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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.
eNews
How short, addictive story videos quietly colonised the Indian smartphone
A landmark Meta-Ormax study of 2,000 viewers reveals a format that is growing fast, paying slowly and consumed almost entirely in secret
MUMBAI: India has a new entertainment habit, and it arrived without anyone really noticing. Micro dramas, those short, cliffhanger-driven episodic stories built for the smartphone screen, have quietly embedded themselves into the daily routines of millions of Indians, discovered not by design but by algorithmic accident, watched not in living rooms but in bedrooms, on commutes and in the five minutes before sleep.
That, in essence, is the finding of a sweeping new audience study released by Meta and media insights firm Ormax Media at Meta’s inaugural Marketing Summit: Micro-Drama Edition. Titled “Micro Dramas: The India Story” and based on 2,000 personal interviews and 50 depth interviews conducted between November 2025 and January 2026 across 14 states, it is the most comprehensive study of the category in India to date, and its findings are striking.
Sixty-five per cent of viewers discovered micro dramas within the last year. Of those, 89 per cent stumbled upon the format through social media feeds, primarily Instagram and Facebook, without ever searching for it. The algorithm did the heavy lifting. Discovery, as the report puts it bluntly, is algorithm-led, not intent-led.
The typical viewer journey begins with accidental exposure while scrolling, moves through a cliffhanger-driven incompletion hook that makes stopping feel unfinished, and is reinforced by algorithmic repetition until habitual consumption sets in. Only then, when a platform asks for an app download or a payment, does the viewer pause. Trust, not content quality, determines what happens next, and many simply return to the free feed rather than pay. It is a funnel with a wide mouth and a narrow neck.
The numbers on consumption tell their own story. Viewers spend a median of 3.5 hours per week watching micro dramas, spread across seven to eight sessions of roughly 30 minutes each, peaking sharply between 8pm and midnight. Daytime viewing is snackable and low-commitment, squeezed into morning commutes, work breaks and coffee pauses. Night-time is where the format truly lives: private, uninterrupted and, for many viewers, socially invisible. Ninety per cent watch alone, compared to just 43 per cent for long-form OTT content. Half the audience watches during their commute, well above the 37 per cent figure for streaming platforms, a direct reflection of the format’s low time investment advantage.
The audience itself breaks into three segments. Incidental viewers, comprising 39 per cent of the total, are passive consumers who stumble in and rarely seek content actively. Intent-building viewers, the largest group at 43 per cent, are beginning to form habits and seek out episodes but remain cautious. High-intent viewers, just 18 per cent, are the ones who download apps, tolerate ads and occasionally pay: skewing male, younger and urban.
What audiences want from the content is revealing. The top three genres are romance at 72 per cent, family drama at 64 per cent and comedy at 63 per cent, precisely the same top three as Hindi general entertainment television. The format rewards emotional familiarity over complexity. Romance in particular thrives because it demands low cognitive investment, needs no elaborate world-building and plays naturally into the private, pre-sleep viewing window where inhibitions lower and emotional intimacy feels safe.
The most-recalled shows, led by Kuku TV titles such as The Lady Boss Returns, The Billionaire Husband and Kiss My Luck, share a common narrative DNA: rich-poor conflict, hidden identities, power imbalances, melodrama and cliffhangers that make stopping feel physically uncomfortable. Predictability, the research warns, is fatal. Each episode must re-earn attention from scratch.
The terminology question is telling. Despite the industry’s embrace of the phrase “micro drama,” viewers have not adopted it. They call the content “short story videos,” “short dramas,” “reels with stories” or simply “serials.” One respondent from Chennai said bluntly that “micro sounds like a scientific word.” The category is at the stage that OTT occupied in 2019 and podcasts in the same year: widely consumed, poorly named and not yet crystallised in the public imagination.
Platform awareness remains alarmingly thin. Only three platforms, Kuku TV at 78 per cent, Story TV at 46 per cent and Quick TV at 28 per cent, have crossed the 20 per cent awareness threshold. The rest languish in single digits. This creates a trust deficit that directly throttles monetisation: viewers who cannot remember which app they used are hardly primed to enter their payment details.
Yet the appetite is clearly there. Sixty-five per cent of viewers watch only Indian content, drawn by the TV-serial familiarity of the storytelling, the comfort of Hindi as a shared language and the sight of actors they half-recognise from decades of television. South languages are rising fast: Tamil, Telugu and Kannada together account for 24 per cent of first-choice viewing. And AI-generated content, still a novelty, has landed better than expected: 47 per cent of viewers call it creative and unique, with only 6 per cent actively rejecting it.
Shweta Bajpai, director, media and entertainment (India) at Meta, called micro drama “a category that is rewriting the rules of Indian entertainment,” adding that the discovery engine being social distinguishes this wave from previous content formats. Shailesh Kapoor, founder and chief executive of Ormax Media, was characteristically measured: the format, he said, is showing “the early signs of becoming a distinct content category” and, given how closely it aligns with natural mobile behaviour, “has the potential to scale very quickly.”
The format’s fundamental mechanics are working. It enters lives quietly, through boredom and a scrolling thumb, and burrows in through incompletion and habit. The challenge now is monetisation: converting a category of highly engaged but deeply anonymous viewers into paying customers who trust the platform enough to hand over their UPI credentials. The story, as any micro-drama writer knows, is only as good as the next cliffhanger. India’s platforms had better have one ready.
