Evaluating the Effectiveness of Artificial Intelligence in Talent Management: Evidence from Multinational Fast-moving Consumer Goods Companies

Abstract

Artificial Intelligence (AI) is increasingly transforming talent management by enhancing recruitment, employee development, workforce planning, and organisational decision-making. However, empirical evidence on its effectiveness within multinational Fast-Moving Consumer Goods (FMCG) organisations remains limited. This study examined the influence of AI adoption on talent management practices in multinational FMCG companies, focusing on organisational preparedness, recruitment and selection, employee development, performance management, employee retention, and organisational competitiveness. An exploratory mixed-methods research design combined quantitative and qualitative approaches. Quantitative data were analysed using descriptive statistics, Pearson's product-moment correlation, and one-sample t-tests, while qualitative data were analysed thematically. AI effectiveness was rated highly (M = 4.45, SD = 0.86), as were the importance of integrating theoretical viewpoints with practical AI applications (M = 4.53, SD = 0.96) and organisational preparedness for managing AI consequences (M = 4.48, SD = 0.97). AI effectiveness was positively correlated with theoretical integration (r = .630, p < .001) and organisational preparedness (r = .645, p < .001); theoretical integration and preparedness were also strongly correlated (r = .886, p < .001). Qualitative findings indicated that AI improves recruitment efficiency, workforce planning, employee development, and organisational competitiveness, while raising concerns regarding algorithmic bias, transparency, employee privacy, and organisational readiness. The study concludes that AI can enhance talent management and organisational performance when supported by effective leadership, ethical governance, organisational preparedness, and continuous employee development. The findings provide empirical support for the Resource-Based View and the Technology–Organisation–Environment Framework and offer practical guidance for responsible and sustainable AI-enabled talent management.