Nvidia CEO Jensen Huang: AI data center buildout could create 1 million jobs and reshape the US economy

Nvidia (NVDA) CEO Jensen Huang, sitting on a panel next to SpaceX (SPCX) and Tesla (TSLA) CEO Elon Musk as corporate AI leaders spent most of the day at the White House, said the AI data center buildout will create “probably about a million jobs.”

Huang added that “this is the first time in probably… 50 years [that] we’re re-industrializing the United States, creating a whole bunch of blue collar jobs.”

As Yahoo Finance’s Brian Sozzi details, the Alliance for America’s Skilled Trades (AAST) — an initiative launched by BlackRock (BLK), Carhartt, Ford (F), and Google (GOOG) — estimates that the US will need to fill 1.7 million skilled trades job openings annually through 2035.

Nvidia, Meta (META), and Microsoft (MSFT) are joining AAST this week.

Read more: AI in America has a huge 1.7 million job shortage problem

AAST defines skilled trade jobs as the 124 occupations — including carpenters, electricians, mechanics of various kinds, plumbers, and pipe fitters — that “build, install, operate, maintain, repair, fabricate, or extract the physical materials, products, equipment, systems, and infrastructure the U.S. economy relies on.”

Current training programs produce just 55 workers for every 100 needed, according to a new AAST report.

Huang explained that the US is adding “somewhere between 10, 20 gigawatts a year” of the infrastructure and said the work reaches well beyond the data centers themselves.

“Don’t forget you got to build a power generation plants, ” the AI hardware giant’s chief executive said, adding: “You’ve got construction, you’ve got power cooling, you’ve got pipe fitters.”

Musk noted that “you’ve got to scale energy, you’ve got to scale chip production,” adding that China “has about three times the electricity production of the United States.”

All in all, according to Huang, “this is our great chance of reshaping our economy and bringing that type of builders and craft back into the United States.”

Internal AI tools helped us analyze transcripts. Humans wrote and edited this post.