The New Hiring Paradox
India's job market is witnessing a significant divergence. While overall IT recruitment saw a 3% decline in June 2026, hiring for AI-specific roles jumped by 16%. This isn't just happening in the tech sector; across 14 industries, AI and machine learning
roles grew by 25%. This trend highlights a major shift: companies are not just hiring less, they are hiring differently. They are moving away from broad-based recruitment and focusing on acquiring specialised, production-ready AI talent. This move is creating a significant demand-supply gap, with NASSCOM and other experts predicting a shortage of over a million AI professionals in the near future if upskilling doesn't accelerate.
Core Technical Skills in Demand
So, what are these sought-after skills? At the foundation, proficiency in Python, SQL, and at least one cloud platform (like AWS, GCP, or Azure) is considered non-negotiable. Beyond that, companies are looking for expertise in specific, high-value areas. Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) are frequently mentioned in job descriptions. There's also a growing demand for Machine Learning Operations (MLOps) engineers, who are crucial for deploying, monitoring, and scaling AI systems. The focus has clearly moved from simply building models in a lab to operationalising AI in real-world business environments.
Beyond Coders: The Rise of 'Builders'
The definition of "AI talent" is expanding. Companies are increasingly looking for "AI builders"—professionals who can manage the entire lifecycle of an AI solution, from prototype to enterprise-scale deployment. This has led to the emergence of new job titles like Agentic AI Developer, GenAI Solution Architect, and AI Product Manager. This shift also means that a formal computer science degree is no longer the only entry point. A joint report by Indeed and NASSCOM found that 50% of employers now prioritise demonstrated AI skills and certifications over formal degrees, adopting a 'skills-first' hiring approach. Roles like Prompt Engineer and AI Business Analyst are becoming accessible even to those without a deep coding background.
The Overlooked Human Skills
As AI automates routine tasks, human-centric skills are becoming more valuable than ever. AI can write code and analyse data, but it cannot build trust with a client, lead a team through a complex project, or think critically about the ethical implications of a new system. As a result, employers are putting a premium on soft skills. Critical thinking, problem-solving, data interpretation, and the ability to collaborate effectively with both humans and AI systems are in high demand. Understanding AI ethics and governance is also becoming a key skill as businesses focus on deploying AI responsibly.
How to Become AI-Ready
For professionals looking to future-proof their careers, the message is clear: continuous learning is essential. The development of AI skills is largely happening outside traditional classrooms, with professionals learning on the job, through self-study, and from peers. Government and industry bodies are also stepping in with initiatives like the AI Skills Passport by Intel and Skill India, and NASSCOM's Future Skills Prime program. For job seekers, it's crucial to build a portfolio of projects that demonstrates practical application of these skills. Crafting a resume that highlights measurable achievements and uses relevant keywords is also vital to pass through initial AI-powered screening tools used by recruiters.
