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September 11, 2025 31 mins

AI isn’t a magic wand—but it can absolutely help nonprofits do more with less when you understand what it is, where it fits, and how to use it wisely. In this energizing conversation, technology associate and CPA Christine Chacko from Your Part-Time Controller (YPTC) explains the practical difference between automation and AI, when to use each, and how to keep data safe while you experiment and learn. As Christine puts it, “AI is actually a form of automation,” but it handles open-ended, judgment-heavy tasks while traditional automation follows clear, narrow rules. Think rules for categorizing expenses (automation) versus analyzing trends, benchmarking, and surfacing insights across donor segments (AI).

Christine offers real nonprofit examples: blend automation to roll up donor data by type, then ask AI to interpret changes year over year, spot seasonality, or flag post-pandemic shifts. She shows how AI shines as a writing helper—drafting grant narratives tailored to funders’ preferences or condensing verbose copy into crisp executive summaries—while reminding us to review outputs for voice, accuracy, and appropriateness. “We really like to think of it as a thought partner,” she says, perfect for bouncing ideas, testing messages, and clarifying complex financial stories for boards.

Security matters, too. Christine’s guidance is simple and strong: read the fine print, know what you opt into, and understand the difference between models embedded in trusted systems and those that reach out to other tools. She introduces agentic AI—systems that can act on your behalf (e.g., access Outlook, browse the web, schedule emails)—and explains why permissions, policies, and internal controls must come first. Hallucinations are less frequent in newer reasoning models, but review remains essential—especially for grants and external communications where stakes are high.

Finally, Christine maps the near-term horizon: expect broader, more accessible agentic AI inside finance, IT, customer support, and daily workflows. Success won’t come from tools alone; it comes from culture—clear use cases, communication, training, and solid processes. Used well, AI reduces drudgery (transcripts, notes, routine emails) so nonprofit teams can focus on judgment, relationships, and mission results.

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