Mastering AI Prompting for Grant Writers: 4 Pointers

AI platforms have been game-changing for grant writers. Learning how to use AI tools effectively leads to improved efficiency and higher-quality proposals, leading to more grants won and more impact on the ground.

You’ve likely seen or heard many stories by now that might make you think twice about using AI for grant writing—like AI chatbots providing nonsense answers to simple questions. However, what sets expert AI users apart from the victims of (sometimes funny, sometimes serious) AI mishaps often comes down to how you approach this technology. 

AI is a tool for you, the human with context, judgment, and common sense, to master and use. It’s not a replacement for careful thought and hands-on quality control.

AI has been with us long enough now that best practices have emerged, specifically around prompting, which involves the inputs or instructions you give generative AI tools that shape their outputs. You then use these responses to compile and curate your grant proposals. Effective AI prompting can make the difference between a won grant and a jumbled proposal that fails to get noticed.

Let’s walk through four essential tips for prompting AI for grant writing tasks.

1. Remember that Context is Essential.

Generative AI is often general AI—meaning these platforms are typically designed to serve many purposes. ChatGPT, for example, is built to be useful for any situation, so it isn’t deeply trained on your particular area of operations or nonprofit subject matter.

This generalized training means you can’t provide a general or vague prompt to a generative AI tool and expect a detailed, perfectly aligned response. You have to provide it with the appropriate context to generate useful answers.

Learn Grant Writing’s guide to AI prompting recommends a four-step framework for building the appropriate context with a generative AI platform:

1. Build fundee context. Provide the AI tool with background information about your nonprofit, mission, history, specific project, and grant application. If you’ve hosted kickoff meetings with your team about the grant, try uploading transcripts. After laying this foundation, you should be able to generate helpful first drafts of your proposal sections about background, project descriptions, and goals.
2. Build funder context. Then, explain important details about the funder to the AI platform. Gather any relevant information about the funder and grant opportunity—focus areas, eligibility requirements, specific language the funder uses, etc.—and provide it to the AI. Generate a “funder profile” summary that the AI can more easily reference going forward.
3. Merge fundee and funder context. Use the combined insights, including your first background sections of your proposal and the “funder profile,” to generate drafts of the remaining sections of your proposal. Review, correct, refine, and retry as needed as you go.
4. Customize and reiterate with advanced techniques. For more complicated proposals or situations, you may need to take additional steps to refine your AI strategy. For example, you might build a custom AI model with preconfigured training and context or use multiple AI tools for different purposes in an orderly workflow.

These steps may sound like a lot of work, but by putting time and effort into these first steps, you can drastically increase the quality and relevance of an AI’s outputs, saving you significant time in the long run. If you don’t provide careful context upfront, the time required to correct and adjust the AI’s responses will mean you might as well have written it from scratch.

2. Understand the Importance of “Chain Prompting.”

When using AI for grant writing, it’s not just about what you ask the AI to generate—it’s also about how you ask it. To save time (and reduce headaches), you’ll need to master a technique that’s all about breaking down your tasks into smaller, more manageable parts. 

If you’ve ever given a vague or overly broad prompt to an AI tool, you’ve likely seen how quickly things can go off track. Why? Because, unlike humans, AI can’t make those logical leaps or fill in contextual gaps. It needs clear, structured guidance to deliver meaningful results.

So, what exactly is chain prompting? In simple terms, chain prompting is the process of breaking a complex task or request into smaller, discrete steps. 

Rather than asking AI to tackle a big question all at once, you guide it step-by-step, ensuring that it has the context it needs at every stage. This approach helps you keep the AI on track and makes it easier to get the specific responses you’re looking for.

For example, let’s say you’re planning an advocacy campaign to raise awareness about environmental policy changes in your area. This is a complex task with many moving parts, and if you simply ask AI, “Help me plan my advocacy campaign,” it might give you a general outline, but that won’t really save you any time if you then need to correct and fill it out yourself.

To get the best results, chain prompting helps you break down the campaign into smaller, manageable steps. Here is how you might approach the example above:

1. Define your main objective: Instead of asking AI for a full campaign plan, start with a specific, clear prompt, such as, “What are the key objectives of an advocacy campaign for environmental policy change in [your region]?” Clearly state your objective and any specific goals to the AI.
2. Identify your target audience: Next, ask, “Who are the key stakeholders for this environmental policy advocacy campaign? How can I engage local businesses, community leaders, and activists?”
3. List campaign tactics: After identifying your audience, move on to specific tactics. You might ask, “What are the most effective strategies for grassroots lobbying in environmental campaigns that align with my objective and goals?”
4. Set a timeline: Once you have your tactics, ask, “Can you help me create a timeline for accomplishing my goals in the next 6 months, broken down by key milestones and actions?”
5. Create messaging: Finally, ask for something more detailed, like, “What should the core message of this advocacy campaign be to appeal to local policymakers, the general public, and funders in support of [specific policy]?”

