Why Seasoned Professionals Are Built to Brave the AI Wave

Mike Lewis – Principal

I recently met with a senior leader at a Fortune 100 company who had just turned 50 years old, and she said something that shocked me: “I don’t know if I have another one of these in me.” She was referring to the rise of generative AI and the pressure to seamlessly integrate it into everyday ways of working.

The anxiety around learning how to use AI effectively is real, but the people most worried about not being able to keep up with AI are, statistically, those with the deepest evidence that they can. That’s because, like the leader I spoke with, many of us have experienced major technological advances and adapted accordingly.

Leaders aged 60 years or older, for example, started their careers in a paper-and-phone office. They have since absorbed PCs, spreadsheets, digital design, email, the web, ERP, the iPhone, social media, cloud/SaaS, Zoom, and remote work. This equates to roughly 11 mainstream tech advances that have required them to adapt in some way. Leaders who are 50 have navigated about nine major tech waves; that number drops to six for 40-year-olds and just two for 30-year-olds, who have only really experienced the COVID-era shift to remote work and generative AI.

That asymmetry matters, because the 32-year-old absorbing AI is experiencing only their second real “everything changes overnight” workplace event; whereas, the 55-year-old absorbing it has a track record of nine prior tech events, all of which have followed roughly the same arc: anticipatory dread, followed by an awkward middle, and then, finally, a new normal where the job evolved instead of vanished.

The AI wave is following a similar script. Workplace adoption rates for AI, which reached 28% in two years, are similar to those for PCs, which reached 25% in three years. Workplace AI usage is about 34% for workers younger than 40 and 17% for those 50 and older, which mirrors the early-PC and early-internet skew that compressed within a few years as the tools matured.

The forces fueling anxiety around AI

Through working with clients, we’ve learned that the fear people describe (I won’t be able to keep up with AI) stems from anticipation, not their capacity to adapt. When experiencing uncertainty, the brain inflates both the probability and the severity of a future threat. When translated to change management, this means that workers facing a looming disruption almost always believe it will be worse than it turns out to be.

Older workers who’ve used computers regularly throughout their careers, however, are reporting anxiety levels comparable to—and sometimes lower than—younger workers, because they’ve already proven to themselves that they can and will adapt.

Another major factor fueling anxiety around AI is the number of organizational changes employees have to navigate today. Gartner research found that in 2016, the average employee experienced just two planned enterprise changes, such as an organizational restructure, culture transformation, or system implementation. In 2022, that number rose to 10, and by 2025, it climbed to 14 concurrent change initiatives per employee, with many organizations reporting overlap rates exceeding 60%.

The skills that enable seasoned employees to find value in AI

Although 30- and 20-year-old employees have more native fluency with AI tools, they don’t yet have the depth of judgment and domain expertise that their more seasoned colleagues have spent decades developing, and it’s these skills that enable people to use AI effectively.

The clearest historical parallel is the introduction of the electronic spreadsheet. Since the workforce started using electronic spreadsheets in the 1980s, accounting clerks lost roughly 400,000 routine jobs, but accountants gained roughly 600,000 higher-judgment ones. The skill floor rose, but the headcount didn’t decrease. The accountants who thrived were those who paired domain expertise with the new tool. The same will be true for those who pair judgement expertise with AI.

Three leadership considerations for reframing AI adoption

1. Stop diagnosing AI adoption as a generational problem. Instead, focus on creating psychological safety that encourages employees to experiment with AI. Logistic and linear regression analyses show that psychological safety reliably predicts whether employees adopt AI tools but does not predict how often or how long they use AI once adoption has occurred. In other words, psychological safety is the gate, but once employees start using AI, organizations must enable them to continue doing so efficiently in the flow of work.
2. Frame AI as collective learning, not a skills test. Amy Edmondson’s foundational research on hospital teams found that the same new technology was adopted quickly where leaders framed it as “we are figuring this out together,” and contested where leaders framed it as “go learn this tool.” Of the 500 leaders surveyed by MIT Technology Review Insights in 2025, 83% believe a company culture that prioritizes psychological safety measurably improves the success of AI initiatives, and four in five leaders agree that organizations fostering such safety are more successful at adopting AI.
3. Name change fatigue out loud. When managers create a psychologically safe environment for their team, it can have a 46% reduction in change fatigue, according to Gartner research. A simple acknowledgment that AI is the eighth or ninth wave a tenured employee has absorbed during their career is an easy place to start that recognizes both the reality of the moment and the employee’s ability to adapt.

If you’re a seasoned professional reading this and still thinking I don’t know if I have another one in me, take a deep breath. You’ve done this before. Your job may change, but you have the skills and experience to evolve with it.