A viral note from a small research firm, Citrini Research, rattled the US information technology (IT) stocks when it warned that artificial intelligence (AI) could lead to “ghost GDP”.
The firm laid out a scenario in which AI replaces all white-collar workers, boosting output and profits, but, at the same time, collapsing demand as displaced workers lose income. At the other extreme are the views that AI will create entirely new categories of jobs yet to be imagined.
Between these poles lies a more optimistic reality of job re-allocation. History offers some guidance on technological job displacement, but this wave is different: AI is automating cognitive tasks at an unprecedented speed. For India, the stakes are higher given its dependence on and global outsourcing.
Task takeover
How far have AI’s capabilities advanced to significantly affect employability across professions?
A recent study by , based on real-world usage of its Claude model, maps the share of tasks within occupations that large-language models (LLMs) can currently perform. Exposure is highest in digital and information-processing roles. Computer programmers top the list, with about 75% of tasks covered, followed by customer service representatives at around 70% and data entry keyers at about 67%.
Other highly exposed roles include medical record specialists, market research analysts, and sales representatives. Even technical roles, such as financial analysts and software testers, show exposure above 50%.
However, even in the most affected occupations, this exposure has not yet translated into job losses, the study finds based on survey data from the US, although there is tentative evidence that hiring has slowed slightly for younger workers aged 22 to 25.
The research underscores that most occupations consist of a bundle of tasks, many of which require judgment, context, accountability, and human interaction, areas where AI still struggles. Even in highly exposed roles, AI is more often used to assist rather than replace workers.
Labour myth
The limited translation of task exposure into job losses, as Anthropic finds, reflects what economists call the “lump of labour fallacy”, the mistaken belief that there is a fixed amount of work in an economy and that automation simply replaces workers one-for-one.
In reality, labour markets evolve as technology raises productivity and creates new demand for goods, services, and entirely new occupations. The World Economic Forum estimates that while about 92 million jobs are expected to disappear globally between 2025 and 2030, around 170 million new roles will be created, resulting in a net gain of 78 million jobs.
Much of this expansion will come from sectors linked to basic services, infrastructure, and the care economy. Farmworkers, labourers, and other agricultural workers alone are expected to add nearly 35 million jobs, accounting for roughly 45% of the total net job growth.
Other major contributors include delivery drivers, software and applications developers, construction trades workers, and shop salespersons. At the same time, routine clerical and administrative roles are expected to shrink sharply. The shift suggests that technological change is likely to reconfigure the composition of work rather than eliminate it altogether.
Rising roles
Even as sectors such as agriculture and logistics are expected to see the largest increase in the absolute number of jobs, the fastest growth during 2025-30 will occur in technology and data-driven occupations, estimates the World Economic Forum.
Roles such as big data specialists, fintech engineers, and AI and machine learning specialists will expand the most rapidly as firms increasingly rely on data analytics, automation, and digital platforms to drive productivity and innovation.
The continued digitalization of finance, commerce, and public services will also boost demand for data analysts, and data warehousing specialists, who will be needed to build and manage large-scale digital systems. At the same time, rising cyber risks and the growing dependence on digital infrastructure will drive demand for information security analysts and security management specialists.
The transition towards electric mobility and connected devices is expected to support growth in autonomous and EV specialists and IoT professionals, while the global push towards climate goals will create new opportunities for environmental and renewable energy engineers. Even outside the technology sector, structural shifts in consumption patterns will be visible, with delivery drivers likely to remain among the fastest-growing roles as e-commerce continues to expand.
AI asymmetry
While global employment is projected to rise over the next five years, the impact of AI on jobs is likely to vary sharply across countries. An International Monetary Fund (IMF) study estimates that about 40% of workers worldwide are in high-exposure occupations, but this share rises to nearly 60% in advanced economies, compared with 40% in emerging markets and 26% in low-income countries.
Country-level differences are equally stark. Nearly 70% of employment in the UK and 60% in the US falls in high-exposure roles, whereas exposure ranges from about 41% in Brazil to 26% in India. These differences reflect underlying employment structures. Advanced economies have a higher concentration of professional, managerial, and clerical roles, which are more exposed to AI, while countries such as India have a larger share of workers in agriculture, crafts, and elementary occupations with lower exposure.
As a result, advanced economies may face faster and more pronounced labour market adjustments, including both displacement risks and new opportunities. Meanwhile, emerging and developing economies may experience a slower transition, but could still benefit through productivity gains, especially in sectors such as healthcare and education.
India’s IT dilemma
Although India’s overall exposure to AI remains relatively low, its IT sector appears particularly vulnerable. For decades, the industry’s growth has rested on a simple value proposition: delivering high-quality services at significantly lower cost than global peers.
However, if the marginal cost of AI coding agents approaches that of electricity, as suggested by Citrini Research, this advantage could erode, posing a structural challenge to Indian IT firms.
India’s policy think tank, NITI Aayog, notes that the sector’s trajectory will depend on the balance between emerging headwinds and tailwinds. On one hand, AI-driven productivity gains may reduce labour demand, while competition from onshore AI-native firms and broader could weigh on growth. On the other hand, significant opportunities are emerging, driven by new technology use cases, expanding global capability centres, and rising demand for advanced digital and AI skills.
NITI Aayog’s estimates suggest India’s tech workforce, currently around 7.5-8 million, could shrink to about 6 million or grow to 10 million by 2031, depending on how these forces evolve. Early signals of restructuring are already visible, with slower hiring and reduced campus intake alongside rising demand for AI, cloud, and data skills.
Puneet Kumar Arora is an assistant professor of economics at Delhi Technological University. Jaydeep Mukherjee is a professor of economics at Great Lakes Institute of Management, Chennai.