New Delhi: Artificial intelligence is creating more jobs than it is eliminating in India, according to a recent report by Nomura, offering some relief amid growing concerns that rapid AI adoption could trigger widespread job losses. India recorded 83,100 AI-related hires, compared with 31,921 layoffs and attrition linked to AI, meaning roughly 2.6 jobs were created for every job lost or affected by the technology.
The numbers, reported by India Today based on a Nomura report first accessed by Bloomberg News, suggest that the immediate employment impact of AI in India may be more complicated than the widely discussed narrative of automation replacing human workers.
However, there is an important catch.
The jobs being created by AI are often not the same jobs that are disappearing. While companies are recruiting workers with specialised AI, technology and business skills, some routine positions are being reduced or replaced by automation. This creates a gap between the skills of workers losing jobs and those required for newly created roles.
The development could have significant implications for India’s large technology-services industry and its millions of young workers entering the labour market every year.
India emerges as a key test case for AI
Nomura economists Sonal Varma and Si Ying Toh examined 69 employment-related cases across Asia, covering the period from 2022 to August 2026. India recorded the largest absolute impact from AI-related hiring and job losses among the countries studied.
The economists describe India as a particularly important market for understanding AI’s effect on employment because of its huge workforce and its dependence on technology services and business-process outsourcing.
For decades, India’s global services advantage has been built partly around its large pool of educated workers. Indian companies have employed millions of people in areas such as customer support, software services, data processing, testing and other business functions.
AI is now changing the economics of several of these activities.
Tasks that once required large teams can increasingly be handled, assisted or automated by AI-powered systems. At the same time, businesses need workers capable of developing, implementing, supervising and improving those systems.
This explains why both hiring and job displacement can happen simultaneously.
AI-related hiring is outpacing job losses
The headline numbers provide a positive signal.
India recorded 83,100 AI-related hires against 31,921 layoffs and attrition linked to AI, according to the Nomura analysis. That works out to approximately 2.6 AI-related hires for every job lost or affected.
At first glance, this suggests that AI adoption could become a net employment creator rather than a net destroyer.
However, the figures should not be interpreted as proof that every worker affected by AI will find a new role.
The report is based on 69 reported employment cases across Asia rather than a comprehensive survey of every company and employee. Therefore, the figures are better understood as evidence of an emerging trend rather than a complete measurement of AI’s total effect on India’s labour market.
That distinction is particularly important when discussing employment because job creation at one skill level does not necessarily compensate for job losses at another.
The jobs being created are different
The biggest challenge is the mismatch between disappearing jobs and emerging roles.
Nomura’s analysis found that several job-loss cases in India involved support teams being replaced or reduced because of chatbots and other AI systems. At the same time, many of the hiring cases involved IT-services graduates being recruited because of growing demand associated with AI.
This creates a structural problem.
A worker who loses a routine customer-support position cannot automatically move into an AI engineering job. The latter may require programming expertise, knowledge of machine learning, data skills, cloud technologies or experience in deploying AI systems.
Even when a worker is willing to retrain, the transition can take considerable time.
This means the overall employment numbers can look healthy while individual workers and particular sectors experience significant disruption.
Entry-level workers could face the biggest challenge
One of the most important concerns raised by the report is the impact on entry-level employment.
For many graduates, the first job is a stepping stone. A young employee may enter a company through a basic role, acquire workplace experience and gradually move into more specialised responsibilities.
AI could disrupt this traditional progression.
If companies automate some basic tasks, they may need fewer entry-level employees. At the same time, they may increase recruitment for workers who already possess specialised AI or technical skills.
That could make it harder for fresh graduates to get the experience needed to qualify for higher-level positions.
The issue is particularly important for India because of the country’s large young workforce and the millions of people seeking employment opportunities each year.
A two-tier labour market could emerge
The Nomura analysis points towards a potential two-tier labour market.
On one side are experienced workers who understand both AI tools and the business processes in which those tools are used. Demand for such employees could increase as companies expand their use of artificial intelligence.
On the other side are workers seeking entry-level positions involving routine or repetitive tasks. These roles could come under greater pressure as businesses automate more processes. (India Today)
This divide could become one of the most important employment consequences of AI adoption.
