SYLLABUS
GS-2: Important Aspects of Governance, Transparency and Accountability, E-governance- applications, models, successes, limitations, and potential.
GS-3: Science and Technology - Developments and their Applications and Effects in Everyday Life.
Context: The recently released World Bank’s India Development Update: India and Artificial Intelligence—Seizing the Development Opportunity report identifies India as one of the top 10 leading emerging-market performers in AI readiness.
Key Findings of the World Bank Report
• Strong foundations but early-stage adoption: India is well positioned to adopt and adapt AI due to its large technical workforce, integrated IT sector and Digital Public Infrastructure; however, AI adoption remains at an early stage and limited compute capacity constrains frontier AI development.
• Rising AI investment and technology ecosystem: Private AI investment more than tripled from US$1.2 billion in 2024 to US$4.1 billion in 2025, while employment in Global Capability Centres rose from 1.9 million to 2.36 million.
• Significant development potential: AI can generate substantial productivity gains, expand export opportunities and improve public-service delivery, provided India broadens adoption beyond large urban firms.
• Adoption and adaptation over frontier development: The larger opportunity for India lies in adopting and adapting AI to local conditions, while limited compute capacity currently constrains frontier AI development.
• Labour-market impact remains uncertain: While the long-term effects are uncertain, current evidence suggests lower labour-substitution risks than in advanced economies, partly because India has a smaller share of cognitive jobs, leaving considerable scope for productivity gains.
• Adoption gap remains significant: Only 23.4% of formal Indian firms report using some form of AI, compared with 42.7% in the United States, indicating considerable scope to deepen enterprise adoption.
AI Ecosystem in India at Present
• Technology and talent base: India’s technology sector was projected to cross US$280 billion in annual revenue in 2025, with more than 6 million people employed across the technology and AI ecosystem.
• Innovation and startup ecosystem: India has 1,800+ Global Capability Centres, including 500+ AI-focused centres, and around 1.8 lakh startups; nearly 89% of startups launched in the preceding year used AI in their products or services.
• Enterprise and sectoral adoption: India scores 2.45 out of 4 on the NASSCOM AI Adoption Index, with PIB reporting 87% of enterprises actively using AI solutions; industrial and automotive, consumer goods and retail, BFSI, and healthcare are among the leading adoption sectors, together contributing around 60% of AI’s total value.
• Emerging AI maturity: Around 26% of Indian companies have achieved AI maturity at scale, according to the BCG survey cited by PIB, indicating a gradual movement from experimentation towards scaled enterprise adoption.
Key Government Initiatives and Policy Push
• IndiaAI Mission: Approved in March 2024 with a budget outlay of ₹10,371.92 crore over five years, the Mission seeks to build a comprehensive AI ecosystem through seven pillars covering compute, applications, datasets, foundation models, skills, startup financing and Safe & Trusted AI.
• Compute, data and indigenous models: More than 38,000 GPUs have been onboarded under the IndiaAI Mission for affordable access, while AIKosh provides shared datasets and AI models, and the Foundation Models pillar supports development of indigenous AI models tailored to Indian data and languages.
• Applications, research and human capital: Government initiatives include AI Centres of Excellence in healthcare, agriculture, sustainable cities and education, India-specific AI applications, FutureSkills and Data & AI Labs to expand AI capabilities beyond the existing technology ecosystem.
• Responsible and globally competitive AI: The Safe & Trusted AI pillar addresses issues such as privacy, bias, explainability and governance.
- India’s wider AI ecosystem was also ranked third globally in Stanford University’s 2025 Global AI Vibrancy Tool, reflecting its progress in AI talent, research, investment, infrastructure and policy.
Challenges to Harnessing AI for Development
• Uneven enterprise adoption: The World Bank’s finding that only 23.4% of formal Indian firms use AI highlights the gap between India's strong technology ecosystem and actual adoption, particularly among smaller firms.
• Compute and infrastructure constraints: Limited access to AI-enabling infrastructure and computing capacity remains a constraint, particularly for frontier AI development and wider adoption beyond established technology centres.
• Skills and workforce transition: India needs to strengthen worker capabilities and continuously reskill its workforce as AI changes the nature of tasks and occupations, even though current substitution risks remain lower than in advanced economies.
• Governance and inclusion: Ensuring broad-based benefits requires an enabling business environment and adaptive governance that reduces regulatory uncertainty while safeguarding data security and privacy.
Way Forward
• Broaden AI adoption: Lower barriers to AI adoption for MSMEs and smaller firms so that productivity gains are not concentrated among large technology-intensive enterprises.
• Build an AI-ready workforce: Strengthen skilling, reskilling and workforce capabilities so that workers can adapt to changing tasks and increasingly complement AI rather than remain vulnerable to technological displacement.
• Promote locally relevant AI: Focus on adopting and adapting AI to Indian conditions, including affordable “small AI” applications for sectors such as agriculture, healthcare and public services where local constraints and limited connectivity matter.
• Strengthen enabling foundations and governance: Expand physical and digital infrastructure, foster local AI innovation and establish a clear, adaptive regulatory framework that supports innovation while protecting data security and privacy.
