Put Some Windex (AI) On It!
AI will be particularly tempting for nonprofit development professionals
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Philip
One of my impressions from attending a couple of nonprofit technology conferences last week is there are a lot of people and companies focused on encouraging individual donations to nonprofits. Each year, Americans donate $326 billion to philanthropic causes, which helps explain why there is so much interest in this space. Collecting this enormous amount of money involves solving many hard problems that come with trying to elicit charity from hundreds of millions of quirky individuals.
Some donors receive information from a newspaper collected from the driveway each morning, while others prefer Tweets or TikToks. There are folks who like high-touch appeals, and people who insist on a hands-off approach. From checkbooks to crypto wallets, the proliferation of payment methods adds yet another dimension of complexity to the challenge of stewarding individual philanthropy.
Even with all the lovely tools in those exhibit halls designed to make the process easier, it’s still painstaking work. Pain seeks relief, and from my viewpoint, it’s easy to see how someone might be tempted to treat generative AI technology like Windex in the movie, My Big Fat Greek Wedding.
How do I keep track of interactions with hundreds of different donors? Put some AI on it!
It’s so annoying to customize all these donor appeals. Put some AI on it!
We’re not getting enough engagement with our email newsletter. Put some AI on it!
Like with Windex, it’s really important to understand what a tool is good for, and when a little placebo can be helpful versus harmful. Large language models (LLMs), like GPT, are extremely good pattern recognizers and replicators, which have been trained on enormous amounts of content created by human beings. They’re mathematically mapping the landscape of meaning, quantifying concepts with numbers in ways that unlock incredible new possibilities.
So how should we apply these capabilities effectively? Here are some ideas for how nonprofit development professionals can use LLMs to improve their work.
Ask AI for insights from large datasets - For example, analyzing sentiment across years worth of donor appeals and responses and asking for suggestions on how to improve
Role play with AI - Ask a chatbot to assume different donor personas and test material with it to learn how you might optimize before engaging with the real thing
Brainstorm content variations - Give an AI a tired template and ask for ways to refresh it for new situations
In these scenarios, AI is acting like a helpful team member running analysis and sharpening ideas. Each of these situations should give the human more actionable information and leave them with important decisions to make.
The pain relief should come from removing obstacles that prevent people from accessing their highest value skills such as creativity, strategic thinking, and distilling insights from nuance.
Now let’s look at how AI might be applied in ways that feel good, but could mask or exacerbate real problems.
Using AI to “personalize” mass emails - A chatbot can easily be used to connect donor data points in messages with the appearance of personalization
Increasing communications frequency with AI - AI can instantly amplify a team’s ability to send out more messages across all of its channels
Implementing a rapid brand overhaul with AI - Generative AI tools can quickly create new versions of most public facing organizational assets
These scenarios differ in that AI has the effect of partially or completely circumventing the same high-value human skills the previous cases enable. Instead of bringing the team to deeper insights or higher-level vantage points to enable better decision making, AI can further obscure root issues in the process of instantly eliminating annoying tasks.
In the last example about freshening up an organization’s brand, the speed and ease with which this can now be accomplished is, itself, a factor that can cause problems. Previously, when rebranding was an expensive and more time-intensive process, more people had the chance to get involved in slower, more deliberate work to make sure the end result is right. More speed can often mean less opportunity for oversight and input to create more depth in a brand.
That said, sometimes, using AI to polish up a few annual donor documents to be a little more thoughtful and effective can be just what an organization needs. Thinking back to my days as a flustered nonprofit executive director trying my best to hold thing together, I would definitely have made use of certain AI assets.
The important thing to remember is AI, like all tools, will require time, patience, and practice to master. A heuristic to reflect upon could be to periodically ask yourself if using AI is leaving you with a “that was too easy…” type of feeling, or a sense of genuine satisfaction.
If it’s the former, take another look at what you’re doing to see if you’re using your AI Windex as it should be, to gain more clarity, or if you might just be making yourself feel better for the time being.
Thanks for reading this edition of The Process. Please share and comment or you can email me at philip.deng@grantable.co
Philip Deng is the CEO of Grantable, a company building AI-powered grant writing software to empower mission-driven organizations to access grant funding they deserve.
I love these insights. Thanks for sharing!