From Floppy Disks to AI: Nonprofits and the Next Digital Evolution
I still remember a time when the internet was a luxury I couldn’t access. As a teenager in a low-income community, my “information highway” was the local library. I’d trek there after school, flipping through AOL chat rooms and looking for the coolest stuff. My first “data storage” wasn’t the cloud—it was a stack of floppy disks with a whopping 1.44 MB capacity each (barely enough for a few documents). In those days, personalization meant the librarian knew my name, and “high-speed connection” was riding my bike home before dark. When we finally got dial-up internet in our home, it felt like a door to the world had opened. Suddenly, I wasn’t limited to encyclopedias; I could ask Jeeves (yes, that was a thing) or AltaVista anything and maybe find an answer. Fast forward: I went from hand-writing fundraising letters and keeping donor info in a rolodex, to managing email campaigns and donor databases online. I went from a childhood without a home computer to adulthood with a smartphone in my pocket more powerful than the NASA computers that sent astronauts to the moon. Each step—floppy disks to CDs to USB drives to cloud; library catalogs to Google; landlines to Zoom—has been a leap in what technology allowed me to do. And now, here we are in 2025, standing on the cusp of yet another transformational leap: artificial intelligence.
The feeling is familiar: a mix of excitement, curiosity, and a hint of fear. I felt it when I first heard the haunting screech of a 56k modem connecting to the web, and I feel it now with AI chatbots crafting paragraphs at my command. Just as the internet revolutionized how I communicated and found information, AI promises to revolutionize how we process information and make decisions. The magnitude of this shift is hard to overstate—it’s as if we’re at “digital round two,” and this time the change could be even more profound. As one technology veteran put it, the current wave of AI is “unlike anything I’ve experienced… not just another wave of innovation, it’s a fundamental rethinking of how we work, connect, and create impact… faster, more disruptive, and impossible to ignore”. In other words, AI is not just a new tool; it’s a whole new era.
The Next Evolution: AI as Transformative as the Internet
If you lead or work in a nonprofit, you might be feeling a bit of déjà vu. Think back to the late 1990s and early 2000s: some nonprofits jumped on online fundraising and email early, while others held back. The early adopters reaped rewards, reaching donors globally and raising more money, while the latecomers missed out and scrambled to catch up. History has a way of repeating itself. Today, AI is that next inflection point. The choice is similar: will we embrace this technology intentionally, or will we hesitate and risk getting left behind? As an article in RSM’s technology blog noted, “In the late 1990s… some [nonprofits] embraced online donations early… Others hesitated – and paid the price… Today, we find ourselves at a similar inflection point with artificial intelligence”. In fact, experts argue that the stakes are as high or higher this time – “just as the internet redefined how nonprofits connect with supporters, AI is redefining how we understand, serve, and scale impact. The stakes are just as high—if not higher.”.
Why “higher”? Because AI can potentially touch every aspect of an organization’s work, internal and external. It’s not one tool, it’s an amplifier of many tools. And it’s fast. We’re not talking about a slow shift from postal mail to email over a decade; AI adoption is happening at lightning speed. In mere months after tools like ChatGPT became widely available, millions began experimenting with them. I’ve seen small nonprofits use AI for tasks that would have required an entire team (or expensive contractor) a few years ago. It’s breathtaking – and a little daunting. Even for a tech enthusiast like me, the pace of AI’s evolution has been shocking. But if there’s one thing my floppy-disk-to-smartphone journey taught me, it’s that the organizations that adapt and learn new tools will thrive, while those that cling to “the way we’ve always done it” risk fading into irrelevance.
Nonprofits at a Breaking Point: Burnout and the Pressure to Do More With Less
Overwhelmed nonprofit professional reflecting the burnout and stress of doing more with less.
Let’s pause for a moment and acknowledge the reality many nonprofit professionals are living in 2025. It’s tough. In the wake of a global pandemic, economic uncertainty, and social upheavals, nonprofits face soaring demand for services – but often with shrinking teams and budgets. Burnout isn’t just a buzzword; it’s an epidemic in our sector. A recent survey found that 95% of nonprofit leaders are concerned about staff burnout, and half of those leaders feel even more burned out themselves than a year prior. Nearly every nonprofit I talk to is trying to “do more with less.” More programs, more need, but less funding, fewer staff, and zero breathing room. One nonprofit CEO described the current reality as unlike anything in her 20-year career: “It seems everything changed after COVID… There are no trailblazers that have faced this path before us… It is a wild world right now”.
