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It happens in a meeting, or a hallway, or a quick side conversation after someone hands in work that surprised you. A person on your team does something (asks a question, pushes back on a process, handles feedback differently than you expected) and without meaning to, you file them under a generational category instead of asking what's actually going on.
Managing a multigenerational workforce is one of the genuinely interesting challenges of running a small business right now. You may have people in their twenties working alongside people in their fifties, with different relationships to hierarchy, communication, feedback, technology, and what a good job even means. That range is real. But the mistake leaders make is turning a range into a rulebook: deciding in advance how someone will think, work, or respond based on the decade they were born in.
Shortcuts like that make leadership feel simpler. They also make it worse.
Why generational stereotypes make the leader's job harder, not easier
A stereotype gives you a story about someone before you've listened to them. And a leader operating on a story they haven't tested will keep missing what's actually in front of them.
A stereotype gives you a story about someone before you've listened to them.
The "young people only want flexibility" story misses the young person who wants structure and mentorship. The "older employees resist technology" story misses the one who adopted every new system faster than anyone and resents being treated like they wouldn't. The "millennials need constant praise" story misses the person who found that kind of management condescending and started looking for work elsewhere.
Every one of those assumptions makes the same mistake: substituting a demographic label for a person. And in a small business, where there's rarely much slack between a team that works and one that doesn't, that substitution costs more than you'd expect.
As we explored in the post on leaders who know themselves, the leader's own assumptions are often the thing most worth examining. That's doubly true when the assumption is about someone you haven't really asked.
Five practices for leading across generations
1. Ask instead of assuming
Find out how each person prefers to communicate and what support actually looks like to them. Not in a formal survey. In a regular one-on-one conversation. Do they want real-time feedback or end-of-week check-ins? Do they prefer written direction or a brief verbal overview? When something goes sideways, do they want to work through it immediately or think first and come back?
These preferences do correlate with age and life stage sometimes. They also correlate with personality, past experience with managers, how they were raised, and a dozen other things. The only way to know is to ask, and then actually adjust.
2. Explain the why behind change
Announcing a new system or process as a done deal, without context, creates more resistance across every age group than the change itself usually warrants. People are more likely to adapt when they understand the reasoning: why the old way wasn't working, what problem the new approach is trying to solve, and what's expected of them during the transition.
This is especially true when the change involves technology. As we've written about in the first AI conversation with your team and in the post on buying software without consulting your team first, the conversation about why a change is happening matters as much as the change itself. A leader who explains the context is not being weak. They're being effective.
3. Make expectations visible
Clear, written standards reduce more confusion than generational theory ever will. When people know what "good work" looks like in concrete terms (not vague aspirations but actual expectations about quality, communication, and follow-through), there's less room for the kind of ambiguity that generates friction across a team.
Younger employees sometimes get labelled as lacking professionalism when they're actually operating on assumptions their manager never clearly stated. Older employees sometimes get labelled as inflexible when they're actually following rules that were never updated. Visible expectations protect everyone from that dynamic.
4. Create two-way learning
Experience and fresh perspective both have value. A 55-year-old who has navigated three economic downturns knows things a 24-year-old doesn't. A 24-year-old who grew up building digital workflows knows things a 55-year-old may not. The mistake is treating knowledge as a one-way handoff, from older to younger, or from "tech-savvy" to "less tech-savvy."
Build in ways for people to learn from each other deliberately. Pair people across experience levels on projects. Create space in team conversations for different kinds of expertise to surface. Make it clear that learning goes in all directions and that nobody gets permanently cast as the one who needs to catch up.
5. Give feedback and development in human terms
Feedback that's timely, specific, and connected to growth works. Feedback filtered through assumptions about how someone's age should determine their response to criticism doesn't.
A younger employee who pushes back on feedback isn't necessarily resistant. They may have a good point, or they may need it explained differently, or they may have come from a workplace where pushback was actively encouraged. An older employee who doesn't respond emotionally to a correction isn't unaffected. They may simply process things internally before speaking.
Give feedback to the individual. Adjust based on what you actually observe, not based on what you assume their generation trained them to expect.
AI is one current example, and it illustrates the point well
Statistics Canada's March 2026 Labour Force Survey supplement found that generative AI use at work varies by age group. Interestingly, core-aged workers between 25 and 54 had the highest rates of use in high-exposure occupations, not younger workers, as many people assume. (source) Among workers familiar with generative AI tools, 37.4% didn't believe those tools applied to their work. The release doesn't break that number down by age.
The implication for leaders is worth sitting with: if you're planning to introduce AI tools to your team, don't decide in advance who will welcome it and who will resist based on age. Ask which tasks feel repetitive and tedious. Find out where people already feel stretched. Train people properly for the actual tools they'll use. Test with real users before rolling it out broadly. Those steps work for every person on your team, regardless of when they were born.
What different generations often have in common
For all the real differences in communication style, career expectations, and relationship to technology, most people at work want the same core things:
To be treated with respect. To receive feedback that's honest and useful, not vague or condescending. To have clear expectations rather than shifting goalposts. To be fairly compensated for good work. And to feel that what they're doing matters, that it connects to something beyond just filling hours.
Those aren't generational preferences. They're human ones. And when a team is struggling, the cause is usually that one or more of these basics isn't being delivered, not that the age gap between employees is too wide.
The leaders who navigate multigenerational teams well are often not the ones who have learned a lot about each generation. They're the ones who are genuinely curious about each person.
Quick questions
Do generational differences really matter at work?
Sometimes, a little. But people vary far more than labels suggest. Ask each person how they like to work, and adjust to what you hear.
How do I lead a team with a wide age range?
Ask instead of assuming, explain the reason behind changes, make expectations clear and visible, let people learn from each other, and give feedback to the individual.
Are younger workers more likely to use AI at work?
Not necessarily. In Statistics Canada's March 2026 data, workers aged 25 to 54 had the highest use of generative AI in high-exposure occupations, ahead of younger workers.
The goal is not expertise in every generation
The goal is not to become an expert in every generation. It is to become the kind of leader who listens closely enough to understand the people in front of them.
If change is creating friction on your team, start with an honest conversation before you reach for another tool. Ask what's not working and why. Ask what would make the work better. You may find that the answers are less about generation and more about leadership, which is something you can actually do something about. The free assessment is a good place to start.
Source: Statistics Canada, "Use of generative artificial intelligence tools among Canadian workers, March 2026," The Daily, July 30, 2026