The Paradox in the Numbers
On the surface, the story of AI in India is one of remarkable growth. A recent report from Nomura highlighted that for every job lost to AI, 2.6 new ones are being created. Specifically, India saw about 83,100 AI-related hires against roughly 32,000 job losses
linked to the technology. This suggests a net positive trend. However, a separate July 2026 survey from the professional networking platform Blind tells a different story: 66% of AI and machine learning professionals in India expect layoffs in their teams within the next six months. This level of anxiety is second only to sales and marketing roles, challenging the popular belief that an AI-focused career is a safe haven.
Where the Hiring Boom Is Happening
The demand for new talent is real and concentrated in highly specialized areas. Companies are aggressively seeking Machine Learning Engineers, Generative AI Developers, Data Scientists, and MLOps Engineers. NASSCOM estimates that India will need over a million AI professionals by 2027, but the current supply of trained individuals covers less than 20% of that demand. This has created a fierce competition for talent, with employers prioritizing demonstrable skills over traditional academic credentials. The hiring growth is almost exclusively in the technology sector, which has absorbed over 90% of the new AI-related roles.
The Source of Widespread Anxiety
The fear of layoffs stems from a fundamental mismatch. The jobs being eliminated are not the same as the ones being created, and the displaced workers cannot easily transition. The roles most vulnerable to automation are those involving routine or repetitive tasks, particularly in sectors like financial services and business process outsourcing (BPO). A NASSCOM report from early 2026 noted that junior and mid-level employees are seen as the most adversely impacted by AI. The anxiety among even AI specialists can be attributed to the rapid evolution of the field; as companies shift from AI research to practical deployment, team structures and skill requirements change, leading to restructuring and a sense of instability.
A Tale of Two Labour Markets
Economists at Nomura describe the current situation as a 'two-tier labour market'. In the top tier, there is soaring demand and high salaries for experienced professionals with specialized AI skills. In the bottom tier, demand for traditional entry-level roles is shrinking. These basic jobs historically served as a training ground for fresh graduates to enter the corporate world. As AI automates these routine tasks, that pathway is closing for many, making it harder for those without pre-existing, job-ready skills to get a foothold. This creates a significant talent shortage, with one survey finding that 82% of Indian employers are struggling to find the talent they need, despite a high volume of graduates.
Upskilling Is No Longer Optional
The data points to a clear, unavoidable conclusion: the key to navigating this new landscape is continuous learning and adaptation. The World Economic Forum has estimated that a significant portion of India's workforce will require substantial upskilling by 2030. The skills in highest demand include not just technical abilities like Python and machine learning, but also the capacity to use AI tools effectively to solve real business problems. The focus has shifted from what you studied to what you can build and what problems you can solve. Leading industry bodies like NASSCOM emphasize that the future is about human-AI collaboration, where technology elevates human roles rather than simply replacing them.
