Elevating talents' experience through innovative artificial intelligence-mediated knowledge sharing: Evidence from an IT-multinational enterprise

Abstract

Managing talent and growth in sizeable global information technology (IT) multinational enterprises (MNE) facing technological disruption requires a well-developed innovation strategy. This study presents novel insights into how a large MNE shared knowledge through artificial intelligence (AI) mediated social exchange using effective global talent management (GTM) strategies. Analyzing in-depth qualitative interview data from an extensive global technology MNE subsidiary, this research draws upon the literature on the knowledge-based view (KBV), AI-mediated social exchange theory and GTM, and explores how, through an AI-mediated knowledge-sharing exchange, the MNE managed its knowledge needs. Findings suggest AI-enabled talent applications improved individual experiences of talents at this MNE pursuing an innovation strategy. Findings from the data analysis suggest that first, an innovation-led strategy and culture created a social context for sharing of talent-specific knowledge through knowledge-based data systems embedded in talent-focused AI applications. Second, talent-focused knowledge sharing using AI-mediated social exchange applications resulted in talents experiencing varying personalization levels and positive experience in terms of increased job satisfaction and commitment and reduced turnover intentions. Implications for MNEs in emerging markets to manage global talents in an AI embedded digital social exchange for effective individual outcomes.