AI

AI is rapidly transforming how teachers work — grading, drafting feedback, summarizing data, generating plans, and more. But there’s a growing issue most districts don’t see until it’s too late: Not all AI tools are built for K‑12, and many quietly put districts at risk. Here are the biggest dangers I’m seeing right now — and what every district leader should understand. 1️⃣ AI Tools That Create New Student Records When an AI system generates grades, feedback, goals, or perfo

A reality check for K‑12 leaders — with real examples As AI becomes part of daily work in schools, there’s a growing risk we don’t talk about enough: 👉 Staff are pasting personally identifying information (PII) into AI tools without realizing the long‑term consequences. This isn’t hypothetical. It’s a systems‑level risk — and recent incidents prove it.

Every district leader I talk to is excited about AI, but equally concerned about FERPA. And they should be. FERPA isn’t a barrier to innovation — it’s the blueprint for building AI systems that districts can actually trust. Here’s the approach we’re taking at G10 Innovations as we build AI‑powered analysis and translation tools for schools.

Most people give AI a command and hope for the best. But the biggest accuracy boost doesn’t come from better instructions — it comes from giving the AI examples. Here’s the difference between zero‑shot and two‑shot prompting, explained in the simplest way possible.

K–12 is entering an AI wave unlike anything the sector has seen before. But beneath the marketing buzz and demo videos, there’s a quiet split happening — a fundamental architectural divide that will shape which AI tools districts trust, adopt, and scale over the next decade. Most people think the big difference is features. It’s not. The real difference is philosophy — and that philosophy shows up in the architecture. Today, two very different approaches are emerging. 1. The

Everyone is talking about AI in education right now. But not all AI is created equal. In K‑12, I see two very different categories of AI applications emerging.

Across districts, we’re sitting on mountains of data — attendance feeds, gradebooks, LMS logs, behavior entries, course trends. Yet the people who need insight the most often get the least clarity. Counselors, teachers, and principals are left stitching together signals from half a dozen systems, trying to answer a simple question: