The US labor market is posting healthy numbers — for now. Yet Americans’ economic prospects vary significantly, depending on who they are and where they live, and these differences will sharpen as the pace of automation picks up in the decade ahead.

For starters, some of the US economy’s largest occupational categories — food service, office support, manufacturing production, and retail and customer service — are highly exposed to labor-saving automation. Moreover, new research from the McKinsey Global Institute (MGI) finds that job displacement within these sectors is likely to be heavily concentrated among specific demographic groups.

Educational attainment emerges as the most critical factor determining the probability of automation-related job loss. Individuals with a high-school diploma or less are four times as likely to be in a role highly likely to be automated than are individuals with a bachelor’s degree or higher.

People with no postsecondary education account for more than three-quarters of the overall displacement that could occur by 2030, based on a mid-point scenario of the pace of automation.

College and advanced degree holders are not immune from automation, particularly as artificial-intelligence systems grow more sophisticated. But individuals who have achieved this level of education will enjoy greater job security relative to people with no postsecondary training. And if they do have to change jobs, they will have a wider range of opportunities.

Large and persistent variations in educational attainment between racial and ethnic groups will be evident in future job-displacement trends.

For example, just 75 percent of Hispanic workers have at least a high-school diploma, compared to 90 percent of white, African-American, and Asian-American workers. Hispanic workers are also overrepresented in food-service jobs, and thus have the highest rate of potential displacement among all minority groups in MGI’s modeling. All told, more than one in four Hispanic workers — almost 7.5 million individuals — could be displaced.

By contrast, Asian-American workers, about 60 percent of whom have a bachelor’s degree or higher (compared to 40 percent for whites, 30 percent for African-Americans, and 20 percent for Hispanics), are the least susceptible to job dislocation by automation.

Nonetheless, more than one in five Asian-American workers are currently employed in roles highly likely to be automated.

Automation will also affect workers differently across age brackets. Some 11.5 million US workers over the age of 50 could be displaced.

While some are close to retirement, others have years to go before they qualify for Social Security.

Moreover, automation will have uneven effects across genders. Men, for example, make up the majority of drivers and assembly-line workers — two roles highly likely to be automated — while women represent a majority of highly likely to be automated administrative assistant and bookkeeper positions.

In MGI’s projection, women will account for 47 percent of displaced workers and men for 53 percent by 2030. But women also stand to capture an outsize share of net job growth, owing to their larger representation in health professions and personal care work. Many of these roles, however, are low-paying, which raises questions about whether the gender wage gap will close or widen.

Based on current trends, it is likely that women will continue to face barriers to accessing high-wage, high-skill jobs in the tech sector, which is expected to grow as a result of automation.

Today, women account for about 47 percent of the labor force in the United States, but hold only 20-25 percent of tech jobs. Increasing the share of women receiving a STEM education (science, technology, engineering, and math) and removing gender inequities in access to tech jobs will be essential for reducing women’s vulnerability to automation.