With each step, you ensure the AI understands the context and gives you a more focused response. At each stage, you can adjust and refine based on your campaign’s needs, adding new prompts like, “How can I adjust the timeline if we experience a delay in the first milestone?” or “Can you suggest a more persuasive messaging strategy for engaging local government officials?”

At its core, this technique involves clearly stating what you want, breaking it down into specific steps or components, and getting confirmation as you go that the AI has retained the context along the way.

This process doesn’t just save time—it ensures the quality and relevance of the outputs you get. By guiding AI through a logical sequence, you’re more likely to end up with a detailed and coherent result that you can use in your grant proposals.

3. Clearly Define Your AI Use Cases and Limitations.

AI is incredible, but it’s not magic. It can’t (and shouldn’t) do it all. To truly make the most of it, you need to know exactly where it shines and where its involvement might actually create more work than it saves.

AI is fantastic for tasks like research, prep work, and drafting sections of text. It can help you gather relevant grant opportunities, create first drafts for certain sections of your proposal, and organize your thoughts. When it comes to business logistics for grant writing freelancers, AI tools can certainly save you time there as well.

But just because AI is fast doesn’t mean it’s the best option for every task. When you’re deep into more nuanced or creative work, like refining your message or tackling a groundbreaking approach, that’s where human expertise shines. Remember, AI is built on patterns from past information. It can’t easily come up with “new” ideas or solutions.

Think of it this way: AI can’t be your primary driver if you’re explaining a novel approach to a problem to a funder or trying to come up with innovative strategies for your project plans. It doesn’t have the same intuition, creativity, or understanding of the unique nuances of your nonprofit’s mission that you do. Use AI carefully in these situations—it’s better as a tool to support your thinking, not replace it.

Set clear boundaries for AI’s role in your process to ensure it works for you, not against you. Defining these use cases will simplify and improve your entire experience using it. 

Of course, you can experiment and add new use cases over time as you learn the best ways to prompt AI for different purposes, but be mindful of how long this takes—if you could do a task yourself at the same level of quality in the same amount of time, it should likely live with you.

4. Use Multiple AI Tools if Needed.

Mastering AI prompting is a critical part of grant writing success, but it’s not just about crafting great prompts. It’s also about using the right tools for the job. 

Think of it like creating a masterpiece: An artist doesn’t use just one brush to complete a detailed painting. They rely on a variety of tools, each designed for a specific task. The same principle applies to AI. While crafting effective prompts is important, choosing the right AI tool for each part of the grant writing process is just as crucial. 

Even with the best prompts, if you’re using the wrong AI tool, you’ll still struggle to get the consistent, high-quality results you need.

Some different tools you can use throughout the grant writing process include:

• Research and Prospecting Tools: AI excels at scanning vast databases and bringing back relevant information quickly. For grant writing, this means tools that help you identify the right funding opportunities and learn more about funders’ giving histories.
• Writing Assistants: These tools help organize your ideas, improve your sentence structure, check grammar, and refine readability. They can also help you keep your language consistent and ensure your proposal aligns with the funder’s expectations.
• Data Analysis Tools: For proposals that require heavy usage of statistics or financial breakdowns, data analysis tools are essential. These tools help you process large amounts of information and distill it into meaningful insights that you can use to tell stories and support claims. 
• Project Management Tools: AI-powered project management tools are great for staying organized during complex grant projects. They help you keep track of deadlines, assign tasks, set reminders, and even coordinate team efforts.

All-purpose generative AI platforms like ChatGPT can fit into all of these categories—but that doesn’t mean they necessarily should. Mastering AI prompting will ensure you can use ChatGPT and similar tools effectively for all kinds of tasks, but just remember that more specialized options exist. If your nonprofit wants to invest in its AI capabilities, it’s worth your time to explore a broader range of popular AI grant writing tools. 

You can even use AI tools to support grant management and report on impact later in the life cycle (but focus on improving your grant seeking process with AI first).

When you pair great prompting with the right tools, you’re setting yourself up for success. Choose wisely, and you’ll streamline your workflow, refine your proposals, and ultimately increase your chances of securing funding. 

AI prompting helps you create more effective, targeted proposals. With clear prompts, the proper context, and the right tools, you’ll get the best possible results every time.

Just keep in mind that while AI can streamline tasks and improve efficiency, your nuanced understanding of your nonprofit’s mission, goals, and challenges is irreplaceable. When you bring your insight and vision to the table, you’ll create proposals that truly shine.