Artificial Intelligence-Augmented Decision-Making in Educational Leadership: A State-of-the-Art Synthesis of Cognitive Automation and Strategic Human Oversight

Abstract

his paper explores the concept of artificial intelligence (AI) systems integration in the decision-making process. Although widespread, with 67 percent of school districts and 73 percent of higher education institutions adopting AI-enhanced services by 2024, educational administrators are confronting such critical issues as cognitive deskilling, algorithmic incomprehensibility, and undermining the professional judgment. Based on a concurrent mixed-method design, this study examined the responses of 156 leadership personnel (superintendents, principals, and provosts) in 89 institutions, based on a newly validated AI-Augmentation Decision Index (AADI). The results indicate that the institutions with the level of Augmentation Maturity 4 reduced the strategic decision cycle time by 52% and enhanced the quality of instructional decision by 38%. On the other hand, premature automation in the absence of metacognitive control was associated with 41 percent rise in ethical transgression and 37% reduction in leadership self-efficacy. It produced five fundamental design principles of cognitive symbiosis, including transparent algorithmic interfaces, calibrated trust protocols, decision decomposition frameworks, metacognitive governance and continuous learning loops. The article reveals a testable implementation roadmap of designing decision systems that enhance and not diminish human strategic intelligence in the education sector.. There is a need to conduct future research on longitudinal effects of leadership development and student outcomes.