Get Better Results from the AI You're Already Using: A Strategy Guide for Nonprofits
Haphazard AI adoption doesn't make much impact. Nonprofits need specific policies, workflows, and data foundations to get better outcomes from AI while protecting the people they serve.
Inside this guide, you'll discover:
Why AI adoption stalls at the individual level
Three gaps explain most of it: no shared norms or governance, a data foundation too fragmented to build on, and a lack of clear links between individual AI use and organizational goals. The fix for these problems needs to be strategic.
What responsible AI use looks like in practice
Seventy-six percent of nonprofits have no formal AI policy, and 47% of staff who use AI do so through unprotected personal accounts. Learn what data privacy, donor transparency, bias review, and environmental impact accounting you can put in place.
How AI is changing nonprofit marketing operations
Content strategy, search, social, and design. Organic search traffic for nonprofits dropped 13% last year as AI-generated answers replaced clicks. This guide covers what it takes to become a source those answers cite, and how a one- or two-person team can run a coordinated program.
What you need to optimize your donor database
AI can't personalize what your data doesn't track. This guide walks through the contact properties, lifecycle stages, and donor journeys that need to exist before automation does anything useful, and you'll get a readiness checklist you can run against your own system this week.