India's IT sector is experiencing a selective hiring revival focused on specialized AI roles, with AI hiring within the IT sector rising 16% year-on-year according to Naukri's June 2026 JobSpeak report, even as overall IT job listings declined 3% during the same period. As reported by Business Standard, companies are adopting different strategies to build specialized AI talent pools, with HCLTech building a cadre of Forward Deployed Engineers who work directly with customers using AI, while TCS has shifted towards smaller, targeted hiring with a focus on AI-native talent. Infosys has revamped its campus hiring strategy to prioritize AI, generative AI, cloud computing and data engineering talent, and Wipro is increasingly adopting a skills-first approach that places greater emphasis on demonstrable capabilities than conventional academic credentials. According to Business Standard, IT hiring is back, but selectively - companies are selectively recruiting professionals whose capabilities align with growing enterprise demand for AI rather than expanding headcount across the board.
The hiring revival faces a significant constraint: India could face a shortage of more than 600,000 AI professionals by 2027, according to a Nasscom report. As reported by Business Standard, more than 90% of early-career technology professionals use AI tools, but only 23% qualify as 'AI-native' engineers with the technical depth and independent problem-solving skills needed to build and deploy AI systems. AI model and application development (39%) and AI literacy (38%) rank among the hardest capabilities to hire according to ManpowerGroup's Global Talent Shortage Survey 2026. The challenge extends beyond technical expertise, with the most difficult roles to fill being those that combine AI expertise with deep industry and engineering domain knowledge. According to Business Standard, growing competition from global capability centres, startups and multinational technology companies, coupled with the rapid evolution of AI models and programming frameworks, is making it harder for India's IT services firms to secure and retain experienced AI professionals.
The talent shortage stems from a fundamental gap between academic education and corporate applications. As reported by Business Standard, Anand Mahurkar, founder and CEO of Findability Sciences, noted that "talent is not the issue, the problem exists in the gap between academic education and corporate applications." Prof V N Rajasekharan Pillai, an elected Fellow of the Indian Academy of Sciences, explained that AI is evolving at a much faster rate than traditional university curriculum revision cycles. The challenge extends beyond curriculum design, with curricula still being siloed while AI is inherently multidisciplinary. The number of institutes that possess faculty expertise, advanced computing infrastructure and industry ecosystems to deliver high-quality AI education at scale is relatively small, according to Business Standard. Access to high-performance computing, cloud platforms, quality datasets and modern laboratories also varies considerably across institutions, creating significant barriers to developing job-ready AI professionals.
As hiring alone becomes insufficient to meet AI talent requirements, Indian IT companies are increasingly investing in reskilling programmes and industry partnerships. According to Business Standard, Tushar Dhawan, CEO of TrueSales, noted that "while external hiring remains essential for specialised roles such as Agentic AI, AI engineering, MLOps and AI security, a growing share of enterprise AI requirements is now being addressed through internal reskilling because it is more scalable and sustainable." Findability Sciences' Mahurkar said companies are investing heavily in AI training academies, role-based learning pathways, certification programmes, hackathons and sandbox environments. Many companies are also partnering with universities and cloud service providers to expand the pipeline of industry-ready talent. As reported by Business Standard, industry leaders say continuous upskilling will be critical as AI technologies evolve faster than traditional hiring cycles, with experts suggesting it could take another three to five years to develop an enterprise-ready AI workforce at scale. Until then, companies will have to rely on a combination of selective hiring, internal reskilling and industry partnerships to bridge the gap between demand and supply.
