More women than men are likely to lose their jobs to artificial intelligence and automation by the end of the decade, as per a report by the McKinsey Global Institute. The study predicts that nearly one-third of all hours worked in the United States could be automated by 2030.
Industries such as food services, customer service, sales, and office support are expected to shrink the most due to automation. Since women are overrepresented in these sectors and often hold low-paying jobs, they are more susceptible to the impact of automation. Similarly, black and Hispanic workers, those without college degrees, and both the youngest and oldest employees are also more likely to face job transitions by 2030.
According to the report, at least 12 million workers will need to switch jobs as their current industries shrink, which is 25% more than the institute’s previous prediction in 2021. The report identifies today’s low-wage workers as the most vulnerable group to job losses by 2030. Workers earning less than $38,200 may account for nearly 80% of potential career transitions during that period, particularly retail salespeople, cashiers, and other low-wage workers, many of whom are women.
While some jobs may become obsolete due to AI, the report suggests that it could also enhance existing jobs and create new opportunities. For white-collar workers, automation could free up time from repetitive or technical tasks, allowing them to focus on creative and strategic work that AI cannot perform yet.
Existing research confirms that women will be affected differently from men by the waves of workforce automation. Another study based on Goldman Sachs data shows that 8 in 10 female workers in the United States, compared to 6 in 10 men, have jobs that are highly exposed to automation.
The report emphasises the need for training and retraining workers in the skills required for the future job market. Employers have an opportunity to recruit from often overlooked populations, including older workers, those without college degrees, individuals with disabilities or employment gaps, and those who have been incarcerated. AI could also be utilised to find and hire candidates from these backgrounds.
