How to Fact-Check Nonprofit AI Content Before You Hit Publish

We’ll be the first to admit that artificial intelligence can be a game-changer when it comes to drafting copy. Instead of a creative block, you can ask your favorite LLM to write a draft of an email, spin up some social copy, or help you outline a program report. You get a draft in seconds. 

But while they may be speedy, your favorite AI tools can’t be trusted to respect the truth, ethics, or your organization’s reputation. 

If you publish AI-generated content without a human reviewing it, you risk spreading misinformation, breaching trust, or compromising the dignity of the communities that you work with. And that is precisely why every time you draft copy using AI tools, it should go through a strict human check.  

To help make it easy, we’ve put together an AI Validation Checklist, which will help you audit your AI content across four core categories—Safety, Ethics, and Governance; Accuracy & Verification; Tone & Emotional Authenticity; and Brand Alignment. 

If you want a quick reference guide that you can download or print out and refer back to, you can get the PDF. If you want to put this into action right now, you can copy and paste the AI Validation Prompt and put it right into whatever AI tool you’re using. 

Plus, we’ve included some tips and tricks at the end of this piece to prompt your technology to challenge its own work and get you better outputs. 

The AI Validation Checklist

Here’s what the checklist covers and what you should be keeping an eye out for as you refine and edit your AI-generated content. 

Safety, Ethics & Governance: Are You Protecting Your Data?

Before you even enter a prompt into an LLM, make sure to strip out anything sensitive—donor names, gift amounts, personal details about the people you serve or about your supporters. 

We can’t repeat this next part enough: You should always, always, always be crystal clear on which AI tools at your org are safe for private data and which ones are not. Free and personal plans of AI tools shouldn’t see data you wouldn’t want stored outside your own systems. 

After you generate content, you’ll want to check to make sure that your draft is painting the right picture and respecting the communities that you serve. AI tends to default to the dramatic version of any story, and standard AI tools are trained on vast internet datasets that often lean on pity-based narratives, helpless framing, or outdated tropes to generate emotional resonance. Language should never reduce someone to their hardship instead of their story. 

Another thing to check in this category is your citations and copyright. AI tools often scrape and blend copyrighted material without giving credit where credit is due. Make sure that your draft does not plagiarize existing articles, and verify that any quotes or unique ideas are not only correct but also properly credited to their original human creators. 

Accuracy & Verification: Is Your AI Telling You the Truth? 

In a similar vein to citations, you’ll want to make sure that any statistics, impact metrics, program names, and partner details are accurate. As noted above, AI can have a flair for the dramatic, and that can include making up data and information that doesn’t exist. 

If you can’t verify a claim in five minutes, cut it. It’s better to have a slightly more vague sentence than some data point that is totally fake.

Open a new tab and confirm every claim against an independent source. Don’t blindly trust the citation the AI hands you because the original source may not actually say what the AI claims, or it may not exist at all. 

From there, confirm any donor and beneficiary details are real. AI will invent realistic-sounding placeholders if it doesn’t have your actual data. You’ll also want to click any links that are provided to confirm that the page actually exists and that it says what the draft claims it says.

Tone & Emotional Authenticity: Does Your AI’s Writing Sound Like You?

Once you’ve checked for the ethics and accuracy points above, read the draft aloud. If you stumble over a sentence or find yourself sounding robotic (not quite Siri, but close) as you read it, you should rewrite it. 

If you’re writing to a donor, make sure to follow that with a donor-centricity check. Is the donor’s impact treated as the central part of the story rather than your organization’s budget? 

Another thing to be on the lookout for is what we like to call “AI-isms,” aka the specific vocabulary terms that show up over and over again in LLMs and read as robotic once you know to look for them. 

Keep an eye out for phrases like these, as they can become a dead giveaway of AI-generated content:

• Dramatic buzzwords like groundbreaking, tapestry, testaments, landscape, beacon of hope
• Corporate action verbs like leverage, harness, cultivate, supercharge, streamline
• AI transitions & setups like at its core, fundamentally, honestly, in today’s landscape, consequently, furthermore, moreover, listen

And these are just a few of them. If you start to use AI more, you’ll likely start to notice other dead giveaways (or you can check out the barrage of clearly AI generated LinkedIn posts by “thought leaders” complaining about how AI is hijacking beloved literary devices like an em dash).

Brand Alignment: Is Your AI Following Your Org’s Rules?

You should also conduct a final pass on your draft to make sure it sounds like your specific organization, not a generic nonprofit template. 

Check that the AI followed your organization’s rules for capitalization, acronyms, and formatting (such as using the Oxford comma). AI tools also love using vague calls to action like “Join us in making a difference today!” 

