The integration of Artificial Intelligence (AI) into higher education has emerged as a critical factor in shaping institutional strategies, governance, and leadership practices. Guided by the paradigm of Digital Leadership 4.0, higher education leaders are increasingly required to adapt their competencies to align with the technological transformations of the Fourth Industrial Revolution. This study conducts a systematic literature review (SLR) to examine the theoretical foundations, research instruments, statistical analyses, gaps, and future recommendations concerning AI and digital leadership in higher education institutions. The review demonstrates that while technology adoption frameworks, particularly the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, dominate the field, there is a growing emphasis on leadership-oriented perspectives such as Transformational Leadership Theory, Dynamic Capabilities Theory, and Leadership 4.0 models. Methodologically, the field reflects a dual approach: quantitative surveys and SEM-based analyses are widely applied to explore adoption factors, while qualitative case studies and interviews capture leadership practices and ethical challenges. However, the literature remains fragmented, with limited longitudinal, cross-sectoral, and cross-cultural studies. The findings highlight several gaps: insufficient integration of leadership competencies into AI adoption models, underrepresentation of small and medium-sized institutions, and inadequate attention to ethical governance, transparency, and sustainability. By synthesizing theoretical, methodological, and practical insights, this study contributes to advancing scholarly and practical understanding of AI-driven digital leadership in higher education. The results underscore the urgency of cultivating visionary, ethically grounded, and technologically competent leaders who can guide universities through the complexities of digital transformation.