The dialog about AI and work revolves principally round jobs being destroyed or new ones rising, across the staff benefiting and people more likely to be left behind. All these debates are reputable. However there are such a lot of different features and penalties which can be not often addressed.
For one, AI has a women problem—with more of them opting out. The info that trains the know-how displays centuries of male-dominated information manufacturing, erasing girls’s experiences and views from the fashions that are actually reshaping how we work. The roles it’s eliminating quickest are disproportionately held by girls: administrative roles, information processing, customer support, the huge military of routine cognitive work that the feminine workforce has lengthy relied on. And the folks 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 girls whose jobs are reworked. Apparently, AI may 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 entails 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 commonplace 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 cause: Full-time jobs—particularly the highest-paying ones—aren’t designed for folks with caregiving obligations. Consequently, these folks 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 will not be linear. Work 20% extra, and also you would possibly earn 40% extra. The pay construction is stacked towards those that may give all the pieces, on a regular basis, indefinitely.
Goldin, who gained 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 evaluation 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 international locations. The very best-paying jobs had been constructed round a employee who has, traditionally, virtually all the time been a person who may depend on another person to look after his household. That’s a really huge cause for the pay hole.
In a grasping job, you can’t simply get replaced by a colleague for a day, per week, or a month. Thus, your worth is tied up in being the particular one that is aware of this shopper, 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 sphere of pharmacy. Within the early Seventies, it was a male-dominated career with a big gender pay hole. In the present day, it is likely one of the most gender-equal occupations within the American (and European) labor market. What modified was know-how: Digital affected person data made it straightforward for one pharmacist to select up the place one other left off. Staff grew to become form of interchangeable. The premium for fixed particular person availability disappeared, and with it, the grasping construction of the pharmacist job. Then girls flooded in.
What automation may do
Now contemplate what AI might 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 executed in minutes. Monetary modeling that justified analyst face time is more and more automated. Lots of the cognitive duties that made sure professionals irreplaceable—diagnostic reasoning in drugs, sample recognition in consulting, and contract evaluation 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 folks. The displacement threat is actual. However there may be additionally one other consequence. When AI standardizes the information related to a high-status job, when it makes it potential for a shopper’s historical past, preferences, and context to be immediately accessible to any competent skilled fairly than locked inside one particular individual’s head, it will increase employee substitutability. It makes grasping jobs much less grasping. And when jobs turn 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 will not be straightforwardly optimistic, and several other issues may overwhelm the substitutability impact. First, the roles most uncovered to AI-driven standardization usually are not uniformly distributed throughout genders. Ladies are already overrepresented in routine cognitive roles—administrative work, information processing, customer support—which can be being automated the quickest. The substitutability argument applies particularly to high-status, high-paying grasping jobs. For ladies 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 staff to cowl extra floor exactly as a result of any one in every of them can now be extra simply changed. The identical know-how that makes a lawyer substitutable additionally makes her extra simply monitored, extra simply in contrast, and probably extra simply discarded.
Third, the motherhood penalty will not be solely a perform of job design. It’s strengthened by social norms that also dictate that when care must be executed, girls 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 alter in parallel.
A slim opening
For a selected subset of extremely paid, extremely grasping professions—regulation, finance, consulting, drugs—AI-driven standardization creates a real alternative to cut back the gender pay gap. As a result of it may possibly do to information work what database techniques did to pharmacy: It could actually loosen the grip of any single particular person, make experience extra moveable, and scale back the premium for being continuously, irreplaceably accessible. The pharmacy case restructured one career, and the results on girls’s illustration and earnings in that career had been profound.
As corporations deploy AI throughout skilled companies, is anybody enthusiastic 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 greater billable targets?
The know-how might create an fascinating chance. It doesn’t assure the result. That half remains to be our collective selection.
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