In the rapidly evolving context of the Fourth Industrial Revolution, organizations in emerging economies face heightened volatility, skill shortages, and institutional instability. Talent has become an indispensable strategic resource for sustaining competitive advantage, yet traditional, intuition-driven talent management models have struggled to respond effectively to these complex challenges. Conventional human resource practices in developing markets are constrained by fragmented labor data, limited forecasting capability, and reactive approaches to leadership development. Such models fail to equip organizations with the agility and foresight necessary to navigate uncertain business environments. This study investigates how data-driven talent management systems (DDTMS) can be strategically integrated to foster sustainable leadership development and organizational agility in emerging economies. It argues that leveraging data analytics in HR is not merely an operational enhancement but a strategic imperative—critical for predicting workforce needs, nurturing leadership pipelines, and ensuring long-term business sustainability.Employing a qualitative multiple-case study design, the research examines four organizations from Brazil, Vietnam, and Kenya that have implemented DDTMS. Data were collected through semi-structured interviews with senior HR leaders and C-suite executives, complemented by internal company documents and publicly available reports. A thematic analysis approach was used to interpret the data and identify cross-case patterns.The study reveals that DDTMS enabled organizations to transition from reactive to predictive talent management. Analytics-based forecasting allowed firms to anticipate skills gaps, deploy agile project teams, and align leadership development programs with future business scenarios. Predictive modeling improved accuracy in identifying high-potential employees, while personalized learning pathways enhanced engagement and retention. Notably, the findings highlight that data systems function as institutional substitutes, compensating for weak external infrastructures by creating internal ecosystems of reliable, actionable intelligence.The study concludes that integrating data-driven systems into talent management is a strategic lever for sustainable organizational transformation in emerging economies. Theoretically, it introduces an integrated framework linking analytics, talent management, and leadership sustainability, demonstrating how technology can substitute for institutional voids. Practically, it proposes an actionable implementation model emphasizing executive sponsorship, iterative adoption, and ethical data governance. The paper calls for future research into AI-enabled leadership development and the extension of these practices to small and medium-sized enterprises (SMEs) to broaden inclusivity and resilience in the next generation of global leaders.
Keywords: Data-Driven Talent Management, Human Resource Analytics, Sustainable Leadership Development, organizational agility
