The Tale of Two Trends
On the surface, the numbers seem to conflict. A recent report from Nomura highlights that for every Indian job lost to AI, 2.6 new ones are created. Between 2022 and August 2026, India saw 83,100 AI-related hires versus 31,921 layoffs linked to the technology.
This suggests a net positive impact, running counter to the narrative of mass unemployment. Yet, a separate July 2026 survey from the anonymous professional network Blind found that 66% of AI and machine learning professionals in India expect layoffs in their teams within six months. This anxiety is second only to sales and marketing staff. So, what’s really going on? The reality is that the workers losing their jobs are rarely the same ones being hired, creating a two-tiered labour market.
Who Feels the Fear?
The roles most vulnerable to AI disruption are those involving routine, repetitive tasks. Think back-office banking operations, traditional customer service, and junior technical positions like basic coding and software quality assurance testing. As AI-powered chatbots and automation tools become more sophisticated, companies are finding they need fewer people for these entry-level jobs. One survey noted that 55% of companies in India's IT sector reported a decline in entry-level hiring. This explains why even as some companies hire aggressively for AI talent, others are implementing hiring freezes and budget cuts, creating an atmosphere of uncertainty. The anxiety isn't just about official announcements; it's fueled by these 'quiet signs' of change.
Where the Growth Is
The explosion in hiring is concentrated in specific, high-skill areas. Companies are not just looking for people with 'AI skills'; they are seeking specialists. More than 90% of the new AI-related jobs are in the technology sector itself. According to Naukri data from mid-2026, AI skills now feature in 47% of all white-collar job descriptions. The demand is intense for roles requiring expertise in machine learning, data science, Python, SQL, and cloud platforms like AWS or GCP. More advanced and highly paid skills include Large Language Model (LLM) fine-tuning and building with Retrieval-Augmented Generation (RAG). In fact, NASSCOM has identified a 17x demand gap for engineers with LLM fine-tuning skills, with fewer than 8,000 qualified professionals for 1.4 lakh open positions.
The Great Skill Reshuffle
This isn't a story of job destruction but one of job transformation. The core issue is a widening skills gap. Companies have shifted from mass hiring and on-the-job training to a 'skills-first' approach, seeking job-ready candidates who can deliver value from day one. This puts freshers and those in legacy roles in a difficult position. The skills that built India's IT and BPO dominance are not the same ones that will secure its future in the AI era. NASSCOM has warned that without a focus on preserving deep engineering expertise, the workforce risks becoming overly reliant on AI tools without understanding the fundamentals. This shift requires a national effort in upskilling and reskilling, with industry bodies and the government launching initiatives like the AI Skills Yatra and AI Skills Passport to bridge the gap.
Your Career's AI Strategy
For the individual professional, the message is clear: adaptation is not optional. The value is no longer in executing routine tasks but in leveraging AI for higher-order work that requires creativity, critical thinking, and problem-solving. Even in non-technical roles, a basic understanding of AI applications is becoming a baseline expectation. Professionals should focus on building a T-shaped profile: deep expertise in their core domain, complemented by a broad understanding of how AI can be applied. Learning foundational skills like Python, understanding how to work with LLM APIs, and gaining experience with data analysis are becoming crucial across functions. The goal is to move from being a worker who could be replaced by AI to one who orchestrates AI to create value.
