AI-Powered Talent Intelligence and Leadership: Empirical Insights from Smart Enterprises

Amena  Muhammed Ali

Abstract

This empirical study explores the transformative role of AI-powered talent intelligence in shaping leadership effectiveness within smart enterprises. As organizations increasingly adopt advanced artificial intelligence tools – including cognitive, generative, and sentient AI – leaders are empowered to make data-driven, predictive, and adaptive decisions that directly influence workforce performance, engagement, and organizational agility. The study investigates how AI-enabled insights into employee skills, performance trends, and sentiment data inform leadership practices, enhance decision-making quality, and support strategic alignment with organizational objectives. Using a mixed-method approach, data were collected from HR managers, team leaders, and employees across multiple smart enterprises to examine the relationship between AI-powered talent intelligence and leadership outcomes. The findings reveal that leaders leveraging AI tools can anticipate workforce challenges, customize development programs, and respond proactively to employee needs, resulting in improved team performance, higher engagement, and greater organizational adaptability. Moreover, the study identifies critical challenges associated with AI adoption, including ethical considerations, data privacy, and technology integration barriers, emphasizing the need for comprehensive change management strategies. By providing empirical evidence on the impact of AI-driven talent intelligence on leadership effectiveness, this research contributes to both theory and practice, offering actionable insights for organizations aiming to enhance leadership capabilities, optimize human capital, and sustain competitive advantage in the era of smart enterprises. The study also highlights future research directions to further explore AI integration in HR and leadership across diverse organizational contexts.

Abstract

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