India's labour market appears to be entering a phase of quiet but consequential transition, with artificial intelligence beginning to reshape not only the nature of work but also the entry points into employment.
For decades, a predictable pathway underpinned middle-class mobility: formal education, followed by entry-level employment in sectors such as sales, IT services, or back-office operations. That pathway is now under pressure, as automation increasingly targets routine, process-driven work.
The resulting shift has prompted a broader question: whether India is witnessing a cyclical disruption, or a deeper structural change in its employment landscape.
Strains At Lower End Of Job Ladder
Concerns regarding job availability are particularly pronounced among younger cohorts.
India produces close to three million engineering graduates annually, yet employment absorption has not kept pace. The services sector, especially IT and business process outsourcing, which together employ over four million people and account for a significant share of GDP, has historically served as a key outlet for such graduates.
However, recent trends suggest a slowdown in hiring intensity. According to the India Employment Report 2024 by the International Labour Organization (ILO), young people constitute approximately 83% of the unemployed workforce, with educated youth increasingly finding it difficult to secure appropriate employment.
Saurabh Mukherjea, chief investment officer at Marcellus Investment Managers, argues that the underlying pressures are already visible. "AI will take jobs. Work that humans used to do will now be done by machines," he says, adding that the effects are being felt in the form of prolonged job searches and downward pressure on wages.
He notes that job loss is now accompanied by extended periods of unemployment, a departure from earlier patterns when re-employment was relatively quicker.
Automation or Reconfiguration?
At the same time, industry stakeholders caution against interpreting these developments as a straightforward contraction in employment.
"AI is not eliminating entry-level jobs; it is restructuring them," says Nipun Sharma, chief executive officer of TeamLease Degree Apprenticeship. "Roles that were historically built around repetitive processes are being automated, but new positions requiring higher-order skills are emerging."
This distinction has contributed to what some analysts describe as a "transition effect", wherein job creation continues but at a pace and in sectors that may not immediately absorb displaced workers.
Data from the World Bank indicate that overall employment growth in India has, in recent years, outpaced the expansion of the working-age population, with urban unemployment declining to 6.6%, the lowest level since 2017-18.
Yet, the same data also underscore persistent structural concerns, including high youth unemployment and a predominance of informal work.
Vulnerability of Entry-Level Roles
Entry-level occupations in sales and customer-facing functions are among those most exposed to automation.
These roles often involve standardised tasks, such as lead qualification, customer interaction, and transactional processing, that can be replicated by AI-enabled systems. Industry data suggest a gradual shift in hiring preferences towards roles requiring analytical, technological, or domain-specific expertise.
Mukherjea views this as part of a broader erosion of the conventional middle-class aspiration. "The idea that a graduate will move into a stable, white-collar job in IT services or similar sectors is no longer as secure as it once appeared," he argues.
Shift from Degrees to Skills
The transformation has implications for education and workforce preparation. "A fresher today needs to think in terms of skills, not degrees," DrSharma observes. He identifies digital literacy, problem-solving ability, adaptability, and familiarity with AI tools as increasingly essential competencies.
This shift is also reflected in evolving employer strategies. Apprenticeship and work-based learning models, once peripheral, are gaining prominence as firms seek to develop job-ready talent.
According to recent data from TeamLease:
- Eight in 10 employers are planning to increase apprenticeship hiring
- Apprenticeship opportunities have grown significantly in recent years, with sectors such as engineering, telecom, and e-commerce leading demand
The move towards such models reflects a broader alignment between education and industry requirements.
Emerging Sectors and Employment Reallocation
While traditional entry points may be narrowing, employment opportunities are expanding in other segments.
Sectors such as healthcare, financial services, manufacturing, and e-commerce continue to exhibit steady hiring demand. Additionally, emerging industries, electric vehicles, semiconductors, and drone technology, are generating new roles, although with different skill requirements.
Labour market data indicate a simultaneous structural shift. More than 55% of India's workforce is now self-employed, pointing to a gradual movement away from formal salaried employment towards more flexible, and often less secure, work arrangements.
Inequality Concerns
The ongoing transformation carries potential implications for inequality.
Mukherjea suggests that the new economy may be characterised by greater dispersion in incomes, with a small segment benefiting disproportionately from technological changes.
Sharma concurs that unequal access to skills and training could exacerbate disparities, but also notes that AI has the potential to widen access to opportunities if supported by inclusive skilling systems.
At present, however, the structure of employment remains uneven. The World Bank estimates that only 23% of non-farm jobs in India are formal, highlighting the limited reach of stable, salaried employment.
An Evolving Timeline
The pace of change is likely to be uneven but sustained. Sharma anticipates that the most immediate effects will be felt within the next two years, particularly in entry-level roles, while broader structural changes may unfold over a longer horizon.
Mukherjea emphasises the risks of inaction, suggesting that the challenge is not only the displacement of jobs but also the possibility of skills becoming obsolete.
Conclusion
India's labour market is not witnessing a uniform decline in employment, but rather a transition in its composition.
Artificial intelligence is accelerating this shift by altering the nature of work, reshaping employer expectations, and narrowing traditional avenues of entry into the workforce.
Whether this transition results in broader opportunity or heightened precarity may depend less on technology itself, and more on the capacity of institutions, educational, industrial, and policy, to adapt to the emerging realities of work.
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