AI unlikely to trigger mass layoffs; reskilling to open new opportunities

AI pioneer Andrew Ng said artificial intelligence is unlikely to cause mass job losses and will instead create new opportunities for workers who reskill.
He urged students and professionals to acquire new skills rather than fear machine-driven job losses. Ng made the remarks at the NDTV World Summit.
He called on education providers and training programmes to prepare people for the changing nature of work instead of focusing solely on skills that employers demand today.
Ng said current AI systems cannot yet eliminate the vast majority of jobs. He added that AI often boosts worker productivity, helping businesses expand and hire more people. “There will be hope and it’s not nearly as bad as the hype says it will,” he said.
He accused many businesses of exaggerating the threat of AI-driven job losses to inflate their perceived potential or attract public relations attention. He also cited recent data suggesting that AI creates more jobs than it destroys.
Ng pointed to software engineering as an example of how AI can reshape employment rather than reduce it. “Certainly, in the United States, the number of software engineer job postings is up because when we make software engineers much more productive, we want to hire a lot more of them,” he said.
He expects similar trends across other sectors as businesses adopt AI tools more widely.
“We’re readying them not for the jobs of 2026 or even, heaven forbid, the jobs of 2024, but for the jobs of 2028 and beyond. So that’s the challenge ahead of us,” he said.
However, a recent paper by MIT Institute Professor and economist Daron Acemoglu warned that the current direction of AI development could deepen inequality and increase job losses unless the industry prioritises tools that complement workers.
Acemoglu argued that policymakers and industry leaders should shift the AI debate away from artificial general intelligence (AGI) and speculative fears towards practical policies that encourage the development of “pro-worker” AI systems.
