Leading the Redesign: Purpose, Ecosystems and Sequencing in School Leadership for AI

Most school responses to generative AI begin with tools: which platform to license, which training day to run, which policy to publish. This article argues that the order is backwards. Drawing on a practitioner newsletter series written for school leaders in 2026, read alongside research on curriculum reform and institutional change, it examines AI in schools as a leadership problem. It sets out five pressures that leaders face: a speed gap between students' adoption of AI and institutions' capacity to govern it; a purpose question about what school is for when knowledge is freely available; an ecosystem problem, in which reforms fail not at the design stage but in the system of assessment, professional learning and routines they land in; a sequencing problem, in which institutions buy tools before doing the human work that makes them useful; and a structural shift in which families increasingly unbundle schooling. It proposes a five-step leadership sequence (purpose, conversation, red lines, ecosystem align‐ ment and iteration) and argues that leaders should separate two decisions that are usually treated as one: what AI should free time for, and how fast the institution should move.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23774160
Primary Topic
Artificial Intelligence in Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Leading the Redesign: Purpose, Ecosystems and Sequencing in School Leadership for AI

Paul Penfold
6 links
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Education
article

Leading the Redesign: Purpose, Ecosystems and Sequencing in School Leadership for AI

Paul Penfold
article en

Abstract

Most school responses to generative AI begin with tools: which platform to license, which training day to run, which policy to publish. This article argues that the order is backwards. Drawing on a practitioner newsletter series written for school leaders in 2026, read alongside research on curriculum reform and institutional change, it examines AI in schools as a leadership problem. It sets out five pressures that leaders face: a speed gap between students' adoption of AI and institutions' capacity to govern it; a purpose question about what school is for when knowledge is freely available; an ecosystem problem, in which reforms fail not at the design stage but in the system of assessment, professional learning and routines they land in; a sequencing problem, in which institutions buy tools before doing the human work that makes them useful; and a structural shift in which families increasingly unbundle schooling. It proposes a five-step leadership sequence (purpose, conversation, red lines, ecosystem align‐ ment and iteration) and argues that leaders should separate two decisions that are usually treated as one: what AI should free time for, and how fast the institution should move.

Zenodo (CERN European Organization for Nuclear Research)
Quality education
Openalex Percentile: Top 7%
Artificial Intelligence in Education
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