The Headline Numbers, Explained
Recent data from a Nomura report paints a surprisingly optimistic picture, running counter to the common narrative of mass job losses. Between 2022 and August 2026, India saw approximately 83,100 AI-related hires compared to 31,921 job losses due to AI-driven
automation and attrition. This results in a net positive gain of over 51,000 jobs, making India 'ground zero' for understanding the real-world employment impact of artificial intelligence. For every job displaced by AI, roughly 2.6 new ones are being created. However, the story behind these numbers is one of deep structural change, not simple replacement.
Where the New Jobs Are Growing
The hiring boom is concentrated in highly skilled, technology-focused roles. Companies are aggressively seeking talent for positions that did not exist a few years ago. The most in-demand roles include Machine Learning Engineers, Data Scientists, Generative AI and LLM Developers, MLOps Engineers, and AI Product Managers. The demand is so high that AI engineering roles in India are growing at a staggering 51% year-on-year. While the technology sector accounts for the vast majority of this growth, industries like healthcare, retail, banking, and financial services are also creating new positions for talent that can leverage AI for tasks like clinical data analysis and IT process modelling.
Which Roles Are Being Disrupted
The 31,900 job losses are not random; they are concentrated in roles with routine, repeatable tasks that are ripe for automation. The most affected positions include customer support teams, which are increasingly being replaced by sophisticated chatbots, and back-office banking operations. Junior-level IT roles, such as those in quality assurance testing and basic coding, are also seeing reduced demand. This shift isn't always happening through outright layoffs. Many companies are simply slowing down or freezing recruitment for these entry-level positions, which have traditionally been the gateway into the tech industry for many fresh graduates.
The Great Skill Divide
The core issue is that the workers being displaced are rarely the ones getting the new AI jobs. This is creating a two-tier labour market: high demand for experienced, specialised professionals and shrinking demand for entry-level generalists. The problem is a significant skills mismatch, with employers reporting that they struggle to find applicants with the right qualifications. In this new environment, employers are fundamentally changing how they hire. A stunning 80% of leaders now say they would hire a less experienced candidate with AI skills over a more experienced one without them. Demonstrable skills and project portfolios are becoming more valuable than traditional degrees alone.
A Practical Roadmap to Stay Ahead
Navigating this transition requires a proactive approach to upskilling. The most sought-after technical skills today include Python, experience with Retrieval-Augmented Generation (RAG) and vector databases, and proficiency with large language model (LLM) APIs. Beyond technical skills, employers are looking for people with 'AI literacy' — the ability to use AI tools responsibly and evaluate their output critically. Your first step should be to gain foundational knowledge in these areas through online courses and certifications. Then, focus on building a portfolio of real projects that showcase your ability to apply these skills. Professionals who combine technical AI knowledge with domain expertise in their field — be it marketing, finance, or HR — will be the most valuable in the years to come.
