiveness (mean score = 3.40), especially screening time (mean = 3.61) and administrative tasks (mean = 3.89). However, the fairness perception was still quite low (mean=2.79). The challenges faced along with ethical concerns were 3.19, which were mainly algorithmic biases (mean = 3.71) and lack of adequate guidance through policies (mean = 2.84). There was an observed medium positive correlation (Pearson correlation = 0.503, p<0.05) between the use of AI system and AI bias perceived by respondents. Multiple regression results revealed that ethical concerns (β=0.233, p=0.010) and use of AI recruitment systems (β=0.198, p=0.049) were significant predictors of difficulties in implementation, with all three predictors accounting for 41.2% of the variance in challenges (R²=0.412). It could be summarized from the findings above that the application of AI is still partial, as the fundamental tools are present while other advanced techniques are yet to be developed and implemented. Moreover, although AI speeds up processes, it lacks the contributions towards increasing fairness and effectiveness in HRM. Ethical concerns, as well as biases and poor guidance policies, constitute major hurdles in responsible AI application. The recommendations offered to managers were to introduce continuous training programs for employees, explainable AI, better data governance and ethical policies, and pilot projects of candidates' facing AI tools.
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Undergraduate