Experience Required
AI can accelerate work, but experience is what makes it useful
I’ve been thinking about this quote a lot lately:
“There is no compression algorithm for experience.”
It’s one that came up often during my time at Amazon. Andy Jassy, then CEO of AWS, first said it in 2017.
Waaaay back in the before times—and by that I mean pre-AI.
Since then, Jassy has become Amazon's CEO and I now work at the intersection of AI and education. But the sentiment feels more relevant than ever.
To AI or not to AI …
Is not the question.
That ship has sailed. AI has been adopted faster than any major technology in recent memory, reaching roughly 39% adoption in just two years.1
Compare that to roughly 5 years for the Internet and 12 years for PCs.
Businesses are betting heavily on AI as a driver of efficiency and growth. You can see it everywhere: job postings now list AI proficiency as a required skill, earnings reports tout AI initiatives, and CEOs blame AI for the latest round of layoffs—because AI is coming for all our jobs, apparently. 🙄
Okay, boomer.
I’m not worried that AI is coming for my job.
It’s true that AI can produce go-to-market plans, sales playbooks, prospecting emails, QBR templates—and pretty much any other asset I regularly produce or use in my role—in a fraction of the time it takes me to do the same.
Some of it is even pretty good … so I use it to support my work.
But not all of it is good. Or right. The problem is AI doesn’t know which is which. (See the recent REI bicycle ad as the latest example of this.)
It doesn’t know my audience. It can’t understand university faculty, staff, and administrators as the wonderfully complicated humans they are. It doesn’t understand institutional politics, competing incentives, or decades of accumulated context.
It doesn’t know what motivates them or how to connect with them.
That requires judgment—the kind that comes from observation, trial and error, conferring with peers, and years spent working in and around this industry.
You have to know when to trust AI, when to ignore it, and how to shape its output into something that actually works.
That takes experience. And there is no compression algorithm for that.
In the weeks to come, I’ll be exploring what this means for us as leaders, for our educational institutions, and for the edtech companies that serve them.
In the meantime, I want to hear what you think:
How does AI reshape our work as leaders, educators, and technology providers? And how do we gain experience and develop judgment in a world where AI is doing more of the work?
Hit reply to drop me a quick note or leave a comment below.
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2024. Federal Reserve Bank of St. Louis, The Rapid Adoption of Generative AI.