Sound familiar? Maybe you’re nodding as you read this. Many of us are scrambling – covering vacant positions we can’t fill, juggling multiple roles, fighting fires every day. We care deeply about our missions, so we work long hours for less pay than our corporate counterparts, and we do it gladly – but it takes a toll. Staff turnover and vacancy rates are high across the sector, which only adds to the load on those who remain. It’s a vicious cycle: overworked staff leave, making others even more overworked. As one report noted, three-quarters of nonprofits struggled with hiring in 2023, and this trend continued into 2024 alongside the burnout crisis. The bottom line is that the nonprofit sector is stretched to its limits.
This is the landscape into which AI arrives – not as a shiny new toy, but as a potential lifeline. When you’re drowning in work, anything that promises to save time and effort sounds appealing. But nonprofit folks are also rightly skeptical; we’ve seen silver-bullet solutions come and go. Money is tight, and we can’t afford to chase every new tech fad. So if we’re going to embrace AI, it has to be intentional and tied to real pain points: fundraising shortfalls, communication overload, staff capacity, and burnout. The good news is, when used wisely, AI can directly address some of these challenges. It won’t fix broken funding models or make self-care optional, but it can automate the drudgery, surface actionable insights, and even help us personalize outreach in ways previously impossible. In short, AI can help nonprofits finally do more with less – not by squeezing staff harder (we’re already maxed out), but by working smarter.
AI for Fundraising and Donor Personalization at Scale
One area where AI for nonprofits is already making a mark is fundraising – particularly in how we understand and engage donors. Nonprofits have always known that personalization is key to donor communication: the more you can tailor an appeal or a thank-you to a donor’s interests and history, the more it resonates. But let’s be honest: true personalization at scale has been out of reach for most organizations. If you have five development officers and 50,000 donors, you’re not going to have deeply customized touchpoints for each person – you’d be happy just segmenting by a few broad categories. Thus, many donors get generic newsletters and one-size-fits-all appeals. As one philanthropy expert observed, most nonprofits resort to mass updates and general appeals that are not customized, because matching each donor’s unique preferences would take extensive time and staff that simply “the vast majority of nonprofits do not have”.
This is where AI can be transformational. Think of generative AI as an intern who can draft 20 versions of an email tailored to 20 different donor profiles in seconds – and never gets tired. It’s not coming up with strategy (that’s still on us humans), but it can execute tactics unbelievably fast. For example, imagine feeding an AI tool your donor data: it might spot that Donor A cares about environmental impact and opens emails about climate, while Donor B always clicks on stories about education. With the right setup, an AI could draft a version of your fall fundraising letter for Donor A that leads with your climate projects, and another version for Donor B that highlights your education work – all in the time it takes you to refill your coffee. In fact, AI has “the power to reshape nonprofit engagement, allowing each donor journey to feel more personal and impactful”, essentially intertwining individual donor stories and preferences into outreach at scale. Every interaction can start to feel bespoke, helping donors feel like an essential part of the mission – and when donors feel that way, they tend to give more and stay longer.
We’re not in science fiction; these capabilities exist today. Customer relationship management (CRM) systems like Salesforce or HubSpot can already integrate with AI to recommend next steps for donor engagement. One simple (yet game-changing) application is using an AI assistant to analyze donation records and suggest the best “ask” for each donor. Perhaps Donor C always gives in December and loves your scholarship fund – an AI might flag to send them a targeted story about a student in November with a gentle ask to renew support. Or consider AI-driven prospect research: instead of manually sifting through wealth screening data, an AI could scan public info to predict who in your email list might have high affinity and capacity, giving your development team a prioritized call list.
