World Development Report 2026: AI’s Economic Potential and India

Subject: GS Paper 3: Science and Technology

Context: The World Bank Group’s ‘World Development Report 2026: The Promise of Artificial Intelligence’ highlights AI’s potential to sustain economic growth, boost productivity, improve public services and expand opportunities.

IAS coaching

Economic Potential of Artificial Intelligence (AI)

• Productivity Enhancement: AI can improve productivity by solving practical problems and enabling businesses, households and governments to perform tasks more efficiently.
• Downstream Adoption: Significant economic value can be generated by deploying AI across sectors and adapting it to local needs, rather than focusing only on developing advanced AI models.

India’s Approach to AI Adoption

• India’s Advantage: India’s experience in deploying technology at population scale, particularly through Digital Public Infrastructure (DPI), provides a foundation for expanding AI adoption.
• About DPI: Digital Public Infrastructure (DPI) is a set of shared digital platforms and systems that enable the delivery of services at scale, facilitate interoperability and promote innovation. Examples: Aadhaar, UPI and DigiLocker.
• Role of DPI in Enabling AI Adoption at Scale:
  • Cost Efficiency: Shared digital infrastructure reduces costs and enables AI applications to reach a wider population.
  • Interoperability: Common digital platforms enable AI systems to integrate with existing services and databases.
  • Promoting Competition: Open and accessible infrastructure encourages innovation and reduces dependence on a single provider.
  • Preventing Technological Lock-in: Open standards and interoperability ensure portability, flexibility and choice among AI providers.
• Sectoral Applications of AI in India:
  • Agriculture: Helps farmers access agricultural advice and improve decision-making.
  • Weather Forecasting: Strengthens weather prediction and supports agricultural planning.
  • Healthcare: Assists health workers in diagnosis and improves disease screening.
  • Education: Supports teachers and expands access to educational resources.
  • Public Administration: Improves public service delivery and administrative efficiency. Examples:
  • Bharat VISTAAR: The Government of India’s digital platform for farmers, on which multiple states are developing AI chatbots in different languages.
  • Wadhwani AI: Its tuberculosis-screening tools demonstrate AI’s potential in healthcare.

AI and Employment in Developing Countries

• Lower Automation Exposure: Only 4.5% of existing jobs in low- and middle-income countries are highly exposed to automation by generative AI, compared with 14.2% in high-income countries.
• Productivity Gains: Around 16.2% of jobs in low- and middle-income countries could experience meaningful productivity gains, compared with 18.7% in advanced economies.
• Complementing Human Labour: AI is more likely to complement workers and enhance their capabilities than to replace them entirely in developing countries.

Key Challenges in Maximising AI’s Economic Impact

• Concentration of AI Capabilities: Advanced chips, computing infrastructure, data, research talent and risk capital are concentrated in a few firms and countries, creating dependence on limited AI providers and risks of market dominance.
• Inadequate Supporting Infrastructure: Limited access to electricity, connectivity, affordable devices, computing resources and local-language data can constrain AI adoption and its development benefits.
• Skill and Institutional Gaps: Inadequate AI skills among users and limited government capacity to evaluate, procure and regulate AI systems can hinder effective adoption.
• Limited Scaling of AI Applications: AI pilots often struggle to reach millions of people due to challenges in financing, institutional ownership and integration with existing systems.

Click to Know UPSC Coaching Centres in India

Way Forward

• Strengthen India’s AI Ecosystem: Build domestic research capabilities, develop Indian-language models, expand shared computing resources and strengthen deep-tech investment. 
  • Initiatives such as IndiaAI, Research, Development and Innovation Fund (RDIF) and the Anusandhan National Research Foundation (ANRF) are important steps in this direction.
• Design for Scale: Ensure every AI pilot has a credible pathway to widespread adoption, supported by financing, institutional ownership and integration with existing systems.
• Adopt an Evidence-Based Approach: Evaluate AI interventions through rigorous testing and real-world experimentation rather than assumptions, leveraging India’s scale to identify effective solutions.
• Scale Successful Applications: Expand what works and discontinue ineffective interventions, while sharing results and failures across states and ministries to facilitate institutional learning.

News Source: IE

Check Out UPSC CSE Books

Visit PW Store