Tag Archives: AI

The A.I. Tug of War in Fundraising—And How to Find Your Footing

Careers, Fundraising Analytics, Major Gift Teams, Profiles, Prospect Identification, Prospect Management, Research in Fundraising, , , , , , , , ,

Let me ask you something: How many times has a piece of technology promised to change everything… and then promptly driven you absolutely crazy?

You know the scenarios. It can do all the things, but only after you’ve configured everything yourself. “Integration” turned out to mean something very different from what you imagined. The upgrade wiped out every custom setting you spent hours building. And whenever you try to do something just slightly outside the norm, the software fights you like a toddler at bedtime.

I could go on. We have all been there.

And yet—here’s the tension—technology genuinely has made our lives easier. Microsoft Word may not make complex formatting a walk in the park, but it has transformed how we create documents. And because it plays nicely with the rest of the MS Office suite, whole categories of headaches have simply disappeared.

Welcome to the tug of war.

The Two Ends of the Rope

When it comes to A.I. in fundraising, this same push and pull is playing out in real time. On one end of the rope are the people who believe A.I. is too messy, too risky, and too unreliable to touch. On the other end are the people who believe A.I. has ushered in such a leap in accuracy that we can use machine-generated information as-is, no human review required.

New technologies that arrive with enormous hype—and A.I. certainly arrived with enormous hype—have a way of polarizing us. But is there something useful to be found in the middle of that rope?

Spoiler alert: There is.

Yes, A.I. Has Been Around. But This Feels Different.

A.I. has been woven into our digital experience for years. Recommendation engines. Spam filters. Autocomplete. But when OpenAI released ChatGPT in 2022, it felt less like a product launch and more like a digital eruption. Things are moving fast. New and genuinely exciting capabilities are emerging. And yes, things are getting broken along the way.

For many in our field, the speed of that change feels dangerous. Whatever you do, don’t ask A.I.

But much like the anxiety that greeted Google’s debut—remember when people worried that nobody would learn anything anymore?—there is real and practical value here, if you know how to use it.

One of the most useful features of a generative A.I. chatbot is that you can ask it to show its work. Where did that information come from? What sources support that conclusion? What transactions were used to build that summary? That transparency is actually a significant feature, not a quirk.

Where A.I. Is Changing the Game for Prospect Research

At Aspire Research Group, one of the most dramatic shifts A.I. has made in our day-to-day work is in writing bios. Even setting aside the time required to gather information, writing a few well-crafted paragraphs about a prospect has always been time-intensive. Using DonorAtlas, we now have well-written bios and the underlying sources for verification—almost instantly. We can deliver a significantly stronger product at the low end, in far less time.

Until, of course, A.I. fails us. And it does fail us.

People in the arts, for example, seem to get misrepresented by A.I. with striking frequency. What is their “job,” exactly? They don’t fit the pattern that it expects. In those cases, we take over the steering wheel and drive that one ourselves.

This is not a reason to abandon A.I. It’s a reason to understand it.

Algorithms Are Only as Good as the Data Behind Them

Remember when Netflix’s recommendations felt almost eerily accurate—until they didn’t? If you shared an account with someone whose taste was wildly different from yours, the algorithm got confused. It was doing its best with messy inputs.

The same principle applies to your fundraising database. If your data is a hot mess, A.I. is going to struggle to give you reliable scores or meaningful analysis. But here’s the thing: it might still give you better results than statistical modeling did. And if better-than-before scores get gift officers out the door and into conversations with donors faster, that’s not nothing. Something is better than nothing.

But that raises the next question—and it’s an important one.

If A.I. Is Better Than What Came Before, Why Not Just Trust It?

If A.I. analysis outperforms statistical modeling, why shouldn’t we lean on it entirely? Why not let it drive portfolio assignments, staffing decisions, campaign planning?

I recently interviewed Vered Siegel on the Prospect Research #ChatBytes podcast, and she said something that I keep coming back to:

“One of the biggest shifts generative AI has introduced in our industry is that information is no longer the scarce resource. Judgment is now the scarce resource. We can generate lists and summaries and signals faster than ever, but that doesn’t automatically make our decisions better. One key aspect of being a strategic partner right now means helping the room slow down just enough to ask the right questions.”

Read that again. Judgment is now the scarce resource.

Finding the Balance

The key to leveraging A.I. well is knowing where human judgment needs to enter the picture—and deciding what level of risk is acceptable for you and your organization.

I’m not suggesting that every single name assigned to a portfolio requires a human review. Not anymore. But what if a feedback loop was built into the prospect assignment process? What if gift officers had a routine way to tell your analytics team when things are working—and when they’re not. That loop is human judgment at scale.

Here’s what breaks down when human judgment is undervalued or eliminated altogether: efficiencies go down. Not up. The risk of an error that could damage donor trust or cause your organization harm goes up. The promise of A.I. is efficiency, but that promise only delivers when the humans in the process are engaged at the right moments.

