Reconstructing Leadership

Higher education, a core institution of knowledge production, faces post-pandemic crises of escalating faculty burnout and turnover within an increasingly digital society. While transformational leadership is vital, its traditional form is increasingly ineffective within AI-suffused academic ecosystems. This study therefore proposes the AI-STAR Leadership Model (Artificial Intelligence-Integrated Support, Transparency, Action, and Resilience), a novel socio-technical framework that reconceptualizes the “Stimulus-Organism-Response” (S-O-R) paradigm. It examines how the technology of AI, when structurally integrated as a constitutive element of leadership praxis rather than a mere tool, fosters new social dynamics to augment transformational leadership and cultivate sustained faculty organizational commitment. Guided by the PRISMA 2020 framework, a systematic review of thirty-two empirical studies (2018–2025) was conducted. The findings reveal that AI, via non-instrumental integration, restructures the core components of transformational leadership. For instance, open-source algorithm auditing operationalizes idealized influence, activating the dual-path mechanism of “supportive scaffolding” to enhance efficacy and “trust calibration” to reestablish procedural fairness. Resource endowment significantly moderates path dominance and commitment type, with high-resource institutions fostering affective commitment (emotional attachment) and low-resource institutions bolstering continuance commitment (cost-based retention). The AI-STAR model resolves the instrumental paradox of AI, demonstrating its constitutive nature as a fundamental element of leadership. It also provides resource-differentiated implementation strategies for enhancing faculty commitment across diverse university contexts, offering a blueprint for technological integration that strengthens the social fabric of knowledge organizations.