AI could soften pay penalties in greedy jobs

As AI accelerates automation, the gender story is not only about lost roles. Economists point to a second possibility: by standardizing parts of high-status “greedy jobs,” AI could reduce the wage penalties linked to constant availability—potentially narrowing

For years, the debate around AI and work has moved along two familiar tracks: jobs vanish, new ones appear, and some workers gain while others fall behind. Those concerns are real. But there is another gender story that keeps getting crowded out.

AI. the argument goes. reflects a knowledge base shaped by centuries of male-dominated production—so women’s experiences and perspectives risk being erased from the models now reshaping work. It also hits faster-growing job categories in which women are heavily represented. including administrative roles. data processing. customer service. and the routine cognitive work that has long depended on a large female workforce. And the people building these systems—and making the design choices that will shape labor markets for decades—are overwhelmingly men.

Yet even as that first story is unfolding, economists say a second story could run in the opposite direction for some women: 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 key idea comes from Claudia Goldin, an economist who won the 2023 Nobel Prize in economics. Goldin has pushed against what she calls “greedy jobs.”

In the highest-paying roles in developed economies—fields like finance. law. consulting. and senior management—the rewards often tilt toward long hours and permanent availability. Deviation from constant presence is penalized through a form of presenteeism. and the relationship between hours and earnings is not linear. Work 20% more can mean earning 40% more. The pay structure, in other words, is stacked toward people who can give everything, all the time, indefinitely.

Goldin’s insight is backed by a systematic review of 48 empirical studies published in 2025 in De Economist, a Dutch academic journal of economics. That review argues the greed-job design is the primary driver of the remaining gender pay gap in high-income countries.

The mechanism is harshly simple. In a greedy job. you can’t easily be replaced by a colleague for a day. a week. or a month. Your value becomes tied to being the specific person who knows a client, a deal, or a case. If a firm can’t swap workers easily. offering flexibility has a productivity cost—so the firm passes that cost on to the employee who requests it in the form of a wage penalty. In practice, mothers are overwhelmingly affected.

There is one counterexample in the research: pharmacy. In the early 1970s, it was a male-dominated profession with a significant gender pay gap. Today, pharmacy is among the most gender-equal occupations in the American and European labor market. The change, the account goes, came from technology. Digital patient records made it easy for one pharmacist to pick up where another left off, making workers more interchangeable. Once the premium for constant individual availability disappeared, the greedy structure weakened—and women flooded into the field.

Now consider what AI could do to the highest-status work that has historically been built like a greedy job.

Legal research. which once could require a junior associate to spend 60 billable hours in a document room. can now be done in minutes. Financial modeling that once justified analyst face time is increasingly automated. Cognitive tasks that made certain professionals hard to replace—diagnostic reasoning in medicine. pattern recognition in consulting. and contract review in corporate law—are being standardized and transferred to software.

That standardization is often framed as a threat, and firms may absolutely want to extract more output with fewer people. Displacement risk is real. But economists also point to a second effect: when AI makes knowledge more available across professionals—when a client’s history. preferences. and context can be instantly accessible rather than locked inside one specific person’s head—worker substitutability increases. Greedy jobs become less greedy.

If jobs become less greedy, the pay penalty attached to reduced availability shrinks. That, in turn, could improve women’s labor market outcomes.

Still, the path is not guaranteed, and the optimism has to be handled carefully.

The first complication is distribution. The jobs most exposed to AI-driven standardization are not evenly spread across genders. Women are already overrepresented in routine cognitive roles—administrative work. data processing. and customer service—that are being automated the fastest. For women in lower-paid work, automation may mean displacement more than liberation.

Second. even if AI makes workers more interchangeable in high-status roles. firms might respond in ways that don’t reduce pressure. Instead of offering more flexibility. they could intensify demands elsewhere—expecting workers to cover more ground because any one person can be replaced more easily. The same technology that makes a lawyer substitutable can also make her more monitored. more easily compared. and potentially more easily discarded.

Third, the motherhood penalty does not operate only through job design. It is reinforced by social norms that push women to adapt when care needs arise. while men do not adapt in the same way. Even if AI reduces the structural penalty tied to availability. those norms would still shape how women and men respond to parenthood unless they shift too.

So the opportunity is narrow. For a specific subset of highly paid. highly greedy professions—law. finance. consulting. and medicine—AI-driven standardization could create a genuine opening to reduce the gender pay gap. The underlying logic is that AI can do to knowledge work what database systems did to pharmacy: loosen the grip of any single individual and make expertise more portable. reducing the premium for being constantly. irreplaceably available.

The pharmacy case restructured one profession. The effects on women’s representation and earnings were profound.

What happens as firms deploy AI across professional services now depends on decisions that don’t come from software alone. The question is whether job redesign is placed on the agenda alongside productivity metrics. If expertise becomes less individual and more shareable. will that change produce more human structures—or will it simply turn into higher billable targets?.

The technology may create a possibility. It does not guarantee the outcome. That final part remains a choice societies will make, not a result AI automatically delivers.

AI automation gender pay gap Claudia Goldin greedy jobs motherhood penalty greedy professions legal research finance consulting medicine pharmacy gender equality