We’ve been sold a narrow definition of success for a long time. Revenue targets, market share, titles, corner offices. Leaders climb the ladder, hit the numbers, and still feel like something’s missing. That’s because most of what we measure at work h…
Finding perspective is primarily about mental flexibility, the willingness to question assumptions and examine situations where we feel stuck from a fresh perspective. That means being prepared to see what is present, and also seek out what might be c…
Human achievements never come without their downsides, and those unwelcome consequences tend to have highly uneven distributions. Higher speeds and their effects have been no exception. Speed brings perils and succor: Excessive speed, in so many guise…
I opened my South by Southwest (SXSW) session with a confession: I have a video from over a decade ago where I am impersonating Ron Burgundy from “Anchorman.” Stiff delivery, robotic cadence, completely inauthentic. Did I say video? I’ll c…
About ten years ago, employees at Michigan-based mortgage lender United Wholesale Mortgage started to notice a huge increase in the use of connected devices at work.
“From cellphones, all of a sudden, you have iPads, and then smartwatches,” s…
College graduates are up against a number of forces as they navigate the current job market—AI being chief among them. As companies cut entry-level jobs and cite AI adoption to justify layoffs, new entrants to the workforce have found themselves in an…
According to a recent internal memo, Microsoft employees are feeling positive about producing meaningful work, but less so about coaching, feedback and motivation from managers, Business Insider reports.
In Microsoft’s biannual “Employee Signals” s…
It’s estimated that the average person will spend 90,000 hours of their life working—that’s roughly a thousand weeks, or a third of our lives.
Over the years, I’ve watched many of my Oxford and Harvard university classmates come to reunions and alu…
If there were ever a truth about generationalism, it’s this: Every generation has the same complaint about the generation that came after it. Kids these days don’t want to work. They want everything but don’t want to work hard enough to get it. They all want participation trophies. We’ve all heard some semblance of these accusations in some fashion or another. In fact, we’re all probably guilty of delivering our own version of these generation-dividing dispositions. However, if every generation says the same about the next, then, inherently, how true can these criticisms really be? Perhaps, instead of there being an impediment in the work ethic of today’s “kids,” maybe they’re actually noticing something we “adults” aren’t ready to admit.
Maybe it’s the reality that entrusting one’s entire career to one organization might actually be a losing proposition—a perspective change that shifted between the boomer workforce and Gen X. Or maybe it’s the idea that work-life should be balanced with life-life—a dispositional shift from the Gen X workforce by millennials. The truth is, they (millennials) were right, just as we (Gen Xers) were right. And right now, today’s kids (Gen Z) are probably noticing something that we can’t fully comprehend: The rat-race orthodoxy that most of us have built our careers around may not be as fruitful as we thought. I’m sure your mind is chock-full of rebuttals to that provocation, but I want to make the case for our Gen Z coworkers here. Don’t take it from me; take it from someone who climbed the professional mountain, planted his flag at the top, and discovered that the view from up there was nowhere near as compelling as promised. And that someone is Blake Mycoskie.
Mycoskie built TOMS into the fastest-growing shoe company in the world. He was the poster child of conscious capitalism, graced the cover of Inc., wrote a best-selling book, and keynoted just about every prestigious business conference there is. He has the kind of biography MBA students point to when they say I want to do that. Yet, he spent the bulk of those years, by his own account, in a depression he couldn’t name out loud. His external life was the thing every business reporter in the country was calling a dream, but his ascension to corporate fame and fortune proved otherwise. So, we invited Mycoskie onto the latest episode of the From the Culture podcast to talk about what he learned from his view on top of the world, and what we all can glean as we pursue our own corporate “glow up” (Am I using that right, Gen Z?).
