AI is only as useful as the data behind it. Before your organization can get real value from AI tools, you need to understand what you have, what shape it is in, and what is missing.
Most nonprofits are sitting on more data than they realize: donor records, program outcomes, survey responses, communications logs, financial reports. But scattered spreadsheets, inconsistent formats, and unclear ownership make it hard to put that data to work, especially with AI tools that depend on clean, structured inputs.
This session gives your team a practical framework for thinking about data readiness. We walk through what "good data" looks like in an AI context, how to audit what you currently have, and where the most common gaps tend to show up. We also cover the fundamentals of data privacy and consent, so your team understands the ethical and legal considerations before any AI tool touches your information.
You do not need to be a data analyst to get value from this session. We keep everything grounded in real nonprofit scenarios and focus on the questions your team can start asking today to build a stronger data foundation for whatever comes next.
Topics Covered in this Session
Each topic is introduced with plain language, real-world examples, and time for questions.
No jargon without context.
Not all data is created equal when it comes to AI. We break down the characteristics that matter most: consistency, completeness, structure, and relevance. Your team will learn to look at their existing data through a new lens and understand what AI tools actually need to produce useful results.
Through a guided exercise, your team will map the data your organization currently collects, where it lives, who maintains it, and how it flows between systems. This audit is the first step toward understanding your strengths and identifying the gaps that could hold back AI adoption.
Duplicate records, missing fields, inconsistent naming conventions, siloed systems: these are the issues that trip up AI implementations. We walk through the most common data problems nonprofits face and share practical, low-cost strategies for cleaning things up over time.
When AI tools process your data, new questions arise about privacy, consent, and trust. We cover the basics of what your team needs to know: what data should and should not be shared with AI tools, how to think about consent in an AI context, and how to build policies that protect both your organization and the people you serve.
We close with a forward-looking framework for organizing and maintaining your data so it is ready when you are. This includes practical steps your team can take immediately: establishing naming conventions, consolidating sources, assigning data ownership, and creating simple documentation that future AI tools can work with.
Designed to Meet You Where You Are
Every session is interactive and tailored to your team's experience level and goals.
90 Minutes
Enough time to go deep without overwhelming. Includes live Q&A throughout.
In Person or Virtual
Available on-site in Colorado or via live video for remote teams anywhere.
No Prerequisites
Built for anyone who works with organizational data. No technical background needed.
Built for Your Team
This session is designed for anyone responsible for collecting, managing, or making decisions with organizational data.
Ready to Get Started?
Details forthcoming in March 2026.
Reach out now to reserve your session or learn more about pricing and availability.