The Impact of AI-driven leadership Capability on Sustainable Performance in the Egyptian Financial Regulatory Authority

Younis, Zeinab Shawky; Mostafa, Bassant Adel

doi:10.21608/msamsj.2025.406594.1122

The Impact of AI-driven leadership Capability on Sustainable Performance in the Egyptian Financial Regulatory Authority

Document Type : Original Article

Authors

¹ The British University in Egypt- faculty of Business Administration, Economics and Political Science, Business department

² The British University in Egypt, Faculty of Business Administration, Economics and Political Science, Business department

10.21608/msamsj.2025.406594.1122

Abstract

This study investigates the influence of AI-driven leadership capabilities on sustainable performance within the Egyptian Financial Regulatory Authority. There is a growing need to understand the impact of AI technology on shaping leadership roles in Public Sector organizations. Despite emerging literature on AI’s role in leadership, limited empirical research addresses its effect on performance in regulatory environments. The study aims to conceptualize and measure AI-driven leadership capabilities (Technological, Adaptive, and Transformational leadership) through the lens of Dynamic Managerial Capability theory and assess their effect on sustaining organizational performance in the Egyptian Financial Regulatory Authority. A cross-sectional quantitative design is adopted, using a structured survey administered to senior and mid-level leaders at the FRA. The study investigates how these AI-driven leadership capabilities contribute to sustained organizational performance. This research offers practical implications for policymakers by providing actionable insights into the competencies needed to lead effectively in AI-integrated environments. The study highlights critical gaps in readiness and digital capability that must be addressed to support sustainable systems. While prior research has explored AI-driven leadership in technology-intensive or private sector settings, this study pioneers by focusing on a public-sector regulatory body. This research extends existing literature and offers a unique empirical contribution to AI-leadership studies.

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