Cubicle workers. Shipping clerks. Loan processors.
“All gone,” Forrester vice president and principal consultant Huard Smith said in describing the impact of artificial intelligence on various professions by 2030.
Smith’s list included a lot of repetitive, manual work that can be automated with machine-learning software. For instance, Forrester projects that 73% of all cubicle-related jobs—think clerical tasks like data entry—will be automated by 2030, equating to over 20 million jobs eliminated.
Location-based workers, which includes people who work as grocery store clerks, will also be severely impacted by A.I., Smith explained. About 38% of location-based jobs will be automated by 2030, eliminating about 29.9 million positions.
A.I.-powered job loss is already occurring in some job roles, he said, mentioning a grocery store that has eliminated five human jobs with the help of a robot that can scan products on shelves to track inventory. Only one human worker remains to restock the store.
If the next version of the inventory tracking robot can stock shelves, then the grocery store “won’t actually need anyone,” Smith said.
And if you think that learning to code will give you an edge in the future, think again. Smith said that even software developers are at risk, because “coding is going to be automated.”
“So if you got kids in coding schools, you might keep them there [temporarily], but don’t tell them to stay,” Smith told the audience at an A.I. conference in Santa Clara, Calif. last week. “Get them into A.I., because coding isn’t going to be a job in the future.”
Company executives typically downplay the impact of A.I. on jobs and insist that A.I. will create new ones. But A.I. will wipe out 29% of all U.S. jobs while creating the equivalent of only 13%, Forrester projects.
Smith’s frank talk wasn’t meant to be a total downer, but was instead intended to create a sense of urgency about A.I.’s effect on jobs. Speaking to Fortune after his talk, Smith explained that company management should be candid with employees about the impact of machine learning on their jobs and invest heavily in corporate training programs.
U.S. workers are increasingly worried about A.I.’s potential negative effects on their jobs, and company managers need to take their concerns seriously by helping them adapt to the fast-changing world.
“They will bolt if they feel that you are just cost cutting,“ Smith said, referring to companies that are adopting machine learning.
“It will be a difficult 10 years and beyond, and the world doesn’t just stop by 2030, so buckle up,” he warned.