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AI could replace half of entry-level white-collar work: Anthropic study
Hiring in AI-exposed occupations fell 14 per cent post-ChatGPT
SAN FRANCISCO: From lamplighters to elevator operators, waves of technology have repeatedly erased once-common jobs. Now artificial intelligence may be poised to do the same for large swathes of professional work.
A new study by Anthropic suggests that while AI tools are technically capable of performing many knowledge-economy tasks, real-world adoption lags far behind that potential, at least for now.
The report, Labor market impacts of AI: A new measure and early evidence, by Maxim Massenkoff and Peter McCrory, introduces a new metric called “observed exposure,” which compares what AI systems could theoretically perform with what they are actually doing in workplaces.
Using professional interaction data from Anthropic’s Claude model, the researchers found that AI could theoretically cover a wide share of tasks in business, finance, management, computing, mathematics, legal services and office administration. Yet current adoption represents only a small fraction of those capabilities.
That gap between potential and reality reflects a mix of legal barriers, technical limitations and the continued need for human oversight, the study said. But the authors suggest those constraints may prove temporary as the technology matures.
Warnings about AI’s impact on white-collar employment have been growing. CEO Dario Amodei has previously argued that AI could disrupt as much as half of entry-level professional work, while Microsoft AI CEO Mustafa Suleyman has suggested that most professional tasks could eventually be automated within 12 to 18 months.
Highly educated workers most exposed
Contrary to common assumptions, the study finds that workers most exposed to AI are not those in manual labour but highly educated professionals. The most exposed group is 16 percentage points more likely to be female, earns on average 47 per cent more than the least exposed group and is nearly four times as likely to hold a graduate degree.
Occupations including computer programmers, customer service representatives and data entry clerks are among the most vulnerable to automation.
Yet even in highly exposed fields, AI is not yet replacing jobs at scale. The researchers cite routine medical tasks, such as authorising prescription refills, as examples that AI could technically perform but is not widely observed doing in practice.
In the report’s visual framework, actual AI usage (the “red area”) remains far smaller than the theoretical “blue area” of possible tasks. Over time, the researchers expect the red area to expand as adoption deepens.
At the other end of the labour market, roughly 30 per cent of occupations show virtually no AI exposure. Roles such as cooks, mechanics, bartenders and dishwashers still depend heavily on physical presence and manual work that large language models cannot replicate.
Hiring slowdown rather than layoffs
So far the clearest labour-market signal is not mass layoffs but a slowdown in hiring within AI-exposed occupations.
According to the study, job-finding rates in those sectors have fallen about 14 per cent since the arrival of generative AI tools such as ChatGPT compared with 2022 levels. A separate study cited by the authors found a 16 per cent drop in employment among workers aged 22 to 25 in AI-exposed roles.
Recent labour data from the US Bureau of Labor Statistics also point to softer hiring conditions, with employers shedding 92,000 jobs in February and unemployment rising to 4.4 per cent.
Some companies have already linked layoffs to automation. Jack Dorsey said his payments firm Block recently cut nearly half its workforce in part because AI tools allow smaller teams to operate more efficiently.
Not everyone is convinced the technology is solely responsible. Critics such as Marc Benioff have accused some firms of “AI washing”, using automation as a convenient explanation for cost-cutting measures.
Still, the researchers warn that the longer-term risk is a potential “white-collar recession”. If unemployment in the most AI-exposed occupations were to double, from about 3 per cent to 6 per cent, it would mirror the scale of labour-market disruption seen during the Global Financial Crisis.
For now, the shift may simply mean fewer entry-level openings. Some young workers are staying longer in existing roles, switching sectors or returning to education rather than entering AI-exposed fields.
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Rapido launches zero-commission food delivery app Ownly in Bengaluru
New platform promises transparent pricing with no restaurant commissions.
MUMBAI: Rapido just served up a fresh order because when the food delivery menu gets too pricey, someone’s got to deliver honesty on a plate. Rapido has rolled out Ownly, its standalone zero-commission food delivery app, across Bengaluru, stepping into India’s fiercely competitive online food delivery space with a model built on price transparency and fairness.
Unlike conventional platforms that charge restaurants commissions and often lead to inflated menu prices or hidden mark-ups, Ownly levies only a straightforward delivery fee on consumers based on actual logistics costs. Restaurants can list everyday low prices without relying on deep discounts, giving them breathing room while keeping bills honest for users.
The launch is backed by a satirical courtroom-themed digital video commercial that takes aim at industry pain points hidden fees, misleading discounts and price manipulation before positioning Ownly as the transparent alternative. The film is live on Ownly’s Youtube channel.
Rapido and Ownly, founder Aravind Sanka said, “Food ordering has become an integral part of everyday life across India, not just in metros but in Tier 2 and Tier 3 cities as well. At Ownly, we see a strong opportunity to build a restaurant-first model that supports partners and caters to the evolving needs of customers. Transparency, honesty and fairness are key drivers of long-term growth for the sector.”
The Bengaluru rollout follows a pilot in Koramangala, HSR Layout and BTM Layout, where the team conducted consumer research and collaborated closely with restaurant partners to fine-tune the offering.
Ownly leverages Rapido’s existing hyperlocal logistics network to scale operations efficiently. By eliminating commissions and focusing on real-cost delivery fees, the platform aims to foster fairer economics for restaurants and more predictable pricing for consumers.
In a market where every rupee on the bill feels like a negotiation, Ownly isn’t just delivering food,it’s delivering a promise: no sneaky surcharges, no inflated prices, just straightforward bites at honest rates.
