Generative AI is likely to become a much greater threat for white-collar roles, such as accounting and book-keeping, rather than blue-collar jobs, a report said on Monday.
Many administrative roles involve repetitive tasks such as scheduling appointments or answering and directing calls, which can easily be replicated by generative AI, according to global learning company Pearson's Skills Outlook report -- 'Gen AI Proof Jobs'.
The report cited that in India around 30 per cent or more time spent on some white-collar tasks every week can be performed by generative AI.
However, generative AI can do less than 1 per cent of a blue collar workers' job in a week, it said.
"As employees look to the future, understanding which jobs are at risk from AI allows them to prepare. They should also consider where new roles might be created by Gen AI," Pearson Workforce Skills President Mike Howells said.
"Workers and employers should look at how they can ride this wave of change by using the best of AI and the best of human skills together," he said.
Pearson's Skills Outlook series looks at 'Gen AI Proof Jobs', based on an analysis of impact of generative AI on more than 5,000 jobs in five countries -- Australia, Brazil, India, the US, and the UK.
As per the report, in India, the most impacted white-collar jobs are accounting and book-keeping clerks (46 per cent), word processor and related operators (40 per cent), administrative secretaries and related associate professionals (38 per cent), stall and market salespersons (30 per cent), and accountants (28 per cent).
In the blue-collar job categories, weavers, knitters and related roles will be impacted 17 per cent, basketry weavers, brush makers and related work by 17 per cent, weaving and knitting machine operators by 16 per cent, waiters and bartenders by 15 per cent and bakers, pastry and confectionery makers by 15 per cent, it added.
(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)
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