We’re using AI whether we know it or not. Now it’s time to use it with intention.
I may be the most analog person you know. I read paper books, constantly find new artistic hobbies, and spend my weekends roaming in the woods. At least once a week, I’m tempted to hurl my laptop into a river.
I’m also deeply concerned about the ways technology companies shape our world—in service of insatiable bottom lines and at the expense of our natural resources, social connection, democratic vibrancy, and wellbeing.
And yet, here I am, about to write to you all: We should be (responsibly) excited about AI.
We recently brought together a panel of incredible thought leaders to discuss how we leverage AI for donor engagement. In the video above, you can hear their experience and recommendations, which all point to our opportunity: If we take a beat and get intentional, this could be a catalytic moment for changemakers.
AI is already part of your donor engagement
Whenever I mention AI to fundraising leaders, they tell me the list of things they are not doing yet. Often, they say, “I haven’t even had a chance to think about it.” We all feel behind.
Thankfully, experts assure me that we are not behind. The truth is, everyone is figuring it out as they go—in all areas of our economy. Nonprofits are not lagging. In fact, in our sector, AI has democratized innovation and made it accessible to even the smallest of teams. Anyone with big questions and an appetite for experimentation can jump in and lead the way.
The other good news is that you’re already using it, whether you know it or not. At a rather dizzying pace, all software and service providers are integrating AI into their tools, processes, and infrastructure. Behind every CRM, fundraising platform, search engine, or research engine you use sits a team of wonky technical professionals who are figuring out how to leverage AI to make that tool more relevant, efficient, and competitive. For you, that means you don’t need to become a wonk yourself (unless, you know, that’s your thing….). You just need to ask: What do I need to know about how AI is integrated into this platform? Given what I do, how can I derive the most value from what has been developed?
The other thing to know is that your donors are using AI—in all kinds of ways. It’s in their search engines. It’s embedded into the platforms they use to find and evaluate organizations. More and more, funders are experimenting with AI as a tool for information synthesis, pattern recognition, and process automation; the best are reserving prioritization and decision-making for the humans, but increasingly with AI as an assistant.
Wherever you are, the path forward is curiosity
Given how ubiquitous AI (or at least hype about AI) has become, it can feel like the time to figure out your organization’s AI plan is, well, yesterday. On top of that, we’ve all read to leverage AI well you have to be thoughtful, strategic, selective, and future-focused.
Unfortunately, speed and thoroughness are a tall order for many leaders and fundraisers in this noisy moment. The less we feel we can make the space to get our plan together, the more behind we feel, and the more anxiety builds.
The best advice I’ve gotten from leaders who are further down this path than I am is that the best place to start is to start…
…and then to realize that your team members have probably started without you. Due to the way generative AI was brought to market, AI adoption has been predominantly bottom-up, with employees getting a way head start over their organizations as a whole. In fact, some research has found that, when asked anonymously, 60% of employees share that they use AI to do their work—even if not officially asked to do so and even if the organization does not allow it.
The proverbial cat (with too many toes) is out of the bag.
So, give in to the chaos and get curious:
Who on your team has already dipped their toe into this world?
What have they tried? What are they learning?
How have their habits changed? Workflows? Workloads?
What has become easier? Harder?
And then get curious about the possibilities. How could AI…
help you with the work you do most often?
help with the tasks you find most frustrating? Most time-wasting? Most abhorrent?
help you get started on things you tend to procrastinate?
help make something complex simple?
Make the time to talk about these questions as a team. Encourage experimentation and even more so the sharing of learnings and ideas.
To make that curiosity sustainable, pair it with simple AI governance: clear guardrails for what data can (and can’t) be used in AI tools, when human review is required, and who is accountable for accuracy, privacy, and unintended bias. The goal isn’t to slow experimentation. It is to create shared norms that protect donor trust and community dignity, so teams can adopt AI with confidence.
Taking adoption from individuals to a team takes leadership
Today, strong teams are embracing this type of curiosity. The best are elevating it from the domain of individuals and individual teams into leadership-led, whole-organization ventures. Curiosity as strategy, business model, and culture.
First, they’re using what they learn from bottom-up adoption to create a holistic strategy. That starts with leadership orienting around the organization’s north star for impact and ensuring clarity on the next leap to make. They talk about what’s standing in the way of that leap—from a mission and operational perspective—and what it will take to close it. They talk about what they’re solving for and why and how. Only then does AI come into the mix as a resource for solving those strategic priorities.
Then, they’re developing the technology. That doesn’t mean purchasing a bunch of software. It primarily means using existing tools in new ways and then making measured investments where needed. The biggest successes have come where data and processes are shared and integrated across teams.
AI adoption goes beyond any single form of AI. Today, AI is a blend of predictive (the original), generative (the GPTs we are most familiar with) and agentic (emerging recently). Each plays a different and specific role in helping to automate processes, elevate opportunities, and simplify impact.
While that level of AI integration requires technical expertise, the imagination and implementation is the responsibility of everyone on the team. AI becomes a collaborative, iterative learning process—rather than an IT initiative. Done well, integrating AI into fundraising is simplifying the back-end to allow fundraisers more time for the actual, well, fundraising.
The opportunity is creating the capacity we’ve dreamed of
No fundraising leader I’ve ever met has said: “We have too many staff. We’re all relaxed and have all the resources we need.” For as long as I’ve been in this field, we’ve been saying: “Imagine what we could do if we had more capacity.”
Well, here’s our chance to find it.
This is not a moment to be stressing about AI replacing our jobs. Operating from a place of scarcity and fear has never moved us forward. Now is the time to ask: What if? What could our amazing changemakers do, be, learn, create, and solve with more time to spend with each other, with community, with donors, with partners?
To be sure, how we work is changing—and quickly. Some roles and tasks will become obsolete. At the same time, new ones will be created. If we seize this moment with clarity and courage, more of our roles can become more people facing—internally or externally. More of our time can be spend moving forward versus catching up. And more of our energy can be invested in acting on ideas versus developing them.
Collectively, the most powerful shift we can make is to release the (valid!) feeling that AI is a phenomenon happening to us and begin shaping what it will mean to our communities, organizations, and hopes for the world.