Even small nonprofits can benefit; you don’t need a PhD data scientist on staff. As one expert noted, generative AI – like large language models (think ChatGPT or Google’s Gemini) – can sit on top of your existing data and tools to automate a lot of this analysis and recommendation work. For instance, with a bit of glue (through tools like Zapier or Make), your CRM could trigger an AI whenever new donor notes are added, and that AI could compose a tailored follow-up action suggestion. One imagined scenario describes exactly that: a CRM note updates, an AI cross-references it with a curated list of engagement options, and presto! – it writes a recommendation into the CRM, like “Invite this donor to the upcoming local volunteer event” because it noticed they care about community engagement. This was the stuff of development team daydreams a decade ago. Now it’s real and (relatively) affordable.
Beyond solicitation, AI helps with donor retention too. Nonprofits lose donors often because communications become stale or irrelevant. AI can analyze tons of donor interactions (emails opened, event attendance, donation patterns) to find signs of waning interest and suggest interventions. Maybe donor D hasn’t opened the last 5 emails – the AI could flag that and even draft a special “We miss you – can we do better?” message. Or, if a long-time donor suddenly drops their gift amount, AI might spot language in their communications indicating a life change, prompting a personal outreach from a staff member. The key is augmenting our human insight with machine speed. One consultant put it well: AI can “make more strategic use of limited resources” by doing in moments what would take humans weeks, crunching data to find the patterns we can act on.
The results? Potentially, more donations and stronger donor relationships. Early signs are promising. Some organizations using AI for donor targeting have seen significant bumps in revenue. For example, the American Cancer Society used machine learning to optimize digital ads, and they saw donation revenue come in at 117% above benchmark – yes, 117% above normal – with a donor engagement rate of nearly 70%. That’s what happens when you reach the right people with the right message. AI doesn’t replace the need for creative fundraising strategy or genuine relationship-building, but it supercharges our ability to execute those personalized strategies at scale. As Ashutosh Nandeshwar (a data science expert in fundraising) said, “Especially with generative AI, not only can it be a lever for becoming more efficient, but [nonprofits] can also free up time to do the things they do best, which is being donor-centric… AI can help elevate philanthropic outcomes and, ultimately, better mission fulfillment.”. In other words, let the AI do the busywork, so humans can do the human work – connecting with donors, telling stories, stewarding relationships.
It’s worth noting that donors themselves have mixed feelings about AI. Some love the hyper-personalization; others worry about privacy or the “creepiness” factor if it’s done clumsily. (Pro tip: just because AI can draft a completely personalized 1-to-1 message to every donor doesn’t mean you should pretend a human wrote each one individually. Be transparent if appropriate, e.g., “This thank-you was assisted by AI to share more impact stories with you.” Authenticity and ethics matter.) But by and large, a personalized approach, however achieved, is welcomed by donors over generic blasts. The key is to use AI to deepen the donor’s connection to your cause, not to spam them. Done right, AI-assisted personalization can make donors feel truly seen and valued by your organization, which is the foundation of loyalty.
AI in Communications and Internal Productivity
Fundraising is only one slice of the nonprofit pie. What about all the other work we do? Reports, grants, emails, social media, staff meetings, board presentations, program delivery… the list goes on. Here’s where I get really enthusiastic: AI tools for nonprofits aren’t just about raising money; they can relieve a lot of the daily grind that leads to staff burnout. Remember that feeling when you discovered some new software that saved you hours of work (like the first time you used MailMerge or an Excel formula)? AI is like MailMerge on steroids. It’s an assistant who can do first drafts of almost anything textual, plus analyze and summarize information faster than any intern.
Content creation is a huge time sink in most nonprofits. Writing newsletter articles, blog posts, social media updates, press releases, grant proposals, annual reports – we often do all this with small communications teams (or just one worn-out comms manager who also does five other jobs). Generative AI is a boon here. Tools like ChatGPT (and its many emerging competitors) can produce remarkably decent drafts of content in seconds. You can say, “Draft a 300-word blog post about our food pantry’s impact, including a call-to-action to donate,” and boom – you have a starting point. No more staring at a blank page. Need it in Spanish, or French? It can translate on the fly, helping you engage non-English-speaking supporters without hiring a translator. Of course, you will edit and fact-check that draft (AI can confidently spew incorrect info, so human oversight is a must). But even if the AI draft is 60% usable, that’s hours saved. And it often might be 80-90% there, especially for straightforward communications. According to a 2024 survey, nonprofit staff found generative AI useful for tasks like taking meeting notes, writing job descriptions, drafting social media posts, and more. These are precisely the kind of lower-level tasks that eat up a lot of time but don’t necessarily require our full human creativity. Why not let the machine carry some of that load?