As Mycoskie put it, “There was a huge difference between how everyone was telling me I should be feeling and how I was really feeling inside. I was so ashamed because I felt like I didn’t have the right to feel that way.” So, he didn’t say anything; he just suffered in silence to the point where he contemplated self-harm. And as the distance between the public scoreboard and his private thoughts widened, he realized no accolade could ever close the gap. No magazine cover. No round of funding. No public stage. No external validation could do the trick because the hole wasn’t shaped like any accomplishment; instead, it was shaped by an internal question: Am I worthy of being here?
All that achievement, yet Blake was not fulfilled. This is the part that the Gen Z pushback is actually about. They aren’t asking for a participation trophy; they are looking at a generation that won every professional trophy but still can’t sleep at night. They are looking at all our accolades and asking whether winning them was worth the cost. Worth our friendships, our families, and all the things we say we really “love.” And, you know what; they’re right to ask. When do we have enough?
This inquiry has become the focus of Mycoskie’s work in his post-TOMS world. He started a new venture called Enough that’s more of a mental health undertaking than a commercial enterprise, and which helped Mycoskie redefine his own worth. It’s now poised to help others remember their own. At Enough, Mycoskie institutionalizes all the Gen Z conventions that other Gen Xers would characterize as “soft” in hopes of helping people focus on the things that truly matter. No emails or texts before 9 a.m. or after 6 p.m. No overworking no matter how much they love the work. And, perhaps most important, Mycoskie made an explicit commitment to admit publicly when he’s gotten the balance wrong (and to correct it out loud) because he realized that every team takes its cues from whether the people above them celebrate weekend grinds or call them out. He knows that leaders who model enough make it permissible for the next layer down, who make it permissible for the next. And so on. So, he adheres to it.
Now, I don’t know about you, but that sounds pretty awesome. I mean, say what you will about Gen Z, but maybe the kids are onto something. Maybe what they’re pushing back against isn’t the work but the lie about what the work was supposed to give us. That the work was supposed to define us because we silently told ourselves that we weren’t enough otherwise. So, perhaps, the next time someone on your team announces with pride that they worked all weekend to get something across the finish line, don’t applaud. Ask what they missed at home to make it happen. Ask whether the deadline was real or whether it could have moved. Ask them if it was worth it? Ask them when enough is enough.
Check out our full conversation with Blake Mycoskie on the latest episode of From the Culture here.
The conversation about AI and work revolves mostly around jobs being destroyed or new ones emerging, around the workers benefiting and those likely to be left behind. All these debates are legitimate. But there are so many other aspects and consequences that are rarely addressed.
For one, AI has a women problem—with more of them opting out. The data that trains the technology reflects centuries of male-dominated knowledge production, erasing women’s experiences and perspectives from the models that are now reshaping how we work. The jobs it is eliminating fastest are disproportionately held by women: administrative roles, data processing, customer service, the vast army of routine cognitive work that the female workforce has long depended on. And the people building these systems and making the design choices that will shape labor markets for decades are, overwhelmingly, men.
All of this is true. And it matters enormously. But there is a second story about artificial intelligence and gender that almost nobody is telling—one that may run in the opposite direction for other women whose jobs are transformed. Interestingly, AI could reduce the gender pay gap in the highest-paying professions … as an unintended consequence of what automation does to the jobs that pay the most.
The mechanism is less intuitive than it sounds, and it involves a concept that economists like Claudia Goldin call greedy jobs.
The architecture of inequality
Why does the gender pay gap persist in the first place? There are several standard explanations: Women choose (freely or not) lower-paying fields, they take more career breaks, or they don’t negotiate as successfully. Over the past few years, some of these explanations have been challenged by researchers who highlight another, more profound reason: Full-time jobs—especially the highest-paying ones—aren’t designed for people with caregiving responsibilities. As a result, these people have less access to them.
Indeed, the best-paying jobs in developed economies share a set of characteristics: They reward long hours disproportionately, they require permanent availability, and they penalize any deviation from constant presence (presenteeism). In finance, law, consulting, and senior management, the relationship between hours and earnings is not linear. Work 20% more, and you might earn 40% more. The pay structure is stacked toward those who can give everything, all the time, indefinitely.