You’ll want to make sure to replace those generic phrases with specific, concrete directions, such as “Donate $25 to fund a box of fresh produce for a local family.”

You Can Also Copy-Paste This AI Validation Prompt Into Your LLM Tool

That validation checklist covers a lot; we know. That’s why we have a ready-to-use prompt that you can use to run all of those checks during your next AI drafting session. 

All you need to do is copy the prompt below and paste it in before you ask for a first draft, or run it against a draft you already have.

5 Additional Tips & Tricks to Prompt Better Outcomes From AI Tools

Beyond the checklist and prompt above, here are some other handy tips we thought we’d share to help you get the best results out of your AI tool. By tweaking how you frame your requests and asking your tools to check themselves, you can save yourself the work of having to majorly update the copy once you generate it.

Here are five prompting strategies to put into practice:

1. Assign a Critical Role, Not Just a Task

Most people prompt AI by giving it an assignment: “Write a reflective blog post about our most recent gala.” When you only assign a task, the tool gives you average text (read: dry, generic, and uninspiring). 

Instead, assign the tool a specific persona before you ask it to write or review:

• The Task: “Review this email draft.”
• The Persona: “Act as a skeptical grant officer who receives hundreds of applications a week. Read this proposal and point out every place where our impact claims feel vague or unsubstantiated.”

By giving the AI a critical role, you shift it from a passive text generator into an active role that allows it to better understand the scope of work at hand.

2. Ask It to Flag Its Own Uncertainty

AI does not know when it is wrong. It generates text by predicting the next logical word, which means it will state something completely made up with the exact same confidence as an established truth.

You can counter this by explicitly telling the tool to mark its own work for review. Add this directive to your prompting routine:

“If you include any specific statistics, historical dates, organization names, or external quotes, highlight them in bold brackets like this: [VERIFY THIS STAT]. Mark any claim where you lack complete certainty.”

This creates visual signposts throughout your draft. You can also explicitly ask your tools to not make up information if it doesn’t have it and, instead, leave placeholder text for you to fill in later.

3. Separate Drafting From Reviewing

Asking an AI model to draft a newsletter and critique its own work in the exact same chat thread isn’t always effective. The tool tends to defend its original choices and miss obvious errors because it is operating on the context of its previous output.

To get an honest review, treat drafting and editing as two completely separate sessions:

1. Session 1 (The Writer): Generate your initial draft, copy the text, and close the tab.
2. Session 2 (The Editor): Open a fresh chat window or start a new thread. Paste the draft in and give the AI a dedicated editing prompt: “You are an editor reviewing copy written by someone else. Identify robotic language, overused jargon, and weak calls to action.”

Starting a fresh session wipes the tool’s memory of how the text was built, allowing it to evaluate the work with a clean slate.

4. Request a Two-Stage Output

When you ask AI to fix a piece of writing, its instinct is to spit out a fully revised version immediately. This makes it hard to see what changes were made.

Slow the process down by forcing the tool to evaluate the text before it rewrites anything. 

You can structure your prompt in two stages:

• Stage 1 (Evaluation): “Read this draft and list three sections that sound overly robotic, along with any beneficiary framing that lacks dignity or agency. Do not rewrite the copy yet.”
• Stage 2 (Revision): Once you review its critique and agree with its notes, respond with: “Great. Now rewrite only those three sections based on your evaluation, keeping the rest of the text as it is.”

This two-stage approach prevents the tool from rewriting perfectly good sections of your copy.

5. Front-Load Real Constraints Upfront

Correcting AI after it generates a draft is exhausting. If you tell the tool to write a donor thank-you letter, and then spend twenty minutes telling it to remove words like “delve,” “foster,” and “transformative,” you are doing the work backward.

Give the tool your boundaries before it starts drafting:

• Specify who you are: Include your organization’s name, primary mission, and target audience.
• List your style rules: State your required reading level (such as 8th-grade level), preferred sentence length, and tone guidelines.
• Provide a negative constraint list: Tell the AI explicitly which words it is not allowed to use. For example: “Do not use the words delve, bolster, leverage, or transformative.”

When you set these ground rules upfront, the tool generates a much cleaner first draft, leaving you with minimal cleanup before you hit publish.

AI is Just Another Tool; Treat it Like One

The resources we’ve provided here will help you streamline your AI content processes and make the final results more effective. But without an experienced, passionate pro like yourself behind the keyboard, they can only go so far.

When you’re using AI to help your draft communications, always keep in mind that people in your community—including donors, volunteers, and beneficiaries—want to hear from you. They don’t want to hear from an LLM pretending to be you.

That’s why you should always be treating AI like a tool, not a teammate. It’s what you use to write better communications faster in support of the work that really makes a difference: Building and developing those personal connections with members of your community that only you can make.