Let’s talk meetings for a moment (everyone’s favorite topic, right?). Nonprofits spend a lot of time in meetings – with staff, volunteers, partners, funders. How much of that discussion is lost or laboriously written up later? AI can help here too. There are AI-powered meeting assistants (e.g., Fathom, Otter.ai, and even features baked into Zoom now) that will record, transcribe, and even summarize your meetings. Instead of someone spending 2 hours writing minutes, an AI can churn out a decent summary in seconds, highlighting key decisions and action items. You or your colleague just skim it to ensure accuracy and voila – meeting minutes done, and done consistently every time. This not only saves time, it helps retain organizational knowledge (great when staff turn over). A leader at Bridgespan noted that tools which transcribe and compile notes can free hours of staff time, and if the notes are imperfect, that’s fine because “I consider these ‘first drafts’” that I didn’t have to do myself. It’s a perfect example of using AI for efficiency: it might not be perfect, but it’s perfectly useful.
Email management is another headache AI can alleviate. Some email clients are integrating AI to prioritize emails or draft replies. If you get 100 emails a day (not uncommon in nonprofits where everyone wears multiple hats), even saving a minute on half of them adds up. AI might highlight, for instance, that 10 of those emails are likely donation receipts or low-priority newsletters you can skim later, while another 5 contain questions that it can draft answers for (based on your past communications) for you to approve and send. It’s like having a personal assistant triaging your inbox.
And oh, grant writing – how many late nights have nonprofit folks spent piecing together grant narratives? Generative AI is like a co-pilot for grant writing now. Feed it your past proposals and some bullet points, and it can produce a solid first draft of the next grant application. There are even nonprofit-specific AI services (e.g., Grantable, GrantBoost) popping up to assist with this. They won’t submit the grant for you, but they handle the drudge work of aligning your standard text to a funder’s questions or word counts. Again, you save time and can redirect your energy to higher-level strategy – or frankly, give your overworked brain a breather.
Crucially, all these productivity gains help address the burnout issue. If your tiny team can accomplish what a team twice your size used to (because AI is automating the repetitive parts), maybe people won’t have to regularly work 60-hour weeks. Maybe that development director can actually take a vacation without their email blowing up. That’s the hope. In the social sector, “efficiency” isn’t just about saving money – it’s about saving our sanity and retaining talent. The Bridgespan Group highlighted that nonprofits are starting to view AI as “a tool for efficiency, a potential mitigator of staff burnout, [and] a lever for delivering impact at greater scale”. The idea is to leverage technology not just to save time, but to make our work lives saner and more sustainable, so we can keep doing the important work we do for communities.
Before I sound too Pollyanna, let me emphasize: AI is not a magic wand. It requires an upfront investment of time to set up, learn, and integrate into your workflow. You might need to clean up your data (garbage in, garbage out, as the saying goes) or rethink some processes. But consider the alternative: not adopting helpful tech because it’s new or intimidating, and continuing to grind your team down with manual workloads. As Bridgespan noted, nonprofits that hesitate on tech adoption risk being outpaced by those that dive in, and the gap between the “digitally savvy” orgs and the rest could determine which nonprofits survive and which missions struggle. We’re already seeing funders and donors gravitate toward organizations that demonstrate innovation and efficiency. Donors want their contributions to have maximum impact; if AI helps you do $1.10 of work for every $1, while another org is only getting $0.70 out of that $1 due to inefficiency, it doesn’t take an MBA to see which org will earn donor confidence. In short, using AI smartly isn’t just a tech upgrade – it’s becoming a marker of organizational effectiveness.
