AI Adoption Slows Entry-Level Hiring in India’s IT Sector

As artificial intelligence technologies become more integrated across workflows, India’s information technology sector is experiencing notable shifts in how companies hire talent. A recent firm-level study by the Indian Council for Research on International Economic Relations (ICRIER), supported by OpenAI, highlights a moderation in entry-level hiring while placing greater emphasis on skills that combine domain knowledge with AI and data capabilities.

Conducted between November 2025 and January 2026 and drawing responses from a wide range of IT firms, the study reveals that AI adoption is reshaping recruitment priorities, although it does not suggest a widespread collapse in employment overall. The findings indicate nuanced changes in workforce demand that reflect broader industry transitions rather than a simple replacement of human jobs by machines.

Entry-Level Hiring Softer as AI Tools Enhance Productivity

According to the ICRIER report titled ‘AI and Jobs: This Time Is No Different,’ as many as 65 per cent of companies surveyed reported reducing overall hiring after adopting AI tools. This trend is especially visible at the entry level, where routine tasks are increasingly automated or supplemented by intelligent systems.

Roles traditionally perceived as early career stepping stones — such as basic programming, clerical data work, automated testing, and manual quality assurance — are seeing the greatest moderation in demand. In these areas, generative AI systems and automated tools are being used to handle repetitive or predictable tasks, reducing the need for large junior teams.

However, the report also notes that entry-level hiring has not disappeared outright in all firms. Some companies continue to recruit early career talent, especially where innovation, creativity, and human oversight remain central. This suggests that the impact of AI on hiring is not uniform and varies across business functions and firm strategies.

Rising Demand for Hybrid Skill Sets

The report finds that 63 per cent of firms now prioritise candidates with hybrid skill profiles — combining domain expertise with AI, data analysis, or machine learning capabilities. This shift reflects a broader trend where technology adoption is not eliminating jobs but transforming the skills needed to succeed.

Demand for specialised competencies such as prompt engineering, data analytics, and machine learning has climbed notably, and companies increasingly seek professionals who can work with and manage AI systems rather than ones who are easily replaced by them. A focus on such hybrid roles positions workers to better support AI driven initiatives and contribute to strategic outcomes.

Mid-Level and Senior Roles Remain Steady or Grow

Despite the moderation at entry level, the study shows that mid-career professionals and senior leaders are relatively stable in terms of workforce demand. Many firms report that mid-level positions are growing, and senior roles continue to play a critical role in driving strategy, managing teams, and overseeing AI integration efforts.

This aligns with broader hiring patterns across India’s tech economy. Independent workforce trend reports indicate that mid-level professionals accounting for 65% of total IT hiring in 2025, with entry-level roles making up a smaller share. While these findings stem from varied data sources, they echo the direction of demand towards experienced, productivity-ready talent.

AI’s Role as Productivity Enhancer Rather Than Job Killer

One of the most important takeaways from the ICRIER analysis is that AI appears to be functioning as a productivity enhancer, not an outright substitute for human labour. Across the divisions most affected by AI adoption, productivity gains outnumber declines by a significant margin. Many business units reported higher output and lower costs without reducing overall employment.

This distinction matters for workforce planning and public policy. Instead of triggering mass layoffs, AI is nudging employers to invest in skills development, targeted training, and strategic hiring — particularly for roles where human judgment, creativity, and domain expertise are essential.

Training and Reskilling Gaps Present Challenges

While firms recognise the importance of AI skills, the study also highlights a gap in training and readiness. Only a small share of companies reported training more than half their employees in AI-related skills over the past year. Barriers such as limited qualified trainers, high costs, and organisational preparedness issues remain obstacles to widespread upskilling.

Addressing these training gaps will be critical for ensuring that workers remain employable and competitive in an AI driven economy. Upskilling initiatives focused on data proficiency, AI fluency, and strategic tech management could help bridge workforce gaps and support broader economic growth.