In a previous article, I explored why artificial intelligence cannot reliably write grant applications that succeed with assessors, the problem being that whilst AI is perfect for creating and editing beautifully written sentences, it cannot judge whether their words genuinely address what a funding body needs to see in a successful application.
So whilst AI is terrible for writing fully completed winning grant applications, that doesn’t mean it’s useless in the process. In fact, in a number of ways it’s in its elements, one of those being in the project preparation stage.
When businesses and organisations approach us at Whitney Consulting, they often arrive with brilliant ideas but incomplete preparation. Our clients know they need funding, they’ve done the work of identifying a grant opportunity, and they’re ready to engage professional writing help. However, what they don’t always have is the organised information required to actually write a strong application.
This isn’t a criticism – our clients are experts in their field, not in grant applications. Many of them have never applied for a grant before so how could they know what information they’ll need, how detailed that information should be, or how to structure their thinking about the project.
This lack of information is not the end of the world for a good grant writer, but it does create a lot of resource challenges in terms of time, finances, and stress. When good preparation is missing, it’s like hiring an architect to design your dream home but without deciding how many bedrooms you want, whether you want open-plan living or a maze of corridors, or what your actual budget is. The architect can certainly ask questions and guide you through these decisions, but the design process becomes slower and more expensive than it needs to be.
Grant writing works similarly. When clients come to us without clear project timelines, we need to spend time helping them develop those. When budget estimates are vague or missing, we need to work with them to create realistic figures. When key stakeholders haven’t been identified or potential risks considered, we need to have those discussions before we can write effectively about how they’ll be managed. All of this necessary work extends timelines, increases back-and-forth communication and sometimes means that applications get submitted closer to deadlines than anyone would prefer.
Professional grant writers need specific information to craft compelling applications such as:
- Precisely what the project will deliver and how
- Who benefits and what evidence demonstrates that need
- What resources are required and when
- How success will be measured
- What risks exist and how they’ll be managed
- Who’s involved and what they contribute
- What happens at each stage of the project
AI can act as a project partner to help you clarify all these elements. It makes for a perfect self-organisation and problem prompting tool, and research assistant.
Pre-Application
Many projects fail because they lacks clarity and the full scope of what needs to happen hasn’t been properly mapped out. Often that’s because the applicant hasn’t thoroughly explored potential challenges leaving objectives remaining vague and/or outcomes poorly defined.
AI as Your Research Assistant
Consider the initial research phase of developing a fundable project. You have an idea, perhaps even a compelling one, but you haven’t taken the time to understand the landscape. Creators of successful projects have looked at what similar projects have been completed elsewhere? They’ve seen the challenges those projects they encountered? The organisation has fully understood and researched the need for the project and the benefits it will bring to them and to the community.
We all know that AI can “hallucinate” incorrect facts and figures, but it can rapidly synthesise information from multiple sources and find relevant case studies you might otherwise spend hours tracking down. It can also help you explore angles you hadn’t considered and identify gaps in your thinking before they become problems in your application. This doesn’t replace the strategic thinking you need to do, but it does accelerates the information-gathering process that informs that thinking.
Clarifying Your Own Ideas
Ever had a project concept that feels clear in your mind but becomes muddled when you try to explain it to others? AI can help you work through this. Think of it as a rehearsal space where the stakes are low. You can experiment with different framings, explore various approaches, and identify weaknesses in your logic before those issues surface in your actual application.
By engaging with AI conversationally about your project, you can test different ways of explaining your idea. The act of articulating your concept to a system that will question unclear points forces you to sharpen your thinking. When AI asks for clarification about something you’ve described, it often reveals where your own understanding needs refinement.
Generating Strategic Questions
One of AI’s most valuable capabilities is its ability to generate comprehensive lists of questions you should be asking yourself about your project. When assessing your project and application, a funding assessor will ask themselves, “What risks might this project encounter?” “Which stakeholders need to be consulted?” “What evidence would demonstrate need in this community?” “What resources are required at each project stage?” “How will you measure success?” AI can help you with this process.
Know how to answer them yourself thoroughly gives you the confidence to know you’re working from a solid foundation, whilst saving you from discovering project-stopping gaps mid-application. This level of confidence and clarity also helps out your grant writer when you come to explain your project to them. Ambiguity kills funding applications.
Organising Complex Information
Projects often involve multiple interconnected elements: partners, timelines, budgets, outcomes, activities, beneficiaries. AI can help you structure this complexity in ways that make sense. Again, you’ll need to review and refine what AI produces. But it provides a starting structure that’s faster to improve than creating from scratch.
For example, you might ask AI to create a project timeline based on the activities you’ve described, organise various project components into a logical framework, identify which outcomes align with which activities, or spot where dependencies exist that you hadn’t explicitly recognised.
All these uses have one thing in common and that’s that they happen before the actual grant writing begins. They’re about preparation, exploration, and organisation. They’re about doing the thinking work that makes the eventual application stronger. What they’re not about is having AI write your application for you. Doing that crucial part of the funding seeking process needs a human touch.
The team at Whitney Consulting can, or course, assist with some simple elements of project planning and help guide some decisions making sure they align with grant funding requirements. Many of our clients come to us without a completely firm project, or with a number of potential ideas. However, time spent in the planning process takes time away from writing, and if you haven’t even considered the basics, then this time can be substantial.
Regardless of which pathway suits you – AI assisted or human all the way – the final stage remains the same: translating your project into an application that assessors actually fund, and that requires more than just a frilly, ultra-professional sounding set of words. That’s what the team at Whitney Consulting are here for.