It also means that simply increasing the number of AI jobs may not be enough.
India would need pathways that help workers move from vulnerable occupations into emerging roles.
IT services could see both opportunities and disruption
India’s technology-services sector is particularly exposed to AI because many of its traditional activities involve repetitive digital tasks.
AI can potentially increase productivity by automating routine coding, testing, customer service, data processing and administrative functions.
For companies, this can reduce costs and allow employees to focus on more complex activities.
However, the same productivity gains can reduce the number of people required to perform certain tasks.
This creates a difficult balance for India’s IT industry.
Companies may hire more AI specialists while reducing headcount in some traditional functions. The result could be a workforce that is smaller in some areas but more specialised overall.
Business-process outsourcing faces similar pressure
The business-process outsourcing sector is another area where the impact could be significant.
India has built a major global industry around services such as customer support and back-office operations. Many of these activities involve structured and repetitive tasks, making them suitable for AI-assisted automation.
Nomura’s findings suggest that support teams are already among the areas affected by AI-related job reductions.
However, BPO companies could also create new roles around AI implementation, quality control, data management and human oversight.
The industry may therefore evolve rather than simply disappear.
The challenge will be ensuring that workers can make the transition from routine service roles to these newer positions.
India’s AI opportunity remains significant
Despite the risks, the employment data also highlights a major opportunity.
India already has a large technology workforce and a strong base of engineering and computer-science talent. The country’s IT-services industry has extensive experience working with international businesses.
If companies invest in training and reskilling, this workforce could benefit significantly from the expansion of AI.
The creation of 83,100 AI-related jobs in the Nomura sample indicates that businesses are already hiring for roles connected to the technology.
The long-term opportunity could extend beyond conventional AI engineering.
Companies may need employees who understand AI applications in finance, healthcare, manufacturing, retail, logistics, marketing, education and other sectors.
This could create demand for workers who combine domain expertise with AI capabilities.
Reskilling could become essential
The shift makes reskilling increasingly important.
Workers whose roles are exposed to automation may need training in AI tools, data analysis, digital systems or specialised business functions.
For employers, internal training could become a way to retain experienced workers while preparing them for changing responsibilities.
For educational institutions, the development could mean greater emphasis on practical AI skills rather than purely theoretical qualifications.
The ability to work effectively alongside AI may become as important as traditional technical knowledge in many professions.
AI skills may become a baseline requirement
As AI becomes embedded in workplaces, employers may increasingly expect employees across different functions to understand how to use AI tools.
That does not mean every employee needs to become an AI engineer.
A finance professional may need to understand AI-assisted analysis. A marketing executive may use generative AI for research and content development. A software developer may work with AI coding assistants. A customer-service employee may supervise AI-generated responses.
This could result in AI literacy becoming a baseline workplace skill.
Employees who can combine their existing expertise with AI capabilities may be better positioned to benefit from the transition.
The entry-level hiring model may need to change
The traditional model of hiring large numbers of graduates and training them on the job could come under pressure.
If AI takes over some of the simpler tasks traditionally assigned to new employees, companies may need to rethink how graduates gain experience.
One possibility is greater emphasis on apprenticeships, internships and structured training programmes.
Another could be the creation of new junior roles focused on managing AI systems rather than performing the routine work those systems automate.
The transition will require companies to balance productivity gains with the need to develop future talent.
AI does not mean every job is at risk
It is also important not to treat all jobs as equally vulnerable.
AI is more capable of automating certain predictable and repetitive tasks than roles requiring complex physical work, human relationships, judgement or accountability.
Even within the same profession, AI may automate some responsibilities while leaving others to humans.
For example, an AI system may handle routine customer queries but still require human employees for complex complaints. Software tools may generate sections of code while developers remain responsible for architecture, security and final testing.
This suggests that the future of work may involve task transformation rather than the complete disappearance of entire occupations.
India’s large workforce makes the transition especially important
India’s scale makes its AI transition particularly significant.
A change affecting a few thousand employees in a small economy can have a very different impact when applied across a country with a massive workforce.