Overcoming AI Skepticism: From Gimmicks to Game-Changers
Despite all these glowing possibilities, I know many folks (especially in creative fields like communications, design, or even program arts) are skeptical or fearful of AI. Let’s address the elephant in the room: Is AI a threat to our jobs? Is it going to dumb down our carefully crafted storytelling, or produce cookie-cutter content, or even worse, steal from human creators? These are valid concerns, and as nonprofit leaders we can’t afford to be naive about them.
First off, there’s a lot of AI hype and gimmickry out there. It seems like every software product now advertises “AI-powered” something. Some of it is genuinely useful; some is just buzzwords slapped on. You’ve probably seen fun (or creepy) demos of AI that can generate an image of a cat riding a unicorn, or write a cheesy poem. Impressive, sure, but not exactly relevant to writing your annual report or meeting with a major donor. The key is distinguishing gimmicks from game-changers. A gimmicky AI tool might, say, automatically add hats to everyone in your Zoom meeting for fun. A game-changer AI will integrate deeply into your processes – like helping analyze large datasets, or generating personalized communications at scale. Foundational AI platforms like OpenAI’s ChatGPT or Google’s Gemini (and others like Anthropic’s Claude, Microsoft’s Copilot, etc.) are powerful engines. Many smaller tools you’ll encounter are basically these engines repackaged for a niche (for example, an “AI fundraising email writer” might just be using OpenAI’s GPT model under the hood). That’s not necessarily bad – a niche tool can have a friendly interface for a specific task – but be aware of what you’re using. Don’t be wowed by a fancy UI if behind the scenes it’s the same AI you could access more directly. Conversely, don’t dismiss AI just because some implementations are silly or overhyped. AI itself isn’t a fad; it’s a fundamental technology, but applications of it can be hit-or-miss.
Now, about the fears among artists and content creators – a group I’d include nonprofit communicators in, since we literally create content for a living (stories, graphics, videos, etc.). There’s a worry that AI will flood the world with generic content, drown out authentic voices, and even plagiarize human creatives. We’ve all seen the headlines about artists suing AI companies for scraping their artwork, or writers concerned that AI-generated text will devalue original writing. These concerns aren’t unfounded. In fact, surveys show that over half of artists (54.6%) fear AI’s impact could decrease their income, and nearly three-quarters of artists want consent before their work is used to train any AI algorithm. As nonprofit leaders, many of us stand with our creative colleagues in calling for ethical practices – AI should not be an excuse to rip off someone’s copyrighted work or to replace human creativity wholesale.
However, I’d argue that in the nonprofit context, AI is more of an opportunity than a threat when handled correctly. Think of all the content we don’t have time to create. Is having an AI draft a first version of a volunteer handbook or a press release stealing a job from someone? Not really – it’s doing work that probably wouldn’t get done otherwise (or would pull someone away from another critical task). And for the truly creative stuff – that heartfelt video script, that powerful op-ed – AI is a tool, not a substitute for your unique voice. If you treat AI output as the final product, yes, you’ll end up with bland, one-size-fits-all content. But if you treat it as the starting point, you can actually spend more time finessing the human elements because the rough draft came easy. One content creator described it well: AI is a hammer. Anyone can use it to hit a nail; a skilled craftsperson can build something beautiful with it. In our case, maybe AI is more like a bulldozer – incredibly powerful, able to move mountains of data or content, but you need to steer it with skill and caution. Give a bulldozer to someone who’s never driven one, and they could wreck the house. But with a trained operator, that bulldozer can build a solid foundation faster than a hundred people with shovels.
So how do we “train” to use the AI bulldozer? It comes down to iteration, prompting, and creativity. Unlike a simple tool (hammer hits nail), AI might not do exactly what you want on the first try. You have to guide it. This is the art of prompting: you might start with “Give me a two-paragraph summary of this 10-page report,” and if the summary misses the nuance, you tweak your prompt: “Now add a bullet list of the three key findings with one supporting statistic each.” You can have a back-and-forth with AI, refining the output. In a way, it forces you to be clearer about what you really need – which is a healthy exercise. And don’t forget to infuse your creativity and judgment. AI can produce 5 variations of a social media post; you choose the one that best fits your organization’s voice (or tweak a bit to add that human touch or timely reference only you would know). The process is iterative: prompt, get output, review, adjust prompt or edit output, and repeat as needed. When you see AI as a collaborator rather than a threat, you start to realize it expands your creative capacity. It handles the mundane 80% so you can elevate the remaining 20% to something great.
