AI Foundations for Advancement Professionals-Recording

Video Transcription

Video Summary

Ashley Bud and Adam Compton led a workshop on using AI in advancement, focusing on practical, responsible adoption. They introduced themselves as non-experts who have learned by experimenting, and used polls to gauge attendees’ AI experience, biggest concerns, and advancement roles.<br /><br />The session was split into two parts: foundations and customization. In the foundations section, they emphasized four key principles: AI outputs are probabilistic, not factual; humans remain the final decision-makers; trust with audiences is fragile and must be protected; and human review and accountability are always required. They also framed AI’s value in advancement as a way to address high volume, personalization demands, and capacity constraints.<br /><br />A major topic was prompting. They showed how stronger prompts include context, goals, audience, guardrails, output format, and review expectations. They demonstrated how AI can support difficult donor conversations, drafting emails, formulas, checklists, decision trees, research, and process workflows. Attendees practiced improving prompts in real time.<br /><br />They then covered agentic AI, which differs from generative AI by acting more autonomously and completing tasks on a user’s behalf, such as research, follow-up, or stewardship workflows. They stressed that agentic tools require stricter governance, transparency, and clear boundaries.<br /><br />In the customization section, they explained how to build custom GPTs using knowledge bases, instructions, use cases, and structured output rules. They shared templates and resources for a writing-focused custom GPT, plus examples using code, web tools, and AI-generated images. The workshop closed with Q&A, emphasizing that AI should expand capacity and support human relationship work, not replace it.

Keywords

AI in advancement

workshop

practical adoption

responsible AI

prompt engineering

human review

probabilistic outputs

donor communication

custom GPTs

agentic AI

stewardship workflows

personalization

advancement strategy

governance

capacity constraints