Artificial Intelligence and Leadership in Organizations: A PRISMA Systematic Review of Opportunities, Challenges, and Emerging Risks

As artificial intelligence (AI) becomes increasingly embedded in organizational processes, questions about its impact on leadership have gained prominence. Yet the existing literature remains fragmented. Studies often focus separately on strategy, leadership skills, governance structures, or ethical concerns, without explaining how these dimensions connect to shape leadership effectiveness in AI-driven environments. This study conducts a PRISMA-guided systematic review of 63 peer-reviewed articles to examine how AI-embedded leadership is conceptualized across contexts. By synthesizing findings across strategic, human, and governance domains, the analysis identifies recurring patterns and structural relationships in the literature. The review shows that effective leadership in AI-intensive settings does not result simply from adopting advanced technologies or developing digital competencies. Instead, it depends on the alignment between how deeply AI is integrated into decision-making processes, how leaders interpret and oversee algorithmic outputs, and how governance mechanisms ensure transparency, accountability, and trust. On this basis, the study introduces the AI-Leadership Configurational Framework (ALCF), a multi-level model that explains leadership effectiveness as the outcome of systemic alignment. The framework integrates previously disconnected debates and offers a clear foundation for future empirical research on leadership in the algorithmic age.