Tools versus rules: School leaders as protectors of collective professional capital under the shock of generative AI
This qualitative study of 17 educational leader candidates interrogates how future administrators negotiate generative artificial intelligence's (GenAI) disruptive insertion into P-12 school activity systems. Framed by the integrated lenses of Professional Capital theory and Cultural-Historical Activity Theory (CHAT), the research traces systemic contradictions between rapid algorithmic capabilities and lagging institutional rules, professional norms, and layered, entrenched divisions of labor. Data were generated via open-ended pre and postcourse surveys during a graduate leadership preparation course in summer 2025, intersecting with an acute macrohistorical shock: the public popularization of an MIT Media Lab preprint warning of GenAI causing student “cognitive debt.” Baseline findings reveal severe primary and secondary contradictions characterized by an acute fear of automated deprofessionalization, curriculum deskilling, and the depletion of teacher decisional capital under rigid district policies. However, post-intervention reflections indicate microlevel movements along an expansive learning cycle. When leadership preparation intentionally mobilizes social capital through collaborative theoretical reflection, candidates shift from defensive, rule-bound policy enforcement toward critical AI literacy. Ultimately, this article offers a conceptual framework for leadership preparation programs to buffer school ecosystems against external narrative panics, resolve institutional friction, and sustain human professional capital against automated erosion.
Authors
- Jess L. Gregory (ORCID: https://orcid.org/0000-0003-1343-0563)
Institutions
- Southern Connecticut State University (US)
Publication Details
- Journal
- Management in Education
- Published
- 2026-10-14
- DOI
- https://doi.org/10.1177/08920206261494941
- Primary Topic
- Teacher Education and Leadership Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00