According to a new report, generative AI could account for up to 30 percent of the hours worked in the US economy by 2030.
The study by McKinsey Global Institute titled “Generative AI and the Future of Work in America” said that AI has the potential to greatly accelerate economic automation.
“By 2030, activities that account for up to 30 percent of hours currently worked across the US economy could be automated — a trend accelerated by generative AI,” it said.
The report asserted that generative AI will not eliminate a large number of jobs right away but would rather enhance the way STEM, creative and business as well as legal professionals work.
However, it added automation’s biggest effects are likely to hit other job categories such as office support, customer service and food service employment.
The McKinsey report said that in US alone, an additional 12 million occupational transitions may be needed by 2030.
How different occupations will be affected
The report said that largest future job gains are expected to be in the healthcare industry, estimaing that there could be demand for 3.5 million more jobs for health aides, health technicians and wellness workers.
It also estimated that there will be a 23 percent increase in the demand for STEM jobs by 2030.
“Although layoffs in the tech sector have been making headlines in 2023, this does not change the longer-term demand for tech talent among companies of all sizes and sectors as the economy continues to digitize,” it said.
The McKinsey report said that employers in banking, insurance, pharmaceuticals and healthcare sectors are undertaking major digital transformations and need tech workers with advanced skills. It added that the transportation services category is expected to see job growth of 9 percent by 2030.
On the other hand, the biggest future job losses are likely to occur in office support, customer service and food services.
The report estimated that demand for clerks in US could decrease by 1.6 million jobs, in addition to losses of 830,000 for retail salespersons, 710,000 for administrative assistants and 630,000 for cashiers.
The analysis said that jobs which involve a high share of repetitive tasks, data collection and elementary data processing will be impacted the most due to automation.
Low wage workers to be hit more
The report said that those working in low wage jobs in US (making less than $30,800 a year and those earning $30,800 to $38,200 a year) are up to 10 and 14 times more likely to need to change occupations by the end of this decade than the highest earners.
“As people leave shrinking occupations, the economy could reweight toward higher-wage jobs. Workers in lower-wage jobs are up to 14 times more likely to need to change occupations than those in highest-wage positions,” it said, adding that most of these workers will need additional skills to do so successfully.
The report also warned that women are 1.5 times more likely to need to move into new occupations than men.
“The jobs in the two lowest wage quintiles are disproportionately held today by those with less education, women, and people of color. Women are heavily represented in office support and customer service, which could shrink by about 3.7 million and 2.0 million jobs, respectively, by 2030,” it said.
’12 million occupational shifts’
The report said that there is no conclusion yet on the raging question about whether generative AI might wipe out jobs. However, it refused to rule out job losses in the short term.
“Technological advances often cause disruption, but historically, they eventually fuel economic and employment growth,” it said.
It said that the decline in food services, customer service and sales, office support, and production work could account for almost ten million (over 84%) of the 12 million occupational shifts expected by 2030.
“By contrast, occupations in business and legal professions, management, healthcare, transportation and STEM were resilient during the pandemic and are poised for continued growth. These categories are expected to see fewer than one million occupational shifts by 2030,” it said.