AI for India’s Economic Transformation

• 19 Jul 2025

This editorial is based on “How India can protect jobs amidst the rapid AI march” which was published in Hindustan Times on 15/07/2025.The article highlights that India must urgently launch a national AI-readiness mission to transform jobs, education, and institutions for an AI-driven future.

For Prelims:Artificial Intelligence (AI), Open Network for Digital Commerce (ONDC), Generative AI, MSMEs, Public-private partnerships, biomanufacturing, BioE3 policy, Global Partnership on AI (GPAI), India’s G20 presidency, IndiaAI Mission, Large Language Models (LLMs), AI for All, PLI incentives,, India's National Semiconductor Mission, Sarvam-M. 

For Mains: The Role of Artificial Intelligence in India’s Economic Transformation. 

Artificial Intelligence (AI) is emerging as a core enabler of India's economic and developmental ambitions. With the domestic AI market projected to reach $17 billion by 2027, and over 600,000 AI professionals currently employed, India holds 16% of global AI talent. Its application spans agriculture, logistics, MSMEs, healthcare, and energy. Leveraging platforms like Aadhaar, Open Network for Digital Commerce (ONDC), and UPI, India is poised to integrate AI for inclusive transformation. However, to realise this potential, a calibrated approach addressing infrastructure, skilling, governance, and equity is essential. 

How can AI Drive Inclusive Growth and Economic Transformation in India? 

• Economic and Employment Impact: 
  • Massive Economic Potential: India's AI market is expected to triple to $17 billion by 2027, growing annually at 25-35%. 
    • This growth reflects India’s youthful workforce, digital access, and enterprise readiness for Generative AI integration. 
  • Boost to Employment and Productivity: AI is projected to create 1.25 million domestic jobs by 2027, according to Deloitte and Nasscom. 
    • Generative AI enhances productivity by 66% in task performance, according to a recent research. 
  • Global Competence in Talent: India accounts for 16% of global AI talent, second only to the United States in volume. 
    • More than 600,000 AI professionals currently work in India, expected to double by 2027. 
• Sectoral AI Adoption:  
  • AI is transforming agriculture, logistics, healthcare, and retail by optimising operations and decision-making. 
  • According to the National Council of Applied Economic Research, logistics costs accounted for 7.8-8.9% of GDP in 2021-22, and with the strategic integration of AI, the sector could uncover valuable patterns, predict disruptions, and create innovative solutions. 
  • PandoAI, for instance, uses AI to reduce logistics inefficiencies and improve real-time supply chain performance. 
• Boosting Agricultural Productivity: 
  • Empowering Agricultural Workforce: Over 46.1% of India's workforce is in agriculture, often suffering from low productivity and climate stress. 
    • ITC's MAARS platform provides personalised crop advisories, input planning, and market access to over 2 million farmers.  
• AI in Biosciences and Energy: 
  • Driving Growth in Biomanufacturing: AI is catalysing India’s biomanufacturing and biosciences sector through predictive modelling and bioprocess optimisation. 
    • Under the BioE3 policy, AI supports high-value domains like biosynthetics, vaccine design, and precision fermentation. 
  • Energy and Sustainability Contribution: AI enables predictive grid management, renewable forecasting, and efficient energy use across sectors. 
    • Such integration supports India’s net-zero 2070 target and energy resilience goals. 
• AI in Public Service Delivery: 
  • Transformation of Education: AI integration can address India’s 1.5 million annual engineering graduates, many of whom face underemployment. 
    • Skill initiatives must embed AI fluency, problem-solving, and adaptability into mainstream curricula. 
  • Strengthening Public Infrastructure: India's digital infrastructure, including the Aadhaar system, UPI, and ONDC, facilitates scalable and inclusive AI  interventions. 
    • With over 700 million internet users, data volume and access offer a foundation for broad-based transformation. 
    • For instance, the RBI's MuleHunter AI uses advanced machine learning algorithms to detect and prevent fraudulent financial activities, such as money laundering and illegal fund transfers. 