The technology-services sector is also an important contributor to India’s services exports and urban employment.
That means changes in hiring patterns could have implications beyond individual workers.
Cities that have developed around IT and BPO employment could experience changes in the type of jobs available, while educational institutions may need to adapt their courses to match new employer requirements.
Asia is experiencing a similar shift
India is not alone.
Nomura found 1,30,758 AI-related hires across Asia, compared with 60,654 job losses in the cases it studied. More than 90% of the hiring was in technology, while around 60% of the job losses were in financial services.
The trend was particularly visible in countries including India, China and the Philippines, where large business-process outsourcing industries are exposed to automation.
This suggests that AI’s employment impact is not simply an India-specific issue.
Across Asia, companies appear to be simultaneously reducing some traditional roles and creating new technology-driven positions.
The numbers need to be interpreted carefully
While the figures are encouraging, there are limits to what they tell us.
The Nomura report examined 69 employment-related cases rather than collecting data from the entire workforce.
As a result, the 83,100 hires and 31,921 layoffs or attrition cases should not be treated as a definitive national employment balance.
They instead provide an indication of how companies are responding to AI.
The distinction matters because the actual impact could vary significantly across sectors, companies, occupations and skill levels.
A large technology company creating thousands of AI roles does not necessarily offset job losses among workers in a different sector.
Productivity could be the bigger story
Beyond employment numbers, AI could significantly influence productivity.
Companies adopting AI may be able to produce more output with the same number of employees or maintain output with fewer workers.
For India, higher productivity could improve the competitiveness of its technology and services sectors.
It could also allow companies to offer more sophisticated services to international clients.
However, productivity gains will need to be accompanied by investment in people if the benefits are to be distributed broadly across the workforce.
Otherwise, the economic gains from AI could be concentrated among highly skilled workers and companies while less-skilled employees face greater disruption.
What workers can do
The changing job market makes continuous learning increasingly important.
Workers do not necessarily need to abandon their existing professions and become AI specialists. Instead, they can focus on understanding how AI is changing their particular field.
A customer-service professional could learn AI-assisted support systems. A programmer could strengthen skills in AI-enabled software development. A finance employee could develop expertise in automated analytics.
The combination of existing domain knowledge + AI capability could become increasingly valuable.
This may also provide a more realistic path for workers than attempting to compete directly for highly specialised AI engineering positions.
What employers need to consider
Companies also have a role in managing the transition.
If automation is introduced solely as a cost-cutting measure, workers displaced from existing roles may struggle to find alternatives.
Businesses that invest in retraining can potentially redeploy experienced employees into new positions.
Such an approach also preserves institutional knowledge.
For India’s workforce, employer-led reskilling could therefore be an important part of ensuring that AI becomes a source of productivity and job creation rather than simply a driver of displacement.
AI could change the meaning of a job
The most significant long-term change may not be the disappearance of jobs but the transformation of what workers do within them.
Employees could increasingly supervise AI systems, verify outputs, manage exceptions and focus on tasks requiring judgement and creativity.
This means the value of human work may shift towards skills that machines find harder to replicate.
Communication, critical thinking, problem-solving, leadership and domain expertise could become increasingly important alongside technical AI skills.
Conclusion
India’s early experience with artificial intelligence offers a more nuanced picture than the fear that AI will simply destroy jobs.
According to the Nomura analysis cited by India Today, India recorded 83,100 AI-related hires against 31,921 layoffs and attrition linked to AI, equivalent to roughly 2.6 hires for every job lost or affected. (India Today)
But the catch is significant: the new jobs are often not going to the same people whose jobs are being displaced.
Routine support and other entry-level functions are increasingly exposed to automation, while employers are looking for workers with specialised AI and technology skills. This could create a two-tier labour market and make the traditional path from an entry-level job to a specialised career more difficult.
For India, the challenge is therefore not simply to create more AI jobs. It is to ensure that workers can acquire the skills needed to move into those jobs.
If reskilling, education and employer-led training keep pace with technological change, AI could become a major source of productivity and employment. If they do not, the headline figure of more jobs being created than lost could conceal a growing skills and opportunity divide.