Algoritmic Leadership: Literature Review Of Opportunities And Challenges In The Digital Age

Abstract

The rapid advancement of artificial intelligence, big data, and algorithms has revolutionized leadership practices across diverse sectors, fostering a transition toward adaptive and technology-driven approaches. Conventional leadership models grounded in experience, intuition, and hierarchical authority are being challenged by emerging paradigms emphasizing agility, collaboration, and data-based decision-making. This study addresses the problem of how leadership can remain effective amid technological disruption and complexity. The purpose of this research is to identify and analyze the fundamental principles of algorithmic leadership that enable leaders to navigate digital transformation effectively. Using a qualitative research design with a literature review approach, data were collected from academic journals, books, and relevant scholarly sources discussing algorithmic leadership concepts. The results indicate that successful algorithmic leadership integrates computational thinking, ethical awareness, and human-centered values while maintaining adaptability in uncertain environments. Leaders must possess the capacity to interpret data meaningfully and align technological tools with organizational vision and human potential. The study contributes to leadership theory and practice by highlighting algorithmic leadership as a strategic competency for sustainable organizational growth in the digital age, where human judgment and machine intelligence must work synergistically to drive innovation and resilience.