Have you ever reflected on how important it is to feel like you’re good at something? I know I do.
Any shrink worth their SSRIs will tell you competence—feeling like you have the tools needed to perform the tasks in front of you—has long been understood as a basic psychological need. Feeling like we know what to do, and can do it well, is a really important component of feeling safe and helping us to self-regulate. It’s calming. People really like it.
So I’ve been thinking a lot about how perpetual upskilling has been billed as the “new normal” in most knowledge work over the last couple of years. It seems like that instinct is correct—I don’t think the pace of change is really going to slow down in this era—but the impact of that change, and the potential inequities and overall misery it is introducing, are not really being grappled with much at all.
A moving (maybe lucrative?) target
Jobs and Skills Australia (JSA) did have a go at one piece of the puzzle. In a report published last year they looked at the correlation between years of experience, skill change and salaries. That analysis found that jobs with a lot of skill change tended to also have more salary growth potential over a lot longer period than jobs where the skillset roughly stays the same.
That makes a kind of sense, if you think about it.
If my job was something I learn once and then practice for years in the same way to become an expert at, my pay would hit its peak earlier—basically as soon as I reached that expert level. But if my job required constant regular upskilling, well, that’s a moving ceiling. (I’d argue it would have also meant a bigger variation of the skills acquired across my peer group, depending on who’s kept up and who hasn’t.)
And, typically, the JSA data shows, keeping up with those moving skills has been compensated. Jobs with a moving skill target take around 20 years of experience to top out.
It has also meant a relentless race to stay “competent”. Constant upskilling shakes your feeling of competence, because the thing you build that feeling on stops being what you know and becomes how fast you can learn. And that race has already, historically, disadvantaged people who took any amount of time out of the workforce—say, to have a baby, for example.
Stale skills might be a myth, the damage is real
We know the motherhood penalty is real. Treasury researchers who analysed government data in 2023 found a 55 per cent reduction in average earnings of mothers over the first five years following the birth of a baby. Analysis attributes that mainly to reduced working hours, rather than lower hourly wages.
And skill depreciation from time out of the workforce is also real. Although how real and what kinds of impacts it has is kind of hard to nail down.
But ask any professional woman who has taken even six months off for baby care. Plenty of them are openly worried their skills have gone stale. I’ll be honest here, I read many very dry, difficult papers trying to establish whether this was actually true or not. I still don’t know.
The data seems to show some skill depreciation if you take a year off work, but that you earn it back and then some within a year of coming back. But other studies show the actual skill loss is very minimal, so when a woman expresses concern about this, we’re going off vibes here. Which is its own competence problem: not knowing whether you’re still good at your job does the damage whether or not your skills actually went anywhere.
And actually, that’s kind of the point.
What’s the grading curve?
What studies do show us is that women are punished more harshly for misconduct, judged more for mistakes—and, if one UK experiment is right, for using AI, for that matter. Plus they know it, and they factor that into how enthusiastically they are approaching AI upskilling.
So competence isn’t only something you just feel internally, it’s something other people decide you have—or don’t—and that probably shapes your prospects even more than your own sense of ability.
This paper from PNAS Nexus found women are more skeptical about the alleged benefits of AI at work—partly because they’re more exposed to the jobs it’s coming for. And when the researchers told people AI was likely to destroy more jobs than it created, women’s support fell away faster than men’s. (This is actually just a really great paper all round, five stars, would recommend.)
That’s not to say they use it less. A recent Roy Morgan report found the gender split on AI-use is now about equal. The dudes just trust it more, which, as a woman, I think is stupid. But then I would. Because, again, woman.
Fast-growing … for who?
That skepticism may go some way to explain the widening gender gap in fast-growing AI careers. New research published yesterday by LinkedIn showed women hold 49.7 per cent of non-AI jobs at non-AI companies in Australia, but only 27.6 per cent of AI jobs inside AI firms. In leadership it goes from 28.1 per cent at non-AI companies to 15 per cent at AI ones.
Basically, women are equal participants in the general workforce, not so much in AI jobs, which, LinkedIn points out are “some of the fastest-growing and highest-value opportunities in the labour market.”
When I asked LinkedIn’s head of public policy for ANZ Audrey Lobo-Pulo why exactly they think this is happening, she told me there wasn’t a single explanation but more a combination of factors at play: “Growth is concentrated in research and technical engineering roles, which have historically been male-dominated,” she said. “At the same time, promotion pathways often continue to reward linear and uninterrupted career progression, while women are more likely to experience career breaks.”
