This post is part of Walkerscott’s “Smarter Fundraising” series based on a fireside chat featuring Katie Dudley (Partnerships & Business Development, Dataro) and Jono Walker (CTO, Walkerscott & Head of Product, Klevr Fundraising). Below you’ll find the blog summary and highlights – scroll down to watch the short video clip.
Artificial intelligence is everywhere right now, but for many fundraisers it still feels like a vague buzzword, exciting in theory, intimidating in practice. The truth is, AI is already reshaping how not-for-profits connect with supporters. When used responsibly, it can reduce admin, strengthen donor relationships, and make fundraising more sustainable.
Here’s how not-for-profits can approach AI in practical, ethical, and donor-centric ways.
1. Demystify AI and see it as a copilot
For many fundraisers, “AI” still feels like a black box, a bit of a mystery, where you see the outputs but not the steps that produced them. That lack of visibility can make AI seem intimidating or less trustworthy.
The reality is that AI is only as good as the data it learns from and the human context and prompts guiding it. Think of it as a copilot: the value comes from combining clean, relevant donor data with the fundraiser’s judgment, empathy, and strategy layered on top.
That’s why familiarity is important. Fundraisers don’t need to become data scientists, but building a working knowledge of how AI operates, and the kinds of tools available, helps remove the sense of mystery. With even a little context, AI feels less like a threat and more like a partner.
Here are a few examples of what’s useful to understand:
- Machine learning → algorithms that spot patterns in donor data and make predictions (e.g. which supporters are likely to lapse or upgrade).
- Predictive models → AI that helps forecast donor behaviour, enabling more precise targeting and engagement strategies. These models often use machine learning algorithms.
- Generative AI tools → systems like Copilot or ChatGPT that create content, from personalised donor emails to campaign summaries, using large language-based predictive models.
- AI agents → software “assistants” that use Generative AI and the ability to read and update systems to handle tasks across these systems, like suggesting next best actions or drafting follow-up emails.
The goal isn’t to master these technologies, but simply to recognise what they do and how they can support fundraising. The more familiar teams become with these concepts, the easier it is to see AI as a tool that enhances human work rather than replaces it.
2. Put donors at the centre with personalisation at scale
Audience-first fundraising has always been the goal. On a one-to-one level, it’s straightforward: if you know a donor prefers email and cares about animal welfare, you tailor your communications accordingly.
The challenge is doing this for thousands of donors at once. That’s where AI shines. By analysing signals from giving patterns and engagement behaviours, AI helps nonprofits interpret donor intent and turn it into actionable strategies.
This means truly putting donors at the centre, using their signals to guide outreach, rather than forcing campaigns to fit an internal calendar. AI works best when it’s embedded into fundraising workflows, not bolted on as an afterthought. The right tools can surface opportunities, suggest next best actions, and create precision audiences, all while freeing up time for fundraisers to focus on building relationships.
In practice, this is the first step toward the kind of tailored experience people already expect from streaming services; the feeling that “this was made for me.”
3. Use AI that understands the nonprofit context
Not all AI is built the same way. Many tools are trained on generic data, which can limit their usefulness in fundraising. By contrast, solutions like Dataro are trained specifically on not-for-profit fundraising data, meaning the predictions are directly relevant to donor behaviour, retention, and giving patterns.
When AI models understand the nonprofit context, they’re not just producing numbers, they’re surfacing insights that actually help fundraisers focus on the right opportunities at the right time.
Of course, the quality of the output still depends on the quality of your own data. A fundraising CRM that maintains clean, structured donor records gives AI a stronger foundation to work from, ensuring predictions are accurate and actionable. Together, nonprofit-trained models and a well-managed CRM create a powerful combination: AI that works with your data to make fundraising smarter, not harder.
4. Trust the foundation: secure and compliant AI
AI can only be as ethical as the environment it runs in. That’s why it’s critical to choose platforms built on secure, compliant infrastructure. With Klevr Fundraising built on Microsoft Dynamics 365 and Azure Cloud, nonprofits can be confident in data privacy, PCI compliance, and strong access controls.
At the same time, predictive platforms like Dataro add value by being trained exclusively on nonprofit data stored in secure systems, ensuring insights are tailored to the sector rather than generic patterns.
Instead of letting staff experiment with popular, off-the-shelf AI tools in isolation, which spreads donor data across unvetted platforms, organisations should keep AI embedded within their existing CRM and donor management systems. This ensures both compliance and data integrity.
5. Embed AI into the way you work
The most effective AI isn’t bolted on; it’s embedded. By integrating directly into core platforms like Microsoft Dynamics 365, AI tools such as Copilot become part of the day-to-day fundraising workflow.
That means fundraisers can use AI for segmentation, journey mapping, campaign optimisation, and even day-to-day tasks like preparing reports or drafting donor communications. It’s not about creating extra work, it’s about enhancing what you already do.
6. Free up time to focus on relationships
The biggest benefit of AI is not more data, but more time. By reducing the manual workload of reporting, research, and administration, AI frees fundraisers to spend more time where it matters: building genuine donor relationships.
“People won’t be replaced by AI, but fundraisers who learn to harness AI will outperform those who don’t.“
AI in not-for-profit fundraising is about practical, ethical, donor-first applications. By demystifying AI, demanding transparency, embedding it into trusted systems, and using it to personalise outreach at scale, nonprofits can build stronger donor relationships while reducing admin. Explore how Klevr Fundraising and Dataro bring ethical, embedded AI into the heart of your fundraising CRM.
