Writing AI Policy From the Ground Up

Without a shared policy, individual teachers and principals were left to work out AI questions on their own, often in opposite directions. One teacher used AI with students with no guidance in place. Another accused students of cheating with AI. Multiplied across four schools, that inconsistency created real risk: unequal expectations, unequal consequences, and no shared standard for what responsible use looked like.

Leadership saw this gap and wanted to close it with a policy rooted in the network’s own community values and written in its own language. They wanted teachers, school leaders, and students to co-author that policy.

The network didn’t have the internal capacity to conduct the research, organize a representative design team, or build a co-design process at this scale. Leadership also needed two things: the policy itself, and the ongoing capacity to keep making good, values-aligned AI decisions long after it was signed.

We provided the capacity the network didn’t have on staff. The engagement began in September 2025 and continues into 2027, spanning survey analysis, policy design, and professional development architecture.

We started by listening at scale. We conducted and analyzed baseline surveys of teacher, student, and family perspectives on AI, so every decision that followed was grounded in the network’s own data.

From there, we designed and facilitated a 14-person cross-stakeholder design team through an eight-month process. The team included the CEO, a principal, department directors, teachers, and students, representing all four schools. Together they co-developed the network’s first formal AI Use Policy, structured around the network’s existing values and covering student learning, equity, staff responsibility, tool approval, transparency, and annual review.

A policy is only as good as the people applying it. We designed a three-session pilot program for an eight-teacher cohort, sequencing field experience before policy work and teacher exploration before adoption decisions, so the policy would be tested in real classrooms.

To keep the policy in active use, we built in an ongoing policy committee structure. We continue to work closely with leadership, adjusting the program as the AI landscape in education keeps shifting.