And there we have it: our uninterrupted career rearing its head again. “The question,” Lobo-Pulo went on to explain, “is how can employers, educators and workforce systems help ensure more people have opportunities to participate and progress?”
And I mean, great question. Hard to answer, though, when nobody has properly counted what employers spend on training their staff since 2002. That was the subject of a report this past week by JSA, arguing the Australian Bureau of Statistics really ought to start keeping track again.
According to this report Australian employers spent around AU$2.90 per $100 of wages paid on training staff in 1993. By 2002, the last year we captured that figure, it was down to AU$1.30 per $100. In 2025, JSA estimates the spend was probably more like AU$1.10. Just for comparison, they estimate that number was more like £3.80 per £100 in the UK in 2024.
“Employers play a major role in helping workers build, apply and transfer their skills throughout their careers. Workers increasingly need to update and deepen their skills as technological, demographic and structural changes reshape Australia’s labour market dynamics,” said acting JSA commissioner, Megan Lilly when announcing the report. Separately, JSA’s modelling has also shown women were “marginally more exposed” to jobs likely to be impacted by AI augmentation and automation.
So, women aren’t getting into AI jobs at the same rates as the blokes. They’re more skittish about AI and its impacts. And their current jobs are more vulnerable to AI replacement or disruption.
Bro, do you even lift?
Everyone seems to agree training and upskilling matter a lot—and not just in the jobs where keeping up was always part of the deal. It’s spreading, as more and more kinds of work get reshaped by AI. But we’re not really sure what people are being trained in, the quality or transferability of that training, who’s paying for it or when and where it is occurring.
Government stats from April this year suggest rates of formal work-related training are actually falling. But a report from the employer lobby Ai Group last November found participation in training was “above the long-term average”, claiming 86 per cent of it was being funded on the company dime, and around 9 in 10 people were doing it inside their paid work time. (Though about 30 per cent were also doing some of it in their own time—a figure that hasn’t budged since 2007.)
Both could be true. Perhaps people are getting more training on the job so they’re enrolling in fewer programs themselves. We don’t actually know.
What we do know, at least according to researchers at Anthropic, is that the current programs being run are not super effective at boosting outcomes for employees. Their review of the evidence, published last week, found small impacts overall—and that the large-scale programs (the ones run at the size you’d actually need) have been “lackluster” (their word, not mine). They believe this strategy would “likely fall short” against AI-scale displacement.
And I’m going to suggest that brings us back to the therapist’s couch.
What is this? A school for ANTS?! You can’t make someone to learn good.
Ryan and Deci described competence as a basic psychological need, sure. But in that same paper they were also pretty blunt about what happens when learning is imposed instead of chosen. Threats, deadlines, directives, pressured evaluations, imposed goals: all of them reliably flatten motivation.
People taught that way don’t just lose enthusiasm, they learn less well. Being forced to train or die on the proverbial office vine is the worst possible setup. And the learning that suffers most is the conceptual, creative kind—which is precisely what a fast-changing human-skills-first job apparently demands.
If more jobs are moving into the upskill forever camp—and that’s going to be thrust on you whether you like it or not—then we’re staring into a possible future of generally lower feelings of competence, and perpetual forced training which is almost guaranteed not to produce the best learning. That sounds like misery to me.
The people who still get to feel competent will be the ones who can move that feeling off what they know and onto how fast they can learn. Which is a bigger change than you might think. Of course, if you already wake up every morning thinking, “Gee, I’m so good at learning new stuff!”—well, lucky you.
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It's going to be a really interesting future watching how AI changes the way we think, mostly by making convenience so accessible that it quietly takes away the difficulty of actually putting in thought and effort. The easier something becomes to hand off, the less practice we get doing it ourselves, so I wonder if thinking ends up being the first skill that erodes from convenience rather than disuse.
This challenge is so palpable rn. Also, it's one thing to have to deal with this shifting ground when you're employed but a WHOLE other thing when you're self-employed. Nobody's spending even $1.10 per $100 on training you and you're doing it all in your own time and you have very few guardrails to make sure you get some decent outcomes of it. The stakes certainly feel high (even tho the learning can become somewhat addictive itself).