AI for nonprofits: where it helps first

What AI means for a nonprofit

AI for nonprofits is not a robot running your charity. It is software that handles repetitive reading, writing and sorting so your people spend more time on programs and donors.

Think of the work that fills a small team's week: thank-you notes, grant reports, volunteer scheduling, data entry. Those tasks follow patterns, and AI is good at patterns.

It is not good at deciding who your mission serves or how to tell a donor's story with care. That stays with your team.

• Drafting: first versions of emails, reports and updates
• Reading: pulling key facts out of forms and documents
• Sorting: routing messages, requests and records
• Reporting: pulling numbers into a clear summary

How many nonprofits use AI today

• 82%

  of nonprofits say they use AI

  BDO, via Nonprofit Quarterly

• 44%

  use it for forecasting, budgeting and payments

  BDO, via Nonprofit Quarterly

• 76%

  have no AI strategy yet

  TechSoup, 2025

Adoption is already high. A BDO 2024 benchmarking survey, reported by Nonprofit Quarterly, found 82 percent of nonprofits say they use AI, with financial tasks the most common use.

The same survey found 44 percent use it for forecasting, budgeting and payment automation.

GivingTuesday's 2024 readiness report found 68% of people had already tried AI in their work. Use is spreading faster than planning.

TechSoup's 2025 benchmark found 76 percent of nonprofits don't yet have an AI strategy. Using a tool and having a plan are different things.

Fundraising and donor communications

Fundraising is where many teams look first. Nonprofit Quarterly puts the question this way: every day we hear more about what AI can do in fundraising, so how should a development director think about it?

Its answer is in the headline of that piece: using AI for fundraising still requires human strategy. AI can speed up the work around a campaign. It cannot choose your message or build a relationship.

Good uses are the repetitive parts: drafting donor updates, personalizing thank-you notes, sorting replies and keeping records current in your CRM.

• Thank-you and receipt messages drafted for review
• Donor updates adapted to each audience
• Lapsed-donor lists flagged for a personal follow-up
• Gift records matched and cleaned in the CRM

Grant work and reporting

Grant work is paperwork-heavy. Applications reuse the same facts about your mission, budget and outcomes, written a little differently each time.

AI can pull past answers into a first draft, check a draft against the funder's requirements and gather program numbers for a report. A grant writer then edits and approves.

Reporting follows the same pattern. Instead of copying figures from three spreadsheets, a workflow can collect them and prepare a summary for your director.

Volunteer and program administration

Behind every program is admin: intake forms, volunteer sign-ups, shift reminders, attendance records and eligibility checks.

This is steady, repetitive work, which makes it a strong fit for automation.

It matters in AI in human services too, where case notes, referrals and intake paperwork take time away from the people being served.

Keep a person in the loop wherever a decision affects someone's access to help. AI can prepare and route. Staff decide.

• Volunteer sign-ups confirmed and scheduled automatically
• Reminders sent before shifts and events
• Intake forms read and entered into your records
• Referrals routed to the right staff member

Data privacy and donor trust

• <10%

  of nonprofits have official AI policies

  CEP, via Nonprofit Quarterly

Donors and clients share personal details because they trust you. Any AI tool that touches that data puts the trust at stake.

Policies are thin. The Center for Effective Philanthropy, as reported by Nonprofit Quarterly, found less than 10 percent of nonprofits have official policies around using AI.

A one-page policy is a good first step. It says what data may go into which tool, who checks outputs and what is never shared.

• Decide which data is off limits, such as health or case details
• Check what a tool does with the data you enter
• Require a person to review anything sent to donors
• Tell donors plainly when AI helps with their messages

Risks to plan for

AI tools can write confident text that is wrong. A made-up statistic in a grant report or donor letter hurts credibility.

Tone is another risk. A message that feels generic or automated can weaken a donor relationship you spent years building.

Cost and sprawl matter too. Many tools signed up for by different staff create scattered data and unclear ownership. One owner and a short list of approved uses prevent that.

How a small nonprofit can start

Start with one process that eats staff hours every week and follows clear steps. Gift acknowledgments, volunteer scheduling and monthly reporting are common first picks.

Write down how the process works today, who touches it and how long it takes. That gives you a baseline to judge results against.

Automate that one process with a person approving the output. When it works, add the next one. A process map helps you see where the hours go before you build anything.

Many teams ask whether they need a technical staff member. Usually not: the builder handles the setup while staff approve each step.

For a wider view of planning, see our guide to AI strategy, and our walkthrough of how to implement AI step by step.