Get the balance right, and productivity goes up. New opportunities surface. Gift officers work with better information. Researchers spend their energy where it actually matters.

Get it wrong—either by refusing to use A.I. at all or by outsourcing your judgment to it entirely—and you’re just holding a rope with nobody on your end.

This Is Your Moment to Lead

Here’s what I want you to take away from all of this: the disruption that A.I. is causing in our field is real. But it’s also creating space for researchers and prospect management professionals to step into a more strategic role.

A.I. can generate the bio. It can surface the signal. It can produce the list. But it cannot decide which signals matter for your organization’s specific mission and relationships. It cannot make the judgment call about when a score doesn’t pass the smell test. It cannot be the strategic partner in the room who helps leadership slow down and ask the right questions.

Only you can do that.

The question—as always—is whether you’re ready to step up and do it.

Additional Resources

A.I. in Prospect Research: Shifting the Focus from Fear to Strategy

Profiles, Prospect Research, , , , , , ,

Let me paint you a picture of yesterday afternoon.

I’m sitting at my desk with twelve browser tabs open, three different databases logged in, and a lot of messy text I have cut and paste into my growing profile. I’ve spent the last two hours checking the client’s CRM, pumping the prospect’s name through our subscription tools, and power searching with Google and my favorites link list.

Then I start working through the messy text and realize I neglected to search for a key section of the profile. Four hours or so later I have worked through the profile multiple times and added some actionable insights. But I’ve also aged approximately three years and consumed enough caffeine to power a small city.

Sound familiar?

The AI Conversation Everyone’s Having

Everyone in nonprofit research is talking about AI these days. But most of the conversations I hear fall into three camps:

Camp 1: “AI is going to revolutionize everything! We’ll all be obsolete by next Tuesday!”

Camp 2: “AI is completely unethical and none of it can be trusted.”

Camp 3: “AI is overhyped nonsense that will never understand the nuance of our work!”

But here’s what I think we’re missing: The AI revolution is less of a revolution and more like the next steps in the AI trend that has been going on for years.

Instead of succumbing to fear, what if we asked:

  • “How much of my day do I spend on tasks that a really good assistant could handle?”
  • “What would I do with my time if I wasn’t constantly copy-pasting from six different systems?”
  • “What strategic insights am I not noticing because I’m drowning in data gathering?”

The Dream (That’s Closer Than You Think)

Picture this: You get a profile request on Monday morning. Instead of opening twelve tabs and settling in for a marathon copy-paste session, you open one interface that has already pulled together:

  • Everything your CRM knows about this donor
  • Matched information from public databases
  • Recent news and social media mentions
  • Wealth indicators and giving capacity scores
  • Relationship connections to your board, staff, and other donors
  • A summary of their philanthropic interests and giving patterns

…all with source citations so you can verify accuracy and dig deeper where needed.

Now here’s the magic: Instead of spending hours assembling this information, you spend hours analyzing it. Thinking about it. Crafting strategic recommendations.

You’re not asking “How wealthy is this person?” You’re asking “What does their giving pattern tell us about their values?” and “How can we connect their passion for education with our new scholarship program?”

Why This Isn’t Science Fiction

The technology exists. Right now. I’ve been testing some of these tools, and for specific use cases, they’re already game-changing. Public company insider research that used to take hours now takes minutes, with calculations we never had time to do manually. Thank you Kaleidoscope Insider Focus!

The challenge isn’t the technology—it’s that all these amazing tools live in silos and depend on the quality of the information inside those silos. Your wealth screening tool doesn’t talk to your relationship mapping platform. Your donor database doesn’t integrate with the AI that’s scraping LinkedIn and news sources.

But integration problems get solved. That’s what technology does—it gets better, faster, and more connected.

The Skills That Matter Now

So if the information-gathering part of our job is becoming automated, what’s left?

Everything that actually matters:

  • Critical thinking: AI can find information, but can it tell you whether that $2 million gift to another organization suggests strong capacity or donor fatigue?
  • Strategic insight: Tools can map relationships, but can they recommend the perfect board member to make an introduction?
  • Storytelling: Databases can list giving history, but can they craft the narrative that helps your gift officer understand what motivates this donor?
  • Ethical judgment: AI can gather data, but can it navigate the privacy and ethical considerations that come with prospect research?

Your Next Move

The researchers who will thrive in an AI-enhanced world are the ones who start preparing now. Not by panicking about job security or doomsday ethical scenarios, but by:

  • Getting curious about strategy: Start asking better questions about the information you’re already gathering (read this Apra Connections article)
  • Building relationships: Become the trusted advisor your development team runs to for insights, not just data
  • Staying current: Understanding what’s possible with new tools, even if they’re not perfect yet
  • Thinking bigger: What would you tackle if the boring stuff was handled for you?

