Generative A.I. will upend the workforce, McKinsey says, forcing 12 million job switches and automating away 30% of hours worked in the U.S. economy by 2030
Discussions of A.I. in the workforce oscillate between alarm bells of mass unemployment and fantasies of a future utopia where everyone is free to pursue their passions instead of grinding out a career. While the particulars of how generative A.I. will transform the workforce may be debatable, experts and workers alike believe that change is inevitable.
A comprehensive new report from consulting giant McKinsey tries to quantify these impending changes by examining how the mix of jobs might change over time. Crucially, McKinsey’s research reaches a point of view that has been uncommon so far in the discourse—that A.I. will not wipe out jobs in the long term. Even though the research in question “cannot definitively rule out job losses, at least in the short term.” The sectors most exposed to generative A.I. could still add jobs through 2030 but at a slower pace than previously anticipated, the report concludes.
Instead, A.I. will either change the way certain jobs are done or create an opportunity for employees in lower-paying jobs to move into high-paying positions, provided they receive adequate training. McKinsey’s report estimates 12 million people will switch careers by 2030, 25% more than it projected just two years ago. Workers will change careers owing to a variety of factors. Though some may see their jobs disappear, others will gravitate toward higher paying fields, or ones where their skills are in greater demand.
For example, health care, which, according to McKinsey, already has an estimated 1.9 million job openings as of April, will add roughly 5.5 million new jobs through 2030. There will also be a 23% increase in demand for STEM jobs, as companies outside the tech industry continue to integrate A.I. into their day-to-day operations. Generative A.I.’s relative competency at performing administrative tasks means demand for jobs like office support and customer service will decline 18% and 13%, respectively, through 2030. Food service can also expect a decline in demand, although at a much lower level of 2% over the same time frame. The reduced job demand in office support roles will disproportionately affect women, while reduced demand in customer service and food service poses outsize risks to Black and Hispanic employees.
The challenge, then, is not so much mitigating these declines as it is ensuring that workers are properly trained for new roles. McKinsey advises starting training as early as high school for STEM fields. It also advises companies to head off eventual hiring challenges by expanding their applicant pools to include unemployed people and those without higher education.
For those who remain in their current jobs, the nature of their work will change dramatically as 30% of their work hours will be automated away by generative A.I. “It is important to note that automation adoption is not the same as eliminating jobs,” the report says. “Many jobs with some automatable tasks will remain, but the day-to-day nature of what people do and how they do it changes.”
McKinsey estimates that without generative A.I. current technologies could automate roughly 22% of work hours among U.S. employees. The increase to 30% can be attributed to ChatGPT, Bard, DALL-E, and other tools’ ability to perform tasks that require genuine expertise, even creativity that previous technologies couldn’t achieve. This would make generative A.I. one of the first technologies to eliminate knowledge work as well as lower paying jobs. For example, lawyers will no longer have to review contract laws, because natural language models could do it for them. (The legal A.I. startup Casetext sold to Thomson Reuters for $650 million in June.) Or graphic designers, who usually have a fine arts degree in addition to at least some natural talent, might find that Midjourney and DALL-E can reduce the number of drafts needed for an illustration.
McKinsey’s anticipated 12 million worker reshuffle presents opportunities for some to graduate into higher paying jobs. McKinsey’s analysis calculates losses of 1.1 million jobs paying $38,200 or less, with a 3.8 million increase in those offering salaries of $68,700 a year. That’s not to say the lowest paid workers won’t be heavily affected. People in the bottom 40% of wage brackets in the U.S., those who earn $38,200 or less, are up to 14 times as likely to need to change jobs. Although the paper makes a chilling admission that some of the lowest paying jobs in the country may be unaffected because it’s cheaper for companies to pay extremely low wages than it is to install an A.I. system to do those jobs—a statistic that gives credence to concerns A.I. would widen existing income inequality.
