Decoding the Data: A Net Positive Story
A recent and widely cited report from Nomura has put hard numbers to the AI employment debate in India. The analysis, covering the period from 2022 to August 2026, found 83,100 new AI-related hires compared to 31,921 layoffs and attritions linked to the technology.
This results in a net positive impact, creating roughly 2.6 jobs for every role lost or displaced. These findings position India as 'ground zero' for understanding AI's real-world impact on employment, given the sheer scale of its workforce and its role as the world's back office. While the data counters the prevailing narrative of mass job destruction, economists caution that it is still early and the numbers represent a snapshot of corporate activity rather than a complete census.
The Two-Tier Labour Market
The most significant story behind the numbers is the creation of a 'two-tier' labour market. The jobs being created are not the same ones being lost, and the displaced workers can rarely step into the new roles without significant retraining. The roles facing displacement are typically routine and repetitive, such as back-office operations, customer support, and basic software testing. Many of these job losses involve support teams being replaced by automated chatbots. Conversely, the new roles are highly skilled. Over 90% of the AI job creation has occurred within the technology sector itself, with a strong demand for IT graduates and specialists to meet growing AI needs. This has led to weaker demand for entry-level workers, while hiring for experienced senior and mid-level professionals remains strong. An ICRIER survey noted that 55% of IT firms reported a decline in entry-level hiring.
The New AI-Powered Roles
The surge in hiring is concentrated in specific, high-demand areas. According to LinkedIn's CEO, AI engineering roles in India are growing by a staggering 51% year-on-year. The most in-demand roles include AI specialists, machine learning engineers, data scientists, and those focused on AI data annotation and linguistics. While many of these are technical, AI's influence is expanding beyond pure engineering. A report from Scaler noted that nearly 50% of AI-enabled career outcomes now lie outside traditional engineering, in fields like leadership, consulting, HR, and marketing. This indicates that AI is evolving from a niche technical skill into a broader workforce capability essential for productivity and innovation across all business functions.
The Upskilling and Reskilling Imperative
The data makes one thing unequivocally clear: the skills gap is the single biggest challenge. While companies are creating AI jobs, a significant shortage of qualified professionals exists. One report warns India could face a shortfall of over a million AI professionals by 2027 if the pace of upskilling doesn't accelerate. This has created a talent paradox where hiring freezes coexist with fervent demand for specific skills. For professionals, the path forward involves proactive upskilling and reskilling. High-demand skills include machine learning, natural language processing (NLP), data engineering, and prompt engineering. Crucially, employers are increasingly valuing demonstrable skills and certifications from platforms like AWS and Azure, with 40% prioritizing them over traditional degrees. The focus has shifted from mass-hiring and training to recruiting job-ready candidates with proven AI fluency.