The Bottom Line

AI won’t replace prospect researchers. But prospect researchers who embrace AI as a powerful assistant will absolutely outperform those who don’t.

The question isn’t whether you’ll have a job in an AI world. It’s whether you’ll be doing the parts of the job that actually matter—the strategic, creative, relationship-building work that transforms donor data into cultivation gold.

And honestly? That sounds like a much better job than the one where I spend half my day copying and pasting between databases.

What do you think—are you ready to let AI handle the busy work so you can focus on the work that actually changes lives?

Ready to Level Up Your Strategic Thinking?

If you’re nodding along thinking “Yes, I want to be the researcher who provides strategic insights, not just data dumps,” then you’re exactly who I built the Research Asset Membership for.

In our workshops, we dig into the real challenges you’re facing: How do you turn research into actionable cultivation strategies? How do you build the relationships that make you a trusted advisor? How do you navigate the ethical complexities of modern prospect research?

Plus, you’ll connect with a community of researchers who get it. People who understand both the frustrations and the incredible satisfaction of this work we do.

Because here’s what I know after years in this field: The researchers who invest in continuously building their strategic skills don’t just survive change—they lead it.

Learn more about Research Asset Membership and join a community of prospect researchers who are shaping the future of our field.

Additional Resources

A.I., Fundraising, and Trust

A.I., Fundraising, and Trust

Focused Fundraising, ,

Is there anything that artificial intelligence (AI) can’t help us do better, faster, and cheaper? Businesses and the fundraising profession have clearly embraced AI as evidenced by the articles, webinars, and courses springing up to teach us all how to use various AI tools. For example, Coursera has a course on using ChatGPT with Excel to clean up your data and Indiana University Lilly Family School of Philanthrop has a course entitled, “AI & Fundraising: Revolutionizing Your Fundraising Efforts.”

Many good things are coming out of AI models, but there is a dark side, too. Inevitably, bias creeps into our algorithms and decision-making processes. Bias can lead to unfair outcomes, damage an organization’s reputation, and even have legal consequences.

Continue reading A.I., Fundraising, and Trust →

Fire your Prospect Researcher! Artificial Intelligence (AI) has arrived.

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For years now we’ve been told that Artificial Intelligence was going to take over prospect research tasks. Truth is, it has. Well, some of them anyway.

Consider wealth screenings. What used to take month after month of tedious, routine, baseline capacity rating work now takes less than an hour. Upload your file, it processes, and presto! You have gift capacity ratings on your prospects based on external wealth matches.

Or how about the user-friendly lookup tools, such as iWave’s PRO, that remove the first step of searching that prospect research professionals used to perform?

Does all of this mean prospect research is on the fast track for complete takeover by the machines? Should you fire your researcher? No way!

Artificial Intelligence has had a lot of hype over the years and very little real action – until now. A few events have led to some breakthroughs:

  • The internet has made vast amounts of data available, which can be used to train computers.
  • Graphical Processing Units (GPUs), the specialized chips used in PCs and video-game consoles to generate graphics, have been applied to the algorithms used in deep learning, a type of Artificial Intelligence.
  • Capacity to run GPUs can be rented from cloud providers such as Amazon and Microsoft, allowing start-ups to innovate.

Self-driving cars may still be on the horizon, but the bots are on the road already! They can schedule appointments on your calendar, draft replies to emails, and even read radiology imaging studies more accurately than a radiologist. The Economist describes the opportunity and threat quite succinctly as follows:

 “What determines vulnerability to automation is not so much whether the work concerned is manual or white-collar, but whether or not it is routine.” (6/25/2016)

 

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It’s easy to leap to the conclusion that prospect research professionals will lose their jobs to the machine – much of what we researchers do is routine – but that would be forgetting how machines have changed the world in the past.

Across the centuries, people have feared the march of the machines. In the late 1700’s to early 1800’s the Industrial Revolution rocked our world. As recently as the 1980’s, the rise of personal computers revolutionized the way we work. And with every introduction, much hand-wringing and predictions of unemployment were had.

How will prospect research professionals likely weather the advancing army of machine algorithms and programs?

Much the same as we adapted to wealth screenings and tools like iWave’s PRO. We learn new skills that wrap around the new technology. We leverage the new technology to work for us and for our fundraising team. We change the tasks we perform.

Prospect research professionals have a unique blend of skills. We can scan mountains of information and pull it together in a way that is meaningful for your specific need, whether that is creating a $5M gift strategy or a $5B campaign. We recognize the opportunities for our organizations in the data patterns the machine discovers.

If you want your organization to keep in step with the advances of machine learning, do NOT fire your researcher! Instead, reassure your prospect research professional of her value and insist that she take advantage of training that will give her the skills to use new technology. If you do this, she will be better able to guide you into new worlds, such as fundraising analytics … and beyond!

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