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Context

NITI Aayog released a report titled “Roadmap for Job Creation in the AI Economy”, which analyzes how Artificial Intelligence is transforming India’s technology and services sectors.  

Highlights of the Report

The report addresses how Artificial Intelligence (AI) will impact jobs in IT and Customer Experience (CX) sectors. It presents two different futures for India, emphasizing that the outcome depends entirely on the strategic choices made today.

1. The Risk (Business-as-usual Scenario)

If India fails to adapt, it could face huge job losses. By 2031, the tech services workforce could shrink from its 2023 level of 7.5-8 million to 6 million. The CX sector could decline from 2-2.5 million to 1.8 million. This represents a potential net loss of over 1.5 million jobs.

2. The Opportunity (Strategic Action Scenario)

If India acts decisively, it can turn the disruption into a generational opportunity. The tech workforce could swell to 10 million, and the CX workforce could grow to 3.1 million by 2031, creating up to 4 million new opportunities and positioning India as the "AI workforce capital of the world."

How AI is Reshaping the Tech Sector: The 3W Framework

The report uses a Work-Worker-Workforce (3W) framework to provide analysis of AI's impact.

Change in Work: AI is fundamentally changing how work is done.

• Automation of Routine Tasks: AI is automating tasks like code generation, bug fixing, and customer support, leading to productivity gains (10-20% in the software development lifecycle).
• Creation of New Revenue Streams: AI is enabling Indian IT firms to enter new domains like drug discovery and quantum computing, which were traditionally non-IT budgets.

Change in the Worker: The roles and skills required of workers are evolving rapidly.

• Roles at Risk: Low-skill, repetitive roles like Junior Testers and  Help Desk Agents face a high risk of becoming redundant.
• Emerging Roles: New, specialized roles are being created. These fall into three categories:
• Enterprise AI Skills: AI Prompt Engineers, AI Architects.
• Frontier AI Skills: Quantum ML Engineers, Neurohaptic Engineers.
• "AI for AI" Skills: Advanced research scientists developing the next generation of AI models.
• Evolving Roles: Existing roles like Data Architects and Full-Stack Developers are evolving to incorporate AI skills like LLM API integration and AI model training.

Change in the Workforce: Structure of organizations is transforming.

• Flatter Pyramids: As AI boosts productivity and automates junior-level tasks, organizational structures are becoming leaner, with fewer layers and a greater focus on high-level strategic skills.

India's Three Critical Challenges

The report highlights that India is at a tipping point due to three major challenges that could push it towards the negative job-loss scenario.

The Scale of Job Displacement: A significant portion of the formal workforce is at risk. According to the Centre of Advanced Study in India, over 60% of formal sector jobs are susceptible to automation by 2030.

Gaps in Education and Skilling:

• Uneven Grassroots Education: Unlike in China and Russia, Computer Science education is not mandatory or uniformly available in Indian schools, limiting early exposure to foundational skills.
• Lagging Innovation Footprint: At the research level, India lags in AI innovation. Its share of granted AI patents fell from nearly 10% in 2010 to under 5% in 2023 (Source: 2025 AI Index Report).

A Widening AI Talent Gap

• Supply-Demand Mismatch: The supply of AI talent in India is only 50% of the current demand, and this gap is expected to widen (Source: NASSCOM).
• Negative Talent Migration: India is not a top destination for global AI talent and suffers from a net negative talent migration (-1.55 per 10,000), as nearly 44% of its top AI researchers work abroad.

Way Forward: Recommendation made by the Report

Integrate AI in the Education System

• Expand AI Literacy: Make AI a foundational skill by integrating it into school and undergraduate (UG) curricula.
• Scale AI+X Programs: Launch large-scale interdisciplinary programs that blend AI with other subjects (e.g., AI in Healthcare or Finance). 
• Boost Research: Increase funding and scholarships for AI PhD fellowships to strengthen India's research output.

Become a Global AI Talent Magnet

• AI Talent Visa: Introduce a dedicated fast-track visa and residency pathway for global AI experts and returning Indian researchers. 
• Incentivize Returnees: Guarantee access to high-end GPU compute infrastructure and R&D grants for returning diaspora researchers.
• Establish Autonomous CoEs: Set up AI Centres of Excellence (CoEs) with institutional autonomy to anchor the work of top talent.

Build AI Skilling Engine for Current Workforce

• National AI Literacy: Launch upskilling programs for the current workforce through platforms like the Skill India Digital Hub (SIDH) and existing schemes such as PMKVY 4.0.
• Micro-Credentials: Introduce specialized, short-term micro-credential courses focused on high-demand, AI-native skills (e.g., Prompt Engineering, LLM Operations).
• Expand Professional Education: Provide flexible AI masters and doctoral programs for working professionals.

Establish India Open-Source AI Commons

• Unify Data: Merge fragmented data platforms (like OGD, NDAP, and AIKosha) into a unified, public "India AI Commons" repository of datasets, models, and APIs.
• Open-Source Models: Release all Government-funded AI models and tools as open-source with clear reuse licenses.
• Transparent Benchmarks: Build transparent benchmarks and validation tools to ensure the trust and quality of public models and datasets.

Operationalize Federated National Compute & Innovation Grid

• Rapid GPU Cluster Deployment: Quickly operationalize GPU clusters and LLM sandboxes with open access (like the planned 18,693 GPUs under the India AI Mission).
• Tiered Access: Offer tiered and subsidized access (via compute credits) to PhD researchers, innovators, and AI startups.
• Decentralize Compute: Establish a federated grid with nodes in top AI labs and Tier 2/3 universities to decentralize innovation. 

Conclusion

The NITI Aayog roadmap provides an analytical and urgent blueprint for India's labor policy in the AI age. It stresses that job evolution is the goal, not just job loss mitigation. Its key strength lies in its integrated, mission-mode approach, seeking to unify skilling, education, and infrastructure under one umbrella.

Source: PIB