Another fear I hear is, “What if AI makes a mistake and we spread misinformation or offend someone?” That’s a valid caution. The solution is human oversight. AI is powerful, but it’s not magically infallible or morally wise. Think of it as a very clever, very fast intern – it still needs supervision. You wouldn’t let an intern send out an important press release without someone senior reviewing it. Same with AI. Use it to draft, but have staff review anything high-stakes. Use it to analyze data, but sanity-check the insights before acting. With those guardrails, you can avoid most pitfalls (and learn from the mistakes that do slip through – because they will, and that’s okay if we catch them and adapt).
Integrating AI: Put Your Tech Investments to Work
Finally, let’s address a practical matter: many of us have already invested in various tech platforms – CRM systems like Salesforce or HubSpot for donors, communication tools like Zoom for virtual events, maybe even specialized software like Gong or Fathom for recording and analyzing donor calls or meetings. These tools are not cheap. But are we fully leveraging them, especially their AI capabilities? Buying software and using it superficially is like money sitting idle in a low-interest account. Integrating AI is how you put that money to work for you.
For instance, if you use Salesforce, are you using its Einstein AI features that can predict donor giving or suggest email send times? If you use HubSpot, have you tried the content assistant that can draft marketing emails or blogs (a feature they’ve integrated using OpenAI)? On Zoom, they’ve introduced AI-generated meeting summaries – next time you have a board meeting, imagine getting an automatic recap to share with those who missed it, without anyone having to spend an extra hour writing it. Tools like Gong (popular in sales but also used in nonprofit major donor work) can analyze your donor conversations and highlight what phrases correlated with donations, or where the donor showed interest or concern – that’s AI under the hood doing conversational analysis. And Fathom can transcribe and tag all your Zoom calls, syncing notes to your CRM. But all these shiny features only help if you turn them on and incorporate them into your workflow.
It might take a bit of effort to connect systems – for example, to have Fathom’s transcript summaries automatically attach to a contact record in Salesforce, you might need a Zapier integration or some API work. This is the “iteration” part in a systems sense: try something, see if it saves time or improves outcomes, tweak, repeat. The payoff is huge. When your systems talk to each other and AI is in the loop, you get something akin to an “AI colleague” who moves fluidly across your organization’s data. Picture this: After a donor meeting (recorded on Zoom), you have an AI-generated summary in your inbox before you even finish your coffee. You skim it, add a couple of personal notes, and with one click sync it to your CRM. The CRM’s AI then reads that note and updates the donor’s interest profile (they mentioned they love your education programs). Next week, when you’re planning your donor newsletter, your email tool suggests a personalized blurb about an education initiative for that donor, courtesy of AI cross-referencing everything. This kind of orchestration is no longer fantasy – it’s doable now, with the tech many organizations already have or could access affordably.
Think of all this like hiring a team of robot interns that operate within your existing software. You’ve already paid for the software (or will pay the subscription regardless). Not using the AI features is like leaving half the tools in the toolbox unused. Every HubSpot, Salesforce, Zoom, Office 365, Slack, etc. is racing to add AI features because they know it increases the value of their product. Take advantage of that! It’s akin to having a financial investment and not collecting the dividends. Those AI dividends come in the form of hours saved or insights gained.
Of course, integration should be done thoughtfully. Don’t integrate for integration’s sake. Identify where a manual handoff between tools is costing you time or data quality. Then see if AI can bridge it. Maybe your volunteer signup form (on something like Google Forms) dumps info that a staffer manually copies into a spreadsheet and emails to the team weekly. Could an AI script or automation do that instantly and even highlight which new volunteers might be good donor prospects based on their answers? Probably, yes. It might be worth consulting a tech volunteer or partner for a day to map these opportunities. Many companies (and increasingly, tech-savvy foundations) are willing to help nonprofits implement these kinds of efficiencies as pro-bono projects, because it showcases what their tech can do in a mission-driven context.