What are the Key Challenges in India's AI Progress? 

• Vulnerable Low-Skilled Workforce: AI threatens low-value service roles like data entry and customer support, many held by informal workers. 
  • These segments include women and rural populations, widening the inequality risk without targeted upskilling. 
• Digital Infrastructure Gaps: Rural areas still face limited internet access and device penetration, curbing AI's inclusive potential. 
  • About 65% of India’s population lives in rural regions, where digital readiness remains low. 
• Compute and Data Limitations: India generates 20% of global data but has only 2% of data centres and compute infrastructure. 
  • High hardware costs and chip dependencies restrict AI research, modelling, and innovation. 
• Weak Institutional Framework: India lacks an intersectoral national AI strategy, unlike other leading economies like the US, China, the UK and the EU. 
  • The IndiaAI Mission lacks the mandate and coordination authority needed for cross-sectoral alignment. 
• Gender Gaps and Informality: Women comprise 35% of India’s workforce, largely in roles vulnerable to automation. 
  • Without targeted re-skilling, AI could deepen labour market exclusion for women. 
• Environmental Footprint: Large Language Models (LLMs) require high energy use, straining green transition goals. 
  • According to Goldman Sachs, AI could become a bottleneck for sustainable energy targets. 
• Research and Academic Lag: India's universities are underrepresented in global AI rankings, and PhD output remains low. 
  • Academia-industry collaboration is weak, limiting indigenous innovation and foundational AI R&D. 

What Strategic Measures has India Undertaken to Harness AI for Development? 

• IndiaAI Mission: India has made steady progress in AI with initiatives like IndiaAI Mission(with a budget of ₹10,372 crore), 
  • Its components are part of a broader, democratised approach through "AI for All" with supportive policies. 
• FutureSkills PRIME Initiative: This joint initiative trains youth in AI, data science, and emerging tech, ensuring job readiness. 
  • It targets reskilling and upskilling across engineering colleges, ITIs, and industry clusters. 
• National Semiconductor Mission: With over $10 billion in PLI incentives, it aims to build domestic chip manufacturing and design capacity. 
  • This supports AI hardware self-reliance and reduces exposure to global semiconductor supply risks. 
• IndiaAI Compute Push: The central government plans to procure 10,000 graphics processing units (GPUs) to bolster India’s AI infrastructure. 
  • Compute capacity expansion is essential to support GenAI modelling and large-scale deployment. 
  • Also, India's National Semiconductor Mission seeks to establish a homegrown chip industry, backed by more than $10 billion in production-linked incentives. 
• AI Opportunity Fund: Launched in 2024, it supports 500,000 workers in partnership with NGOs and education providers. 
  • It provides access to AI skilling for underserved communities including women and informal workers. 
• AI for MSMEs: Policies promote AI access for 90% of India's business base, the MSME sector. 
  • Platforms like Dx-EDGE are empowering MSMEs with AI tools tailored to their unique needs. Launched by the CII, NITI Aayog, and AICTE, Dx-EDGE serves as a national initiative to facilitate digital transformation for MSMEs. 
  • Public and private efforts help MSMEs adopt AI for inventory, customer management, and operations. 
• Grow with Google Programmes: Trained over 60 million people across Asia Pacific, with India as a major beneficiary. 
  • These training modules focus on digital literacy, AI basics, and contextual application. 
• Sarvam AI and Krutrim Initiatives: Startups are creating India-centric LLMs like Sarvam-M and Krutrim’s multilingual conversational tools. 
  • These platforms drive linguistic inclusion and reduce reliance on foreign models. 
• BioE3 and Healthcare Applications: India’s BioE3 Policy and AI-integrated healthcare platforms aims to boost biomanufacturing and personalised medicine. 
  • The BioE3 policy also emphasizes the establishment of Bio-AI Hubs to drive innovation and collaboration in the fields of biotechnology and artificial intelligence. 
  • Firms like Biocon and Strand Life Sciences are leading with predictive drug screening using AI. 
• Smart Energy Integration: AI enables smart grid, fault detection, and demand response in energy systems. 
  • Supports India’s goal of 500 GW non-fossil capacity by 2030 under Paris Agreement commitments. 
• Other IndiaAI Initiatives: 
  • IndiaAI Innovation Centre: A hub for fostering collaboration and innovation in AI technologies by bringing together academia, industry, and government. 
  • IndiaAI Datasets Platform: A centralized repository of high-quality, publicly available datasets to support AI research and development in India. 
  • IndiaAI Applications Development Initiative: An initiative to develop and deploy AI-driven applications across sectors like healthcare, agriculture, and education for societal impact. 
• Geopolitical and Governance Leverage: India leads in the Global Partnership on AI (GPAI), promoting inclusive and ethical AI governance. 
  • India’s G20 presidency elevated AI as a global development and strategic agenda. 

