A new report by the McKinsey Global Institute reveals that the rise of artificial intelligence and automation may result in more women than men losing their jobs by the end of the decade. Published on Wednesday, the report predicts that nearly a third of hours worked in the United States could be automated by 2030. Industries most prone to shrinkage due to automation include food services, customer service and sales, and office support. Since women are overrepresented in these sectors and hold more low-paying jobs compared to men, they are likely to be significantly affected. Additionally, the study highlights that black and Hispanic workers, workers without college degrees, and the youngest and oldest workers are also more vulnerable to job displacement by 2030. The report estimates that by 2030, at least 12 million workers will need to find new jobs as their industries shrink, which is 25 percent more than previously predicted in a February 2021 report. Most of these workers are expected to be at the lower end of the pay scale and will likely need to acquire new skills in order to transition to new industries. The report states that the labor market will also experience significant changes over the next decade due to government investments in green technology, the increasing demand for healthcare workers as the U. S. population ages, and the structural shifts brought about by the pandemic. These changes, coupled with advancements in artificial intelligence, will result in an increased demand for some existing jobs, the creation of new jobs in emerging industries, and the obsolescence of other jobs. According to the report, low-wage workers are at the highest risk of job loss by 2030 across all categories. Workers earning less than $38, 200 could account for almost 80 percent of all potential career transitions during that period. This means that retail salespeople, cashiers, and other low-wage workers, among whom a larger proportion are women, are particularly vulnerable. While the progress of artificial intelligence may render certain jobs obsolete, it can also have positive effects on existing jobs and create new work opportunities. For white-collar workers, automation may mean less time spent on repetitive or technical tasks, allowing for more focus on creative or strategic work that AI cannot perform – at least for now.

The report highlights that lawyers and civil engineers are among the workers who stand to benefit the most. However, workers in more manual fields, such as healthcare or agriculture, perform tasks that are not as easily automated. Nonetheless, these fields are predominantly male-dominated. According to the U. S. Bureau of Labor Statistics, women accounted for only 17. 1 percent of civil engineers and 38. 5 percent of lawyers in 2022. While new technologies are expected to create new jobs, not all of these jobs may be desirable. Kerry McInerney, a research fellow at the Leverhulme Center for the Future of Intelligence at Cambridge University, suggests that workers who currently hold low-paying jobs with challenging conditions could potentially be pushed into roles like data labeling, which entails adding labels to videos, images, or audio to teach machine learning models how to recognize content. Nonetheless, McInerney highlights that such jobs can be psychologically harmful due to the nature of the material that needs to be identified. The findings of the report correspond with existing research indicating that women will be affected differently from men by the waves of workforce automation. An analysis of Goldman Sachs data conducted by Mark McNeilly, a marketing professor at the University of North Carolina at Chapel Hill's Kenan-Flagler Business School, and Paige Smith, an MBA candidate at the school, revealed that 8 in 10 female workers in the United States, compared to 6 in 10 male workers, have jobs that are highly susceptible to automation, with over a quarter of their tasks being automatable through generative AI. The report emphasizes that training and retraining workers in future-proof skills will be a significant challenge for employers, but also an opportunity to recruit from overlooked populations, such as older workers, individuals without college degrees, workers with disabilities or gaps in employment, and those who have been previously incarcerated. The report suggests that AI can be utilized by employers to identify and hire candidates from these groups. However, research on the current use of AI in hiring demonstrates that it struggles to grapple with different life experiences and work patterns. For instance, a candidate who recently had a baby might be asked what they do in their spare time, with their ranking being determined by their response, without considering that they may have limited leisure time. McInerney asserts that automated hiring systems based on AI may be able to identify candidates with unconventional backgrounds, but they may not treat them equitably.