The main point here is: don’t let your tech stack’s potential sit idle. You’ve invested in these tools – now supercharge them with AI capabilities. It’s like you own a hybrid car; why not put fuel and electricity in it to get the best mileage? When you weave AI throughout your organization’s systems, you create a compound effect. The fundraising team saves time, the programs team gains insight, the comms team produces more content, and leadership gets better data to drive strategy. All from the same staff, same budget – just working smarter. That’s the promise of AI in the nonprofit tech stack: efficiency and effectiveness across the board.
Embrace AI as a Lifeline, Not a Threat
Nonprofit friends, we are in an overwhelmed landscape. The needs are growing, the resources are not. Our teams are running on empty, yet our missions have never been more critical. AI is not a threat; it’s a lifeline. It’s a chance to lighten the load, to give us a bit of breathing room to focus on the human parts of our work that AI can never replace – the empathy, the relationship-building, the creative strategy, the moral leadership. All the administrative, analytical, number-crunchy stuff? I’m more than happy to let the machines handle more of that, under our guidance.
Yes, adopting AI requires change. There will be a learning curve, and bumps along the way. We must navigate ethical dilemmas (privacy, bias, transparency) and set policies for responsible use. But doing nothing is not an option we can afford. Already, we see some nonprofits accelerating ahead: deploying AI chatbots to answer common supporter questions, using machine learning to identify which communities could benefit most from their programs, leveraging GPT-4 or Gemini to auto-generate first drafts of their annual reports. These organizations aren’t doing AI for AI’s sake – they’re doing it because it helps them deliver more impact with the same or fewer resources. Meanwhile, nonprofits that shy away from these tools may find themselves falling behind in fundraising, in stakeholder engagement, and in operational capacity. The gap could become existential; as one report warned, the divide between tech-embracing nonprofits and those that lag could “shape which organizations survive and which communities are served” in the years ahead.
I began this piece reminiscing about life before the internet to make a point: those of us who’ve been around a while have witnessed huge technological shifts, and we (mostly) adapted and benefited. AI is the next chapter in that story. It’s natural to feel uneasy – just like I did hearing that first modem dial-up tone – but imagine telling your younger self all the things the internet would empower you to do for your cause. That’s the kind of promise AI holds now. It won’t solve all our problems, but it can give us a fighting chance against some of the toughest challenges – donor disengagement, staff burnout, inefficiency, information overload.
So, my call to action for nonprofit professionals is this: approach AI with curiosity and courage. Experiment in small ways (try a free AI writing tool for a routine task, see what it can do). Educate your team and board about the potential – and the risks – so you can craft a thoughtful strategy. Share successes and failures with each other; as a community, we’re all learning. Most importantly, keep the focus on people. AI is a means to an end. The end is a more just, compassionate, and sustainable world, powered by organizations that are resilient and equipped to do their best work. We owe it to our missions and our colleagues to use every tool we can to make that happen.
In a world that demands we do more with less, AI is the leverage that can make the impossible feel a little more possible. It’s not coming for our humanity – it’s here to amplify our humanity by freeing us to do the uniquely human work that machines can’t. Embrace this new era, iterate and improve, and let AI carry some of the weight. The future of our organizations, and the communities we serve, will be better for it.
Keywords: AI for nonprofits, AI nonprofit fundraising, AI nonprofit tools, how nonprofits use AI, GPT for nonprofits, nonprofit donor personalization with AI. (In embracing AI, nonprofits can unlock new levels of fundraising personalization, operational efficiency, and mission impact.)
Sources: Nonprofit and tech experts on AI’s potential and the state of the sector were referenced in crafting this article. Key insights were drawn from sector research and thought leaders, including reports on nonprofit burnout, analyses of AI-driven personalization in philanthropy, and expert commentary on how AI parallels past tech revolutions and can redefine nonprofit work. Practical examples of AI in action for fundraising and operations were highlighted from industry case studies. These sources reinforce the message that AI, used wisely, is a transformative tool for the nonprofit sector – one that can help organizations rise to the challenges of today and tomorrow.
Sources
fidelitycharitable.orgfidelitycharitable.org
