Schools are being asked to adopt AI faster than most feel ready for, and the gap is rarely the AI itself — it's the data behind it. AI is only as useful as the context it can see, and in most schools that context is scattered across the SIS, LMS, assessment, attendance and wellbeing systems, each governed differently. Connect AI to one slice and you get narrow answers; connect it to everything without proper controls and you create real risk around student data.
This hands-on workshop walks through what a practical data foundation for AI actually looks like in a K-12 setting: bringing data together without ripping and replacing the systems staff already rely on, applying role-aware access so the right people see the right things, and keeping your school in control of its own data and its choice of AI tools. It's built for the people who'll have to make this work — data teams, IT and operations leaders — and you'll leave with a clear sense of the steps, the decisions, and the questions to ask before connecting any AI tool to student data.
