At a time when global conversations around artificial intelligence are dominated by fears of large-scale job displacement, new evidence from India presents a more balanced picture. A joint study by the Indian Council for Research on International Economic Relations (ICRIER), supported by OpenAI, finds that generative AI is not triggering mass layoffs in India’s IT sector. Instead, it is reorganising work, amplifying productivity, and reshaping skill demand.
Titled “AI and Jobs: This Time Is No Different,” the study is among the most comprehensive firm-level assessments of generative AI adoption in India. Based on a survey of 650 IT firms across 10 cities, conducted between November 2025 and January 2026, the report analyses hiring patterns, occupational demand, productivity outcomes, and workforce skilling trends.
The findings suggest a structural transition — not a disruptive shock.
Productivity Is Rising — Without Job Collapse
Across more than 1,900 business divisions identified as AI-affected, productivity gains significantly outpaced declines. Divisions reporting higher output with stable or smaller team sizes outnumbered those facing productivity drops by 3.5 to 1.
Nearly one-third of divisions reported both higher output and lower costs. This signals operational leverage: firms are scaling delivery without proportional increases in headcount, but crucially, not through widespread workforce reductions.
Entry-level hiring has moderated modestly. However, mid-level and senior roles remain stable. The report notes that this moderation aligns with broader post-pandemic IT hiring corrections rather than being solely attributable to AI adoption.
Notably, roles often considered vulnerable — such as software developers and database administrators — are seeing strong demand growth, reinforcing the view that generative AI is acting as a productivity complement rather than a substitute for technical expertise.
The Shift Toward Hybrid Talent
One of the clearest structural signals is the demand for hybrid skills.
63% of surveyed firms report increased demand for professionals who combine domain expertise with AI or data capabilities. As generative AI becomes embedded in coding workflows, testing, documentation, analytics, and customer engagement, the premium is shifting toward professionals who can supervise, validate, and contextualise AI outputs.
This reflects a broader truth about AI adoption globally: productivity gains accrue most where human judgment and machine capability intersect.
Upskilling Gap: The Real Risk
While more than half of firms are running AI awareness or training programmes, and another 38% plan to, coverage remains shallow. Only 4% of firms have trained more than half their workforce in AI tools and workflows.
Challenges include:
Shortage of qualified trainers
High implementation costs
Uncertain ROI
Ethical and legal concerns
Organisational readiness gaps
Ronnie Chatterji, Chief Economist at OpenAI, emphasised that the transition is underway, but preparation remains uneven. The opportunity lies in scaling workforce readiness before capability gaps widen.
India’s Strategic Position in the AI Cycle
The study concludes that rising global demand for AI-enabled goods and services is likely to support net job creation in India’s IT sector over the medium to long term.
India’s competitive advantage lies in:
A large technical workforce
Deep services integration capabilities
Rapid enterprise AI adoption
Cost-efficient delivery models
If managed well, AI could strengthen India’s position as a global digital services hub rather than erode it.
Beyond the Study: The Broader AI Inflection Point
The findings align with broader global signals.
AI is shifting from experimentation to integration. Enterprises worldwide are embedding AI copilots into development, security, analytics, finance, and customer operations. The result is workflow acceleration, compression of decision cycles, and reduced friction across delivery chains.
Meanwhile, companies such as Anthropic are advancing frontier models like Claude, with strong enterprise uptake in coding assistance, reasoning-heavy tasks, and regulated environments. Anthropic’s emphasis on AI safety, constitutional AI, and reliability has influenced how enterprises think about governance and responsible deployment.
The impact is twofold:
Capability Expansion: Developers can iterate faster. Analysts can synthesise insights more quickly. Decision cycles shrink.
Governance Maturity: AI adoption now requires structured oversight, risk frameworks, and clear accountability — creating new roles in AI governance, compliance, and ethics.
Globally, the AI race is no longer just about model performance. It is about enterprise integration, trust, and workforce transformation.
A Transition Defined by Adaptation
Shekhar Aiyar, Director and CEO of ICRIER, notes that while the results should reassure policymakers, complacency would be a mistake. India’s IT sector is managing AI adoption relatively well — but preparedness is uneven.
The evidence suggests that AI is reinforcing productivity growth and evolving employment patterns rather than causing contraction.
This transition is less about replacement and more about reconfiguration.
The real divide may not be between humans and AI — but between firms that reskill aggressively and those that do not.