“I am too old for this.” It is the most common thing I hear from accomplished leaders when AI comes up, usually said with a laugh that is not quite a joke. It feels true. It is not. And I do not just believe that, I studied it, and the data disproved the age excuse a decade before AI made it urgent.
The assumption everyone shares
My 2014 doctoral work was a qualitative descriptive multiple-case study built on in-depth interviews with 19 people across adopting and resisting Fortune 500 organizations. Going in, the assumption was obvious: younger leaders adopt new technology, older leaders resist it. The interviews seemed to confirm it at first. Eighteen of the nineteen participants believed younger generations are more likely to adopt, and all nineteen believed older generations are least likely. The belief was nearly unanimous, on both sides of the adoption line.
Then the data turned the belief inside out. The finding that emerged was that generational difference does not actually determine adoption. What people believed about age and what the evidence showed about age were two different things, and the gap between them was the most interesting result in the study.
The outlier who broke the pattern
One participant made the whole thing visible. He was a Baby Boomer, classified by every generational assumption in the study as a least-likely-to-adopt candidate. He did not behave like one. The reason traced back to a single moment from his childhood, before he was ten years old. During a church service, the preacher said that one day money would no longer be exchanged by hand, that electronics would be used instead. Two decades later, debit and credit cards arrived exactly as predicted. That early moment lodged something in him, and he stayed current with technology for the rest of his life, convinced it was worth keeping ahead of.
He was the outlier who proved the rule. His birth year said he should resist. His early relationship with technology said he should adopt. The early relationship won. He mattered more than the averages, because he showed what the averages were actually measuring, and it was not age.
What actually predicts adoption
When I looked past age at what the adopters had in common, the real driver was use or admiration of technology in the first twelve years of life. Every adopting participant in the study had engaged with or been fascinated by technology early, and carried that openness forward. The resisters, by and large, had not, or had stopped engaging at some point and never restarted. The pattern was not generational. It was a relationship with technology that some people of every age carried and others did not.
This is not just one study’s quirk, and the independent evidence on it has only gotten stronger. A 2025 peer-reviewed study in JMIR Aging surveyed more than two thousand people across three generations and found that the ability to keep up with new technology is shaped by attitudes, economics, and engagement, what the authors call complex and intersecting factors that go beyond age (JMIR Aging, 2025). Pew Research reaches the same place from a different angle: about one in five adults 65 and older hold strong early-adopter preferences, the same share found in much younger groups, and the smartphone gap between the youngest and oldest adults narrowed from 53 points in 2012 to 35 points by 2021 (Pew Research Center; Pew Research Center, 2022).
The lesson is blunt and freeing at the same time. Your ability to adopt AI does not expire with your birth year. It tracks whether you are willing to engage with it now. Age is not the variable. Engagement is. This is one of the five forces I cover in the 5 drivers of AI adoption, and it pairs directly with the real gate, which is understanding, covered in you cannot adopt what you do not understand.
It is already happening
If you still think older professionals are sitting out the AI wave, the most recent data says otherwise. AARP’s 2025 research found that AI use among adults 50 and older nearly doubled in a single year, rising from 18 percent in 2024 to 30 percent in 2025, and that the real barriers people cite are data privacy and ease of use, not age (AARP, 2025). The people supposedly too old for AI are adopting it faster than almost any other group right now. The story that age is the barrier is not just wrong in principle, it is being disproven in real time.
What to do with that
If you have been using your age as the reason to stay on the sidelines, retire the excuse. You do not need to have grown up with this technology. You need to start engaging with it deliberately now, the way that one Baby Boomer never stopped doing. Pick one real task this week and do it with an AI tool instead of the old way, then another next week. Exposure compounds, and according to the research, sustained engagement is the thing that actually separates adopters from everyone else.
If you want a clear read on where you stand and what to do first, the Omnine AI Readiness Assessment takes about three minutes and gives you a starting point built around your actual situation, not your birthday.
References
Goodwin, M. R. (2014). A qualitative descriptive multiple-case study: Fortune 500 leaders’ social business platform adoption (Doctoral dissertation, University of Phoenix). ProQuest Dissertations Publishing (UMI No. 3648813).
Offerman, J., et al. (2025). Factors associated with the ability to keep up with technology developments. JMIR Aging, 8, e77930.
Pew Research Center. Older adults and technology use.
Pew Research Center. (2022). Share of those 65 and older who are tech users has grown in the past decade.
AARP Research. (2025). 2025 tech trends and adults 50-plus.