What Policy and Institutional Reforms are Needed to Build an Inclusive AI Future? 

• Build Stewarding Institutions: Establish cross-sectoral "stewarding institutions" to align AI development with public welfare. 
  • Form a permanent Inter-Ministerial AI Coordination Committee to harmonize AI policy and regulatory efforts across government entities, avoiding fragmentation and ensuring a unified national strategy. 
  • These bodies should anticipate risks, opportunities, and labour transitions in real time. 
• Bridge Skilling and Education Gaps: Integrate AI skills across ITIs, polytechnics, and Tier-2/3 colleges, not only elite institutes. 
  • Develop contextual, multilingual, gender-sensitive skilling platforms with real-world application focus. 
• Incentivise Industry-Academia Collaboration: Encourage deep-tech R&D via fellowships, co-labs, and IP-sharing models. 
  • Align academic curricula with AI readiness and evolving industry demands. 
• Ensure Equitable Infrastructure: Expand compute and data infrastructure to Tier-2 and rural India, ensuring inclusion. 
  • Boost public and private investment in data centres, connectivity, and edge AI deployment. 
• Prioritise Ethics and Accountability: Design a framework for explainable, fair, and responsible AI, especially in sensitive domains. 
  • Incorporate transparency, data governance, and algorithm audits into regulatory norms. 
• Foster Global and Local Partnerships: Pursue multilateral cooperation and local entrepreneurship for AI standard-setting and localisation. 
  • Support startups solving India-specific challenges in agriculture, healthcare, and governance. 
• Prepare for Labour Market Transition: Forecast job transitions and reskill workers vulnerable to AI-driven automation. 
  • Create flexible labour pathways into medium- and high-skill AI-augmented roles. 
• Embed AI in Governance and Planning: Use AI for policy simulation, targeting efficiency, and climate resilience planning. 
  • Make AI a tool for inclusive governance, especially in urban planning and welfare delivery. 

Conclusion 

AI can transform India’s economy by enhancing productivity, creating jobs, and improving service delivery. With the right institutional frameworks, equitable access, and multi-sectoral readiness, India can harness AI not just for growth but for inclusive and sustainable development, becoming a global leader in ethical and human-centric AI innovation. 

Drishti Mains Question:

How can Artificial Intelligence (AI) contribute to inclusive and sustainable economic growth in India? Examine with sector-specific examples.

UPSC Civil Services Examination, Previous Year Question (PYQ)  

Prelims:

Q. With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)

1. Bring down electricity consumption in industrial units 
2. Create meaningful short stories and songs 
3. Disease diagnosis 
4. Text-to-Speech Conversion 
5. Wireless transmission of electrical energy 

Select the correct answer using the code given below:

(a) 1, 2, 3 and 5 only   

(b) 1, 3 and 4 only  

(c) 2, 4 and 5 only   

(d) 1, 2, 3, 4 and 5

Ans: (b)

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Mains: 

Q. What are the main socio-economic implications arising out of the development of IT industries in major cities of India? (2021)