NEW DELHI, October 21, 2026 — Artificial intelligence is not yet showing up as a straightforward decline in India’s overall employment, but it is changing how companies recruit—and making it harder for some young professionals to secure their first job.
The World Bank’s India Development Update – October 2026 examines how India can use AI to improve productivity and expand development opportunities. Separate industry evidence points to a more immediate challenge: companies are increasingly automating routine tasks that have traditionally helped fresh graduates enter the workforce.
An Indian Council for Research on International Economic Relations (ICRIER) survey of 651 IT firms found that 55% reported a decline in entry-level hiring. By comparison, 25% reported lower recruitment at the mid-career level and 14% at senior levels. The figures indicate that the pressure is concentrated more heavily at the beginning of the career ladder than among experienced workers.
The distinction matters. A slowdown in recruitment does not necessarily mean that companies are dismissing large numbers of existing employees. Instead, businesses may be adjusting their workforce by leaving positions unfilled, reducing campus placements or asking smaller teams to handle more work with AI tools.
Why Are Fresh Graduates Facing More Pressure?
Entry-level employees often begin with structured, repeatable tasks that help them learn how a business operates. In technology companies, these can include routine coding, software testing, documentation, data processing and basic support work.
AI systems can now perform or accelerate parts of many of these activities. Companies may therefore need fewer people to complete the same volume of routine work, particularly when they can integrate AI tools into existing workflows.
That does not mean every junior role will disappear. Employers still need people who can check AI-generated output, identify errors, understand business requirements, protect data and take responsibility for the final result. But graduates may increasingly be expected to demonstrate these capabilities earlier in their careers.
For job seekers, the challenge is becoming twofold: securing an opening and showing that they can contribute beyond tasks that software can automate easily.
Is India’s IT Sector Actually Shrinking?
The picture is more complicated than a simple story of industry-wide job losses.
According to the figures in the supplied report, India’s six largest IT services companies reduced their combined workforce by around 64,000 from a base of approximately 1.7 million employees. At the same time, the wider technology-services ecosystem—including Global Capability Centres (GCCs)—added roughly 700,000 jobs over three years, taking employment in the sector to about 4.4 million.
These figures suggest that workforce changes have been uneven. Some large IT services firms have reduced headcount, while other parts of the technology ecosystem have continued to expand.
GCCs, which handle functions such as software development, analytics, engineering, research and business operations for multinational companies, are an important part of this broader employment picture.
However, aggregate growth does not guarantee that new jobs will be available to the same people who lose opportunities elsewhere. New positions may require different technical skills, more experience or specialist knowledge.
AI Hiring Is Also Creating New Jobs
Nomura’s analysis of 69 AI-related employment announcements across Asia, covering the period from 2022 to August 2026, recorded approximately 131,000 AI-related hires and 61,000 job cuts or attrition cases.
India accounted for around 83,100 hires and 31,921 layoffs or attrition cases in the analysis. That represents a net difference of approximately 51,000 more recorded hires than job losses or attrition cases.
The figures offer evidence that AI-related hiring has so far exceeded documented job losses in India. But they should not be interpreted as a complete count of all employment changes across the country: the analysis is based on reported company announcements and selected cases, not a census of the entire labour market.
Nor does a positive net figure mean every worker benefits. Hiring and displacement can occur in different companies, occupations and locations. A worker whose routine support role disappears may not have the skills needed for a new position in AI engineering or data operations.
Nomura also found that many of the new positions were concentrated in technology-related work, including AI training and data annotation. The longer-term outlook for some of these roles remains uncertain as AI systems evolve.
Which Jobs Face Greater Exposure to AI?
The World Bank’s October update considers both the risks and the development opportunities associated with AI. Its broader message is that the technology’s impact depends on how businesses and public institutions adopt it, as well as whether workers can access the necessary skills and infrastructure.
The supplied figures indicate that about 22% of employment in India falls into a high AI-exposure category, compared with roughly 60% in advanced economies. The difference partly reflects India’s larger share of agricultural and manual work, where many tasks are harder to automate using software alone.
Within the reported 22% category, the figures distinguish between jobs where AI may substantially change work and those where it could primarily improve productivity. Financial and telecommunications services are examples of areas where work processes may change significantly. Healthcare and education also have opportunities to use AI to support professionals and improve service delivery.
Exposure does not automatically mean a job will be eliminated. AI can automate certain tasks while leaving other responsibilities in human hands. The outcome depends on the occupation, the tools being used and how employers redesign jobs.
AI Is Being Used Beyond Technology Companies
India’s AI transition is not limited to software development or corporate offices. Agriculture and healthcare offer examples of how targeted applications can support people working in sectors where access to information and specialist services can be limited.
Agriculture: Local-language advice for farmers
Platforms such as Kerala’s KATHIR and Maharashtra’s MahaVISTAAR AI are cited as examples of technology being used to deliver agricultural information. Depending on the service and its available features, AI-based tools can help farmers access guidance on crop management, pest control, weather conditions and market information in local languages.
These applications are intended to help farmers make better-informed decisions. Their effectiveness depends on the quality and timeliness of the underlying data, the local relevance of the advice and farmers’ ability to access and use the services.
Healthcare: Supporting diagnosis
AI-assisted medical imaging tools can help clinicians analyse chest X-rays and flag signs of disease. In settings with limited access to specialists, such tools may support earlier assessment and help healthcare workers prioritise patients.
They are not a substitute for clinical judgement. Performance varies by tool, disease and patient population, and claims about accuracy, cost or offline operation should be assessed against evidence for the specific system being used.
What Should Students and Job Seekers Do?
The shift in recruitment makes practical skills and the ability to use AI tools responsibly increasingly important. Students entering technology and other professional fields can strengthen their prospects by focusing on:
- AI literacy: Understand how AI tools work, where they can fail and how to verify their output.
- Strong fundamentals: Build skills in programming, mathematics, writing, data analysis or the core discipline relevant to the chosen career.
- Real projects: Demonstrate the ability to solve a problem, explain the process and evaluate the result—not merely produce an AI-generated answer.
- Human judgement: Develop communication, collaboration, domain knowledge and problem-solving skills that complement automated systems.
- Continuous learning: Be prepared to update skills as employers change their workflows and job requirements.
For employers and policymakers, the challenge is to make sure that automation does not close off the first steps of a career. Apprenticeships, structured graduate training, work-based learning and accessible reskilling programmes can help young workers gain the experience that entry-level jobs traditionally provided.
The Bottom Line
India’s AI jobs story is not simply about jobs disappearing or new jobs appearing. The evidence points to a more uneven transition: AI-related hiring is creating opportunities, while routine work and entry-level recruitment are under pressure in parts of the economy.
The immediate question is whether young workers can still find a first rung on the career ladder—and whether companies, educators and policymakers can help them develop the skills needed to climb it.
