Artificial Intelligence: Which jobs are going to be replaced by AI? Which age group will be exposed the most? Here's what experts say

AI or artificial intelligence is witnessing exponential growth even as there are apprehensions about the impact of the latest technology especially on jobs and employment. However, as the AI race heats up between giant corporations, and leading economies around the world, it is likely that AI will be the dominating force in coming times.

There are several experts and researchers have raised one question and that is -- what will be social cost of the rapid progress of AI.

AI Impact on Jobs


Anthropic's economics team modeled a range of scenarios for how much extra growth AI would deliver at an annual rate in 2030. Assuming a baseline of 2 per cent in a non-AI environment, it suggested growth of 2.4 per cent in a scenario with modest AI impact, 5.4 per cent in a substantial scenario and 15.4 per cent in an extreme scenario.

Higher growth would mean more jobs lost, it said, without assigning probabilities for any of the outcomes.

Amodei forecast last year that AI could wipe out half of all entry-level white-collar jobs within five years. For now, however, some researchers say it appears to have been limited to making it harder for those seeking office work to find a job.

Studies in the US and Britain have pointed to a slowdown in early career hiring for white-collar positions performing tasks at which AI is adept, even if overall employment remains strong.

Researchers at Stanford University said in August that employment of workers aged 22 to 25 in AI-exposed industries, such as accountants and paralegals, was 19 per cent lower than for jobs that AI found hard to replicate, like janitors and builders.

Future of AI

Yet even if the promised transformation takes longer than numbers surrounding AI companies imply, real economic benefits should stay - just as trains still ran after the Panic of 1873 that bankrupted railroad barons, while the internet didn't shut down after the 1990s dotcom bubble burst.

Recursive self-improvement, while potentially delivering exponential AI advances, has also raised concerns about existential risks to humanity. Yet the pace of change in productivity might still end up lagging the timelines needed by corporate accounts departments.

Diane Coyle, an economist at Britain's Cambridge University, said the productivity impact of past revolutionary technologies had usually taken about 10 to 50 years to feed through.

"History is our friend in trying to understand this," said Coyle. "As long as one is left with the infrastructure that's needed to support all the productivity effects down the road, that's okay." ​

Funding into Artificial Intelligence

Never has so much cash flowed into a new technology as is pouring into AI, eclipsing the sums splurged on railways or the internet when those technological revolutions sucked in capital.

Cumulative spending globally on data centers alone could top $30 trillion by 2050, according to a projection by PwC, almost matching the value of outstanding US Treasuries. It "dwarfs" what was spent in the railroad or dotcom booms, even after adjusting for inflation, PwC said.

Meanwhile, Anthropic, just one of the major firms in the AI race, plans to spend $518 billion in coming years, according to the IPO prospectus seen by Reuters, which is more than 100 times its 2025 revenue. Its backers say AI technology will be more transformational than the advent of steam engines and the industrialization they powered.

Yet lurking behind the dizzying projections and huge outlays by AI companies, alongside sky-high valuations, lie assumptions about vast broad-based productivity gains and future profits with little evidence so far - or historical precedent - to be sure they can deliver, economists say.

JP Morgan wrote in August that broad-based productivity gains in the US, which leads the AI race, "remain elusive", raising questions about the sustainability of AI valuations.

A Bain & Company study said productivity gains from existing markets would not be enough to justify current outlays and "entirely new markets must emerge to close the funding gap", suggesting those could range from using AI-guided robots to developing new materials for batteries and semiconductors.

US hyperscalers - the companies rolling out infrastructure around the world like Google, Amazon and Microsoft - and others in the AI race needed to find more than $4.2 trillion of new revenue in the next five years to fund the buildout, Bain said.