The AI challenge: How to maximise economic impact, spread gains evenly, Pg10

Key Highlights:

• The World Bank Group’s ‘World Development Report 2026: The Promise of Artificial Intelligence’ emphasizes AI's potential for growth, productivity, public services, and opportunity.
• The report suggests major AI gains will come from practical application at scale, not solely from building frontier models.
• Only 4.5% of jobs in low- and middle-income countries are highly exposed to generative AI automation, compared to 14.2% in high-income countries.
• India is well-positioned to leverage AI due to its rapid economic growth and experience with population-scale technology deployment via digital public infrastructure.
• Key challenges for AI adoption include concentration of resources (chips, compute, talent) and lack of complementary investments (electricity, connectivity, skills).
• Initiatives like IndiaAI, Research, Development and Innovation Fund (RDIF), and Anusandhan National Research Foundation (ANRF) are crucial for India's AI advancement.

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Detailed Insights:

• The global AI narrative often overemphasizes intelligence generation, leading to a narrow focus on model-building companies.
• Economic value from general-purpose technologies historically accrues significantly to downstream users who adapt and diffuse them.
• India's Digital Public Infrastructure (e.g., Aadhaar, UPI, DigiLocker) demonstrates successful technology deployment at scale, reducing costs and fostering innovation.
• For developing countries, AI is more likely to complement workers, enhancing capabilities in agriculture, healthcare, education, and public administration.
• Examples like Bharat VISTAAR (digital platform for farmers) and Wadhwani AI’s tuberculosis-screening tools show AI's tangible benefits in India.
• India's approach should prioritize open architectures, similar to UPI, to promote competition and avoid technological lock-in.
• Strategic capabilities for India include domestic research, Indian-language models, shared compute resources, and a stronger deep-tech investment ecosystem.
• The IndiaAI Mission is a central-sector scheme approved in March 2024 with an outlay of ₹10,371.92 crore over five years to build India's AI ecosystem.
• The Research, Development and Innovation Fund (RDIF) is a ₹1 lakh crore initiative launched in November 2025 to strengthen deep-tech R&D, operating under the Department of Science and Technology (DST) and ANRF.
• The Anusandhan National Research Foundation (ANRF), established by the ANRF Act, 2023, is India's apex body for funding and directing scientific research and innovation.
• Three principles for India's AI strategy are designing for scale, evidence-based testing, and scaling successful initiatives while discontinuing ineffective ones.

Key Concepts Involved:

• Digital Public Infrastructure (DPI): Shared digital platforms and systems (like Aadhaar, UPI) that enable public and private services at scale.
• Generative AI: Artificial intelligence capable of producing new content, such as text, images, or other data, often based on learned patterns.
• Technology Readiness Level (TRL): A measurement system used to assess the maturity of a particular technology, typically from TRL 1 (basic principles observed) to TRL 9 (actual system proven in operational environment).
• Deep-tech: Technologies based on substantial scientific or engineering breakthroughs, often requiring significant R&D investment and longer development cycles.