Schools everywhere are struggling to deal with AI. Thoughtful administrative leadership, deliberative planning, and collaboration can help schools lead instead of being led by the new tech.
Last year, the question in our district was, “Did a student use AI? Are our teachers using AI?”
This year, the better and stronger question is, “Are we (University Prep) going to lead this, or let it lead us?”
That shift in posture changes everything. For everyone.
In Account 1, I named the tension. AI was surfacing in student work with lightning speed, sometimes eroding the productive struggle and academic rigor that make learning meaningful and lasting.
In Account 2, I pushed my own thinking further. The issue was not simply cheating. It was bigger than that. It was clarity, equity, and whether our systems were ready for what is already here. My team and I are committed to building a framework with educators, not for them.
Now we are in motion.
My improvement plan centers on capacity building. If AI represents a foundational shift, then our response must be structural rather than reactive. We can’t keep falling behind in the name of innovation. Our Director of Data and Innovation launched an AI Innovation Lab composed of teachers and leaders across our network of schools. The charge is ambitious. To co-create a three-year AI Implementation Framework for our network while piloting AI tools in real classrooms.
What has surprised me most is the overwhelming interest from educators to participate. We anticipated cautious curiosity. Instead, we saw energy and excitement. A willingness to learn and grow. Teachers volunteered their time and efforts. Leaders asked to join. The message was clear. Our staff does not want to sit on the sidelines of this conversation. They want to shape it.
The AI Innovation Lab is not a passive think tank. It is a working design space. We are grounding our approach in partnership with aiEDU, a national nonprofit focused on preparing students to live and work in a world where AI is everywhere. That framing matters. This is not about shortcuts. It is about readiness and responsibility.
Participants are piloting tools aligned to instructional goals and sharing reflections in real time. For our math instructors and interventionists, we are placing particular focus on Edia to strengthen feedback loops and personalize practice. Early insights are encouraging. Teachers report more targeted small group instruction and quicker identification of misconceptions. At the same time, they are naming risks. Over-reliance. Superficial engagement with the content. The temptation to prioritize efficiency over depth and power of conceptual understanding.
That tension is productive. It keeps the work grounded in learning!
Beyond the Lab, we are ideating with Wayne State University around an AI microcredentialing certification for educators. The spirit of that partnership is collaboration and co-design, with a particular focus on mathematics education. We are exploring how AI can strengthen conceptual understanding rather than simply automate procedures. The goal is to build expertise together, not outsource it.
I also connected with Dr. Kendra Hearn, Associate Dean for Undergraduate Education and Educator Preparation Programs and Clinical Associate Professor at the Marsal Family School of Education. Our conversation centered on how students and staff are engaging with AI across contexts. We discussed the similarities in enthusiasm and uncertainty, as well as the growing concern about digital fluency gaps. If some students are learning to leverage AI strategically while others lack access or guidance, schools cannot remain neutral. We have to design intentionally.
Our emerging Implementation Framework is taking shape in phases. Year one emphasizes literacy and guardrails. Shared definitions. Ethical norms. Professional learning that builds confidence. Year two moves toward deeper instructional integration aligned to standards and measurable student outcomes. Year three focuses on refinement, impact analysis, and scaling what works.
We are documenting everything. Wins. Missteps. Teacher fatigue. Student reactions. This is what it looks like when thoughtful educators wrestle with an authentic problem. It is iterative. It is messy. It is deeply human.
The AI Innovation Lab will conclude in May, and our plan is to submit a robust AI Implementation Framework to our Board in June. That moment feels significant. Not because a document will solve everything, but because it will represent months of collaborative thinking, piloting, and reflection led by our own educators.
We are no longer asking whether AI belongs in our schools. We are asking how to steward it responsibly.
And I am still holding one essential question. How do we build something steady enough to guide practice, yet flexible enough to evolve as the technology inevitably shifts?
We at UPrep are leaning into one of our core academic pillars: distributed leadership. In this moment, that means we are choosing to lead. Together.