iWorld
Viacom18 restructures its leadership team
MUMBAI: Viacom18 today announced changes in its leadership team to focus on scaling and bolstering its digital and broadcast businesses. As part of the rejig, Ferzad Palia will head all SVoD services (Voot Select & Voot Kids) and International expansion for Voot and will report to Viacom18 Digital Ventures COO Gourav Rakshit.
The network’s youth, music and English entertainment business will now be led by Anshul Ailawadi, erstwhile strategy and project management lead at the group CEO’s office. Anshul will be reporting to Network18 MD Rahul Joshi in his new role.
Palia has led the growth of the network’s youth, music and English entertainment business for the past 16 years. More recently he launched Voot Select that has already raced to add 1 million plus subscribers within a year. He will now look to cohesively grow Viacom18’s SVoD and International digital businesses. Ailawadi has played a key role in the growth of Viacom18 over the last six years and is a strong proponent of the tremendous fandom, and the potential business opportunity that the YME brands of Viacom18 command. In a young country like India, these brands have a long runway for growth, especially given the proliferation of digital platforms.
Viacom18 forayed into digital subscription businesses in late 2019 with Voot Kids that was closely followed by Voot Select launched in March 2020. Voot Select recently reported acquiring over 1mn subscribers in its first year and though being a late entrant in the category it’s the fastest growing broadcaster-backed OTT service. Youth, Music and English Entertainment portfolio of Viacom18 consists of category leading channels like MTV, MTV Beats, Vh1, Comedy Central and Colors Infinity.
eNews
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.
