The dialog about AI and work revolves principally round jobs being destroyed or new ones rising, across the employees benefiting and people more likely to be left behind. All these debates are respectable. However there are such a lot of different features and penalties which are hardly ever addressed.
For one, AI has a women problem—with more of them opting out. The information that trains the expertise displays centuries of male-dominated data manufacturing, erasing ladies’s experiences and views from the fashions that at the moment are reshaping how we work. The roles it’s eliminating quickest are disproportionately held by ladies: administrative roles, information processing, customer support, the huge military of routine cognitive work that the feminine workforce has lengthy relied on. And the individuals constructing these techniques and making the design decisions that may form labor markets for many years are, overwhelmingly, males.
All of that is true. And it issues enormously. However there’s a second story about synthetic intelligence and gender that just about no person is telling—one which will run in the wrong way for different ladies whose jobs are remodeled. Curiously, AI might scale back the gender pay hole within the highest-paying professions … as an unintended consequence of what automation does to the roles that pay probably the most.
The mechanism is much less intuitive than it sounds, and it includes an idea that economists like Claudia Goldin name grasping jobs.
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The structure of inequality
Why does the gender pay hole persist within the first place? There are a number of customary explanations: Ladies select (freely or not) lower-paying fields, they take extra profession breaks, or they don’t negotiate as efficiently. Over the previous few years, a few of these explanations have been challenged by researchers who spotlight one other, extra profound motive: Full-time jobs—particularly the highest-paying ones—aren’t designed for individuals with caregiving obligations. Because of this, these individuals have much less entry to them.
Certainly, the best-paying jobs in developed economies share a set of traits: They reward lengthy hours disproportionately, they require everlasting availability, and so they penalize any deviation from fixed presence (presenteeism). In finance, regulation, consulting, and senior administration, the connection between hours and earnings isn’t linear. Work 20% extra, and also you would possibly earn 40% extra. The pay construction is stacked towards those that may give the whole lot, on a regular basis, indefinitely.
Goldin, who received the 2023 Nobel Prize in economics, went on a campaign in opposition to the so-called grasping jobs. And her central perception is confirmed by a scientific evaluate of 48 empirical research published in 2025 in De Economist, a Dutch academic journal of economics. It constitutes the first driver of the remaining gender pay hole in high-income nations. The best-paying jobs had been constructed round a employee who has, traditionally, nearly all the time been a person who might depend on another person to take care of his household. That’s a really massive motive for the pay hole.
In a grasping job, you can not simply get replaced by a colleague for a day, per week, or a month. Thus, your worth is tied up in being the precise one that is aware of this consumer, this deal, this case. When a agency can not simply swap one employee for an additional, offering flexibility comes at a productivity price. The agency then passes this price on to the worker requesting it within the type of a wage penalty. Moms, overwhelmingly.
The one counterexample within the analysis is the sector of pharmacy. Within the early Seventies, it was a male-dominated career with a major gender pay hole. At this time, it is likely one of the most gender-equal occupations within the American (and European) labor market. What modified was expertise: Digital affected person data made it straightforward for one pharmacist to choose up the place one other left off. Employees grew to become sort of interchangeable. The premium for fixed particular person availability disappeared, and with it, the grasping construction of the pharmacist job. Then ladies flooded in.
What automation might do
Now contemplate what AI may very well be doing to the highest-paying professions. Authorized analysis, which as soon as required a junior affiliate to spend 60 billable hours in a doc room, can now be accomplished in minutes. Monetary modeling that justified analyst face time is more and more automated. Plenty of the cognitive duties that made sure professionals irreplaceable—diagnostic reasoning in medication, sample recognition in consulting, and contract evaluate in company regulation—are being systematically standardized and transferred to software program.
That is normally seen as a risk (which it very effectively could also be). Companies need to extract extra output with fewer individuals. The displacement danger is actual. However there’s additionally one other consequence. When AI standardizes the data related to a high-status job, when it makes it doable for a consumer’s historical past, preferences, and context to be immediately accessible to any competent skilled moderately than locked inside one particular individual’s head, it will increase employee substitutability. It makes grasping jobs much less grasping. And when jobs change into much less grasping, the pay penalty for decreased availability shrinks, and ladies’s labor market outcomes enhance.
Let’s not be unreasonably optimistic
The connection between automation and gender equality isn’t straightforwardly optimistic, and a number of other issues might overwhelm the substitutability impact. First, the roles most uncovered to AI-driven standardization will not be uniformly distributed throughout genders. Ladies are already overrepresented in routine cognitive roles—administrative work, information processing, customer support—which are being automated the quickest. The substitutability argument applies particularly to high-status, high-paying grasping jobs. For girls in lower-paid work, automation is extra more likely to imply displacement than liberation.
Second, corporations might reply to elevated substitutability, not by making jobs extra versatile, however by intensifying calls for in different methods—anticipating employees to cowl extra floor exactly as a result of any one in all them can now be extra simply changed. The identical expertise that makes a lawyer substitutable additionally makes her extra simply monitored, extra simply in contrast, and doubtlessly extra simply discarded.
Third, the motherhood penalty isn’t solely a operate of job design. It’s bolstered by social norms that also dictate that when care must be accomplished, ladies adapt and males don’t. Even when AI reduces the structural penalty for decreased availability, these norms will proceed to form how men and women reply to parenthood—except they modify in parallel.
A slender opening
For a selected subset of extremely paid, extremely grasping professions—regulation, finance, consulting, medication—AI-driven standardization creates a real alternative to scale back the gender pay gap. As a result of it might do to data work what database techniques did to pharmacy: It could possibly loosen the grip of any single particular person, make experience extra transportable, and scale back the premium for being consistently, irreplaceably obtainable. The pharmacy case restructured one career, and the results on ladies’s illustration and earnings in that career had been profound.
As corporations deploy AI throughout skilled companies, is anybody fascinated about this intentionally? Job redesign needs to be on the agenda alongside productiveness metrics. Will the discount in particular person irreplaceability that AI creates get channeled into extra human constructions or simply into increased billable targets?
The expertise might create an fascinating chance. It doesn’t assure the end result. That half continues to be our collective selection.
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