📨 AI for Social Impact Newsletter

👋 From the Editor

Hi! I’m Joanna. I’m on a mission to help folks in the social impact sector understand, experiment with, and responsibly adopt AI. We don’t have time to waste, but we also can’t get left behind.

Let’s move the sector forward together. 💫

🧠 EDUCATION

• Data Integrity: The adage "garbage in, garbage out" applies more than ever with AI because no matter how sophisticated your AI tool is, messy data means unreliable output. Taking steps to ensure your data is accurate, consistent, and well-organized is essential before AI can create efficiencies. Think of data integrity like building a solid foundation for a house, which might include cleaning your databases, standardizing naming conventions, or clearly labeling information. Then you can consider where AI might help enhance data retrieval or analysis.

• System Prompts: System prompts are like the instruction manual that tells AI how to handle data: the rules, processes, and boundaries that shape its behavior. When companies create specialized AI tools (like an AI grant writer, for example), they essentially have an invisible layer (a system prompt) that defines the AI's role, tone, process, and guardrails before you type a single word. Of course there’s so much more that goes on behind the scenes in developing specialized AI tools, like training, and of course, data integrity.

✨ INSPIRATION

• Leading with Data: The KPMG U.S. Foundation awarded $6 million in grants to various nonprofits, helping them integrate AI into their operations. From Dream Charter Schools integrating AI into its operations and curriculum to the National Health Alliance on Mental Illness leveraging AI to improve operational systems and workflows, all of these AI use cases have one thing in common. Data integrity is at the core of their AI implementation.

• From Data Chaos to Clarity: A Florida-based nonprofit with seven business functions stored information across siloed systems, creating data challenges that negatively impacted productivity and budgets for over 1,000 employees across more than 20 locations. The solution? They implemented a cloud-based CRM that integrated all operational functions into one platform, completely transforming their data environment at a fraction of the original cost.

🚀 ACTIVATION

• Conduct a Data Audit: Before implementing any AI tool, spend some time reviewing a key dataset in your organization. Ask yourself: Are naming conventions consistent? Are fields clearly labeled and complete? This quick audit can reveal where your data needs cleaning before AI can help and identifies which databases should be your first priority for standardization.

• Level Up Your Data Practice: Implement regular data audits and train your staff on standardized processes so everyone enters information the same way. Use dropdown menus for commonly repeated fields like states, prefixes, and donor types to reduce manual entry errors before they happen. Remember: data integrity is an ongoing journey!

🤖 What I Asked AI This Week

Can you please write a haiku about the post-holiday season slump and going back to work in January?

Tinsel packed away
The gray commute begins again
Cold desk, colder heart

❄️🧣🩶

💬 What Do You Think?

This newsletter is meant for you, so I’d love to hear what you think. 💌 Reply anytime!

👀 ICYMI

If you’re new here, welcome! You can check out the archive of past issues here.