International Journal of Scientific Research and Engineering Development

The integration of Artificial Intelligence (AI) into electrical engineering organisations has redefined traditional leadership roles and introduced complex change management challenges. Despite rapid technological advancement, many organisations face difficulties aligning human capital, digital infrastructure, and strategic objectives to sustain AI-driven innovation. This study explores how leadership styles and change management frameworks influence successful AI adoption in electrical engineering contexts. Employing a mixed-methods approach—combining quantitative surveys of engineering professionals with qualitative case studies from selected AI-enabled firms—the research identifies the leadership competencies and organisational practices most critical for effective transformation. The findings reveal that transformational and adaptive leadership styles significantly enhance employee engagement, innovation diffusion, and operational agility during AI integration. Conversely, resistance to change and inadequate communication channels emerge as key barriers. The study contributes to leadership and technology management literature by proposing a conceptual model linking leadership behaviour, change readiness, and AI performance outcomes. The implications suggest that sustainable AI implementation in engineering firms requires not only technical preparedness but also a robust leadership culture that fosters learning, collaboration, and resilience.

Muhammad Arsalan, Muhammad Ayaz, Yousaf Ali, Uroosa Baig ,"Leadership & Change Management in AI-Enabled Electrical Engineering Organisations: Challenges, Strategies and Outcomes" International Journal of Scientific Research and Engineering Development, V8(6): Page(2404-2414) Nov-Dec 2025. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.