Anonymized examples from other teams. Learn from how others have walked the framework.
A faith-based microfinance NGO considered ML to predict loan defaults. They rejected at Receive when they found CGAP guidelines already addressed this.
A child sponsorship org considered using AI to write more engaging profile descriptions for sponsors. They rejected at Reject — automation would distance them from the children.
A health NGO considered a chatbot for community health workers asking common medical questions. They reimagined by adapting an existing open-source tool rather than building new.
A discipleship org considered an AI to provide 24/7 spiritual direction to new believers. They strongly rejected — the soul work belongs to humans in community.
A nonprofit considered AI-personalized thank-you letters. They reached Create but with strict guardrails: AI drafts only, human signs every letter, sender knows the donor.
These examples are illustrative. Real discernments will be more complex, more painful, and more specific to your context. The library helps you see the shape of the work.
Examples paraphrased from common patterns observed in faith-based development AI projects. Not based on any single real organization.