This paper explores the evolving nature of leadership in the context of AI integration, focusing on the transformation of leadership roles, ethical challenges and the redistribution of power and decision-making authority. It aims to offer a conceptual framework that guides leadership theory and practice in the digital age.
Using a structured literature review of sources published between 2014 and 2024, the paper synthesizes insights from transformational leadership, ethical leadership and the Cynefin framework. It also examines key organizational and human-centric challenges associated with AI adoption, including resistance to change, ethical risks and competency development.
The review indicates that in AI-mediated systems, leadership is enacted primarily as leadership governance. This involves decision-rights allocation, accountability, oversight and auditability, and escalation and human override. It also includes contesting algorithmic outputs when needed. The three domains identified (human-centred, strategic and technical) function as resources for enacting governance. Legitimacy and identity pressures rise when leaders are held accountable for AI-influenced outcomes without equivalent interpretive access or discretionary control.
For leadership educators, the findings suggest the need to move beyond generic “AI literacy” toward governance-informed learning designs that develop judgement under algorithmic mediation. Curriculum modules can explicitly combine ethical reasoning, identity work, and decision-making under algorithmic uncertainty.
The paper contributes to leadership theory by reconceptualizing transformative leadership in AI-integrated contexts as leadership governance, a sociotechnical condition defined by decision-rights allocation, institutional accountability, oversight, and enforceable escalation and override.
