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<p>The study aims to examine the impact of artificial intelligence (AI)-savvy leadership on employee engagement in the education technology (EdTech) sector, with a specific focus on digital natives. It also explores the mediating role of AI utilization in this relationship, providing insights into fostering employee engagement through technology-driven leadership in contemporary workplaces. A quantitative approach was employed, collecting data from 281 digital natives working in EdTech companies in Delhi NCR, India. Using a validated survey instrument, the study measured constructs including AI-savvy leadership, AI utilization, and employee engagement. The data were analyzed using structural equation modeling (SEM) to test the hypothesized relationships and evaluate mediation effects. The results reveal that AI-savvy leadership positively influences AI utilization at work (β = 0.504, t = 11.332, <i>p</i> &lt; 0.05), having effect size of 0.349; AI utilization at work positively influences employee engagement (β = 0.299, t = 4.451, <i>p</i> &lt; 0.05), having an effect size of 0.079. AI utilization fully mediates the relationship between AI-savvy leadership and employee engagement. The study unfolds no influence of AI-savvy leadership on employee engagement; these findings highlight the pivotal role of leadership in facilitating effective AI integration and addressing the engagement challenges of digital natives in technology-driven workplaces. This study contributes to the emerging literature on AI-savvy leadership by integrating the Technology Acceptance Model (TAM) and JD-R theory. It emphasizes the necessity of strategic leadership in aligning AI capabilities with organizational goals and emerging workforce needs. The findings provide actionable insights for managers and policymakers in leveraging AI to create engaging work environments, particularly for the youngest demographic cohort in the workforce.</p>

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AI-Savvy leadership for enhancing AI utilization and employee engagement among digital natives in the EdTech sector

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月27日

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  • Majdi Anwar Quttainah,
  • Priyanka Sadhna,
  • Arun Aggarwal,
  • Pratima Daipuria,
  • Bhavna Bhardwaj,
  • Ishani Sharma

摘要

The study aims to examine the impact of artificial intelligence (AI)-savvy leadership on employee engagement in the education technology (EdTech) sector, with a specific focus on digital natives. It also explores the mediating role of AI utilization in this relationship, providing insights into fostering employee engagement through technology-driven leadership in contemporary workplaces. A quantitative approach was employed, collecting data from 281 digital natives working in EdTech companies in Delhi NCR, India. Using a validated survey instrument, the study measured constructs including AI-savvy leadership, AI utilization, and employee engagement. The data were analyzed using structural equation modeling (SEM) to test the hypothesized relationships and evaluate mediation effects. The results reveal that AI-savvy leadership positively influences AI utilization at work (β = 0.504, t = 11.332, p < 0.05), having effect size of 0.349; AI utilization at work positively influences employee engagement (β = 0.299, t = 4.451, p < 0.05), having an effect size of 0.079. AI utilization fully mediates the relationship between AI-savvy leadership and employee engagement. The study unfolds no influence of AI-savvy leadership on employee engagement; these findings highlight the pivotal role of leadership in facilitating effective AI integration and addressing the engagement challenges of digital natives in technology-driven workplaces. This study contributes to the emerging literature on AI-savvy leadership by integrating the Technology Acceptance Model (TAM) and JD-R theory. It emphasizes the necessity of strategic leadership in aligning AI capabilities with organizational goals and emerging workforce needs. The findings provide actionable insights for managers and policymakers in leveraging AI to create engaging work environments, particularly for the youngest demographic cohort in the workforce.