Received:
2026-02-20 | Accepted:
2026-05-15 | Published:
2026-06-30
Title
Enhancing employee engagement through transformational leadership and AI use: evidence from the healthcare sector in Saudi Arabia
Abstract
The research examines how transformational leadership and AI usage affects healthcare employee engagement in Saudi Arabia. Additionally, it investigates how employee voice moderates the relationship between transformative leadership and employee engagement. The data was collected from 408 healthcare employees who worked at hospitals and healthcare facilities throughout the Kingdom of Saudi Arabia. The researcher utilized Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyze the collected data. The findings showed that the four dimensions of transformational leadership—inspirational motivation, idealized influence, intellectual stimulation, and individualized consideration—significantly influence employee engagement. The findings further show that the usage of AI technologies can lead to more employee engagement. Furthermore, the findings confirm the moderating role of employee voice in enhancing the relationship between transformational leadership and employee engagement. It concludes that employee voice enables transformational leaders to achieve higher employee engagement through settings which support open dialogue and staff involvement. This article contributes to knowledge by combining leadership theory with employee voice concepts and digital transformation elements into a single model which provides healthcare leaders and policymakers with practical methods to boost employee engagement through leadership development and AI-powered workplace technology. Specifically, it underscores the importance of transformational leadership and AI technologies in enhancing employee engagement.
Keywords
transformational leadership, employee engagement, Artificial Intelligence, employee voice, healthcare sector, Saudi Arabia, digital transformation
JEL classifications
M54
URI
http://jssidoi.org/jesi/article/6665
DOI
Pages
445-460
Funding
The authors extend their appreciation to the Deanship of Postgraduate Studies and Scientific Research at Majmaah University for funding this research work through the project number (R-2026-214).
This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License
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