Goldin, who won the 2023 Nobel Prize in economics, went on a crusade against the so-called greedy jobs. And her central insight is confirmed by a systematic review of 48 empirical studies published in 2025 in De Economist, a Dutch academic journal of economics. It constitutes the primary driver of the remaining gender pay gap in high-income countries. The highest-paying jobs were built around a worker who has, historically, almost always been a man who could rely on someone else to care for his family. That’s a very big reason for the pay gap.
In a greedy job, you cannot easily be replaced by a colleague for a day, a week, or a month. Thus, your value is tied up in being the specific person who knows this client, this deal, this case. When a firm cannot easily swap one worker for another, providing flexibility comes at a productivity cost. The firm then passes this cost on to the employee requesting it in the form of a wage penalty. Mothers, overwhelmingly.
The one counterexample in the research is the field of pharmacy. In the early 1970s, it was a male-dominated profession with a significant gender pay gap. Today, it is one of the most gender-equal occupations in the American (and European) labor market. What changed was technology: Digital patient records made it easy for one pharmacist to pick up where another left off. Workers became kind of interchangeable. The premium for constant individual availability disappeared, and with it, the greedy structure of the pharmacist job. Then women flooded in.
What automation could do
Now consider what AI could be doing to the highest-paying professions. Legal research, which once required a junior associate to spend 60 billable hours in a document room, can now be done in minutes. Financial modeling that justified analyst face time is increasingly automated. A lot of the cognitive tasks that made certain professionals irreplaceable—diagnostic reasoning in medicine, pattern recognition in consulting, and contract review in corporate law—are being systematically standardized and transferred to software.
This is usually seen as a threat (which it very well may be). Firms want to extract more output with fewer people. The displacement risk is real. But there is also another consequence. When AI standardizes the knowledge associated with a high-status job, when it makes it possible for a client’s history, preferences, and context to be instantly accessible to any competent professional rather than locked inside one specific person’s head, it increases worker substitutability. It makes greedy jobs less greedy. And when jobs become less greedy, the pay penalty for reduced availability shrinks, and women’s labor market outcomes improve.
Let’s not be unreasonably optimistic
The relationship between automation and gender equality is not straightforwardly positive, and several things could overwhelm the substitutability effect. First, the jobs most exposed to AI-driven standardization are not uniformly distributed across genders. Women are already overrepresented in routine cognitive roles—administrative work, data processing, customer service—that are being automated the fastest. The substitutability argument applies specifically to high-status, high-paying greedy jobs. For women in lower-paid work, automation is more likely to mean displacement than liberation.
Second, firms may respond to increased substitutability, not by making jobs more flexible, but by intensifying demands in other ways—expecting workers to cover more ground precisely because any one of them can now be more easily replaced. The same technology that makes a lawyer substitutable also makes her more easily monitored, more easily compared, and potentially more easily discarded.
Third, the motherhood penalty is not only a function of job design. It is reinforced by social norms that still dictate that when care needs to be done, women adapt and men don’t. Even if AI reduces the structural penalty for reduced availability, those norms will continue to shape how women and men respond to parenthood—unless they change in parallel.
A narrow opening
For a specific subset of highly paid, highly greedy professions—law, finance, consulting, medicine—AI-driven standardization creates a genuine opportunity to reduce the gender pay gap. Because it can do to knowledge work what database systems did to pharmacy: It can loosen the grip of any single individual, make expertise more portable, and reduce the premium for being constantly, irreplaceably available. The pharmacy case restructured one profession, and the effects on women’s representation and earnings in that profession were profound.
As firms deploy AI across professional services, is anyone thinking about this deliberately? Job redesign should be on the agenda alongside productivity metrics. Will the reduction in individual irreplaceability that AI creates get channeled into more human structures or just into higher billable targets?
The technology may create an interesting possibility. It does not guarantee the outcome. That part is still our collective choice.
