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9 incentives that digital start-ups need: IAMAI
MUMBAI: To recognise Prime Minister Narendra Modi’s vision of ‘Digital India,’ the industry body Internet and Mobile Association of India (IAMAI) has come up with specific fiscal and non-fiscal measures that India’s Internet scene requires. According to the association, the digital start-up ecosystem in India should be systematically encouraged by focusing on specific fiscal interventions.
The suggestions are as follows:
1) Improve Investment Environment: India’s entrepreneurs need early stage venture capital, which is why the domestic venture capital sector needs to develop further. In the US, the VC industry took off when their government allowed the large pension funds to put 5-10 per cent of their assets into VC firms.
2) Angel Tax: Angel Tax under Sec 56 (2) of the Income Tax Act has not been tailored to restrict start-up funding but it has put start-ups under the the Income Tax scanner, questioning the valuation by domestic individual investors. The criteria to qualify as an angel fund are stringent and need to be eased to support the start-up ecosystem in the country. The association suggests that there should be tax breaks and incentives for individuals supporting start-ups with capital.
3) Incentivize Internet services start-ups: Internet services based start-ups form the bulk of internet companies in India. Comprising aggregators, digital advertisers and online classifieds, bring in a lot of efficiency, and are the largest employment generators. They are either enabling businesses, or they are creating lot of employment in the country, resulting in many people are earning a lot of money than they should otherwise have.
4) Service Tax: Start-ups end up paying a huge amount over the first three years in way of service tax. Survival then takes a back seat and penalties just make a struggling start-up’s life harder. The association recommends that for the first three years, the service tax could be waived off or incentivizes the start-ups, if they pay their service taxes on time.
5) Streamline taxation for e-commerce: Online marketplaces are changing the way businesses are done in India. Small players are setting up niche businesses in India and are attracting lot of investments in India. Online marketplaces bring in a lot of efficiency in the entire retail value chain from customer experience to payments and delivery.
6) Taxes on e-commerce transactions: The e-commerce marketplace industry is being subjected to onerous VAT demands from several states. They should be recognised as marketplaces and exempt from VAT demands in states. As market places they provide a service to online sellers and pay the service tax on that account. The State of Rajasthan for example treats e-commerce players as market places.
7) Boost FinTech Start-ups: FinTech plays a significant role in serving those underserved or not served by formal institutional mechanisms. They are also likely to play a significant role in various financial inclusion programmes of the government. Various forms of FinTech services such as pre-paid instruments, wallets and others create efficiency, transparency and wider reach in financial transaction.
8) P2P lending and crowd-funding need contribution from government: While some early inroads have been made in the P2P lending segment in the country, individual efforts have not translated into a policy from the government. The lack of clarity of rules and regulations has meant the industry is shooting in the dark. In the absence of dictated policy or scriptures, it is quite plausible that misguided individuals may fall prey to unscrupulous operators that may look to make a quick buck.
9) Easy KYC through Aadhar: This will allow innovators to build new services, which in turn will help bring more people under the ambit of financial services. Various forms of digital payments such as pre-paid instruments, wallets and others create efficiency, transparency and wider reach in financial transaction.
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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.
