‘AI in Question, Part 2’: Can Data Replace Experience?
Last week in Part 1, I wrote about how AI can never replace real relationships.
This is because fundraising has always been about building trust, listening, and showing up… all things no algorithm can do.
This week, I want to ask the question, Can data replace experience?
Bytes vs. lived experience
AI has “experience” in the form of trillions of bytes. It can read every direct mail letter you’ve ever written, every email subject line you’ve tested, and every design you’ve approved. It can crunch all of that data and spit out something new in seconds.
But that isn’t the same as experience.
Because AI doesn’t know how something will make someone feel. It can predict open rates, but it can’t sense when a line feels flat or when a mailer is over-designed.
Experience is lived. It’s earned. It’s the scar tissue of failure and the joy of breakthroughs. It’s being a student of human behavior: watching how people respond, listening to what they say and don’t say, and learning from surprises.
That’s the kind of experience AI will never have.
The questions no one’s asking
Which raises a question every organization leaning heavily into AI for their fundraising creative needs to ask:
Who on your team has the experience to know if what AI gives you is actually best practice?
The tool can generate great content, but who’s experienced enough to evaluate it? Who has the scars of failure to say, “This looks polished, but it won’t work”?
Which leads me to an even bigger question no one seems to be asking:
Who on your team has the experience to know if the inputs you’re giving AI are even best practice in the first place?
I’ve worked with graphic designers for over 20 years, and not once—not a single, solitary time—has round-one direct mail design been fully optimized for fundraising.
This isn’t because designers aren’t talented. It’s because direct mail fundraising design is never taught in school, it’s not intuitive, and pretty often, the strategy calls for something that goes against a designer’s instincts: “ugly” creative that outperforms “beautiful” or “cool.”
Which means if you’re training your AI on years of not-best-practice design, you’ll just get faster, shinier not-best-practice creative back.
And without experience looking over your shoulder, you’ll never know it.
AI can’t read the room
There’s another problem. AI can’t “read the room.”
It doesn’t if donors are weary from constant crises, or if something going on in culture calls for restraint instead of urgency. It doesn’t know when a familiar appeal from three years ago now feels tone deaf.
But experienced fundraisers do.
That’s the difference between data and discernment, and between recycling words and responding to reality.
Why experience still matters
So yes, AI has bytes of information, but it doesn’t have the miles on the road.
It doesn’t have the late nights staring at results, the tough calls to pivot mid-campaign, or the long-term memory of how donors have changed over time.
Experience matters, because that’s where discernment comes from.
Next week in Part 3 of AI in Question: We’ll wrap up the series by talking about just that: discernment. Why it isn’t built from billions of bytes, and why the future of fundraising creative depends on having people who can judge, edit, and guide what AI produces with Spirit-led wisdom.
