A Tale of Two Trends
The Indian job market is currently defined by two conflicting AI narratives. On one hand, the country is a hotbed for AI-driven job creation. A recent Nomura report highlighted that India is seeing approximately 2.6 AI-related hires for every one job lost
or affected by the technology. From 2022 to August 2026, India recorded 83,100 AI-related hires against 31,921 layoffs linked to automation. LinkedIn's CEO also recently noted that AI engineering roles in India are growing at a staggering 51% year-on-year. This paints a picture of a booming sector hungry for new talent. However, a contradictory trend of deep-seated anxiety is growing in parallel. A July 2026 survey by the professional network Blind found that 66% of professionals working in AI and machine learning roles in India expect layoffs in their teams within the next six months. This suggests that even those building the tools of tomorrow are not immune to career uncertainty, challenging the assumption that an AI-focused job is a safe haven.
Where the AI Jobs Are
The demand for AI talent is not uniform; it's heavily concentrated in specific sectors. Unsurprisingly, the IT services industry, including giants like TCS and Infosys, is a primary driver of AI hiring. The Banking, Financial Services, and Insurance (BFSI) sector is another major recruiter, using AI for fraud detection, risk management, and customer operations. India's booming product and e-commerce companies are also aggressively hiring AI talent to enhance user experience and logistics. While these roles offer significant opportunities, they are not the same ones being displaced. The Nomura report points out that most job losses are in support teams being replaced by chatbots, while hiring is focused on IT graduates with specific AI skills. This mismatch is creating a significant challenge: the workers losing jobs rarely have the skills to transition into the new roles being created.
The New Skill Set in Demand
The qualifications for securing these new roles have shifted dramatically. Employers are increasingly adopting a 'skills-first' approach, prioritising demonstrable ability over degrees alone. The most sought-after technical skills include Python, SQL, and experience with machine learning frameworks like TensorFlow or PyTorch. More advanced roles demand expertise in newer areas like Retrieval-Augmented Generation (RAG) and designing agentic AI systems. However, the skills gap isn't purely technical. A NASSCOM report from July 2026 warns that while many young professionals are 'AI-proficient' (meaning they can use AI tools), only 23% are 'AI-native'—able to apply deep engineering judgment and problem-solving skills alongside the technology. Employers are also placing a higher premium on 'human' skills like analytical and creative thinking, resilience, and complex problem-solving—abilities that AI cannot replicate.
The Roots of Job Insecurity
The anxiety felt even by AI professionals stems from the rapid evolution of the technology itself. The skills that are in demand today may not be tomorrow. According to the Blind survey, AI/ML workers feel nearly as vulnerable to cuts as sales and marketing professionals, roles long considered prime for disruption. This feeling of precarity is fueled by the very productivity gains AI delivers; as models become more powerful, the need for large teams to build and maintain them may shrink. Furthermore, there's a growing divide between being a user of AI and being a creator. NASSCOM cautions against the risk of the workforce becoming 'AI-reliant' rather than 'AI-native', where professionals use AI as a crutch without developing fundamental expertise. This could lead to a decline in deep engineering skills, making even technical workers more expendable over the long term.
