The AI Challenge How to Maximise Economic Impact, Spread Gains Evenly

UPSC Syllabus: Gs Paper 2- Science and Technology

Introduction

Global AI investment has centred on advanced models, chips and data centres, encouraging the belief that gains will go to the companies building them. However, the World Bank Group’s World Development Report 2026: The Promise of Artificial Intelligence argues that development gains depend on applying AI to practical problems at scale. For India, the challenge is to adapt AI to local needs and spread its benefits widely.

AI as a Driver of Inclusive Economic Growth

1. Productivity and Economic Growth: AI can sustain economic growth by improving productivity, expanding access to expertise and making public services more effective.
2. Lower Risk of Job Automation: Only 4.5% of jobs in low- and middle-income countries are highly exposed to generative AI automation, compared with 14.2% in high-income countries.
3. Potential for Worker Productivity: Another 16.2% of jobs in low- and middle-income countries could experience meaningful productivity gains, compared with 18.7% in advanced economies.
4. Complementing Human Labour: AI is more likely to support the work of many employees in developing countries than replace them, increasing their capabilities and efficiency.
5. Affordable, Task-Specific Tools: AI applications designed for specific tasks can make useful expertise more accessible to businesses, households and public institutions.
6. Improving Public Service Delivery: AI can assist teachers, support medical diagnosis, improve agricultural advice and strengthen public administration, expanding access to essential services.

India’s Potential to Maximise AI Benefits

1. Strength in Technology Deployment: India’s experience in deploying technology at population scale provides a strong foundation for applying AI to practical development challenges.
2. Agricultural Productivity: In Baramati, AI-supported farming reportedly increased sugarcane yields by 40% while reducing water and fertiliser use by 30%, demonstrating the potential for resource-efficient agriculture.
3. Healthcare Screening: AI-based tuberculosis detection has reportedly increased detection by 35%, while Wadhwani AI’s screening tools demonstrate the potential to strengthen healthcare delivery.
4. Weather Forecasting: India combined multiple AI models to provide monsoon forecasts and farming advisories to millions through text, voice and AI-powered services, predicting the unusual 2025 monsoon.
5. Multilingual Farmer Services: Bharat VISTAAR and state-level AI chatbots can provide farmers with locally relevant information in multiple languages, improving access to agricultural advice.
6. Agricultural and Animal Health Applications: Gujarat’s AgriStack serves 5 lakh farmers, while the Sarlaben animal-health initiative reportedly benefits 3 crore cattle and their farmers.
7. Applications Across Sectors: AI is being deployed in education, governance, financial services and public services, showing its potential beyond agriculture and healthcare.

Key Challenges in Scaling AI for Development

1. Concentration of AI Resources: Advanced chips, computing power, data, research talent and investment remain concentrated among a few firms and countries, limiting wider access.
2. Dependence on Major Providers: Although competition has made leading models relatively affordable, dependence on a small number of providers creates risks and may increase their market power.
3. Inadequate Physical Infrastructure: Reliable electricity, connectivity, affordable devices and computing resources are essential for the effective deployment of AI.
4. Shortage of Local-Language Data: AI systems need suitable local-language data to respond effectively to India’s linguistic diversity and specific development needs.
5. Gaps in Digital Skills: People need the skills to use AI effectively, while workers and enterprises require greater capacity to integrate it into their activities.
6. Limited Institutional Capacity: Governments need the ability to evaluate, procure and regulate AI systems so that technology delivers measurable public benefits.
7. Difficulty in Scaling Successful Pilots: AI applications may work in limited settings but require financing, institutional ownership and integration with existing systems to reach millions of people.
8. Weak National AI Preparedness: Only one of the world’s 25 low-income countries had published a national AI strategy, indicating gaps in preparedness among countries with substantial potential gains.

Government Initiatives to Strengthen India’s AI Ecosystem

1. Digital Public Infrastructure: Aadhaar, UPI, DigiLocker and emerging data-sharing systems provide shared infrastructure that lowers costs, enables interoperability and supports innovation.
2. Open Architecture and Competition: UPI’s open architecture offers a model for AI adoption by reducing dependence on a single provider and supporting competition, portability and flexibility.
3. IndiaAI Compute Capacity: The IndiaAI Mission seeks to improve access to computing resources, helping expand AI development and adoption beyond a few large technology companies.
4. Indigenous Models and Datasets: The Mission supports indigenous foundation models through the IndiaAI Innovation Centre and datasets through AIKosh, strengthening domestic AI capabilities.
5. Application Development and Skills: Its application development and FutureSkills pillars aim to promote practical AI solutions and build the human capabilities needed to use them.
6. Startup Financing and Research: IndiaAI Startup Financing, ANRF and RDIF support the broader effort to strengthen innovation, research and deep-tech investment.
7. Safe and Trusted AI: The Mission supports bias mitigation, algorithm auditing, explainable AI, privacy-preserving systems and deepfake detection, alongside institutional mechanisms for AI governance and safety.
8. State-Level AI Innovations: Andhra Pradesh’s Navachetana screens children for developmental delays, Maharashtra’s MahaVISTAAR AI supports farmers, Meghalaya’s EdskGrid strengthens education governance, and Vyuhaa-Cerviai supports point-of-care cervical cancer screening.

Way Forward

1. Design for Scale: Every AI pilot should have a clear route to wider adoption, backed by financing, institutional ownership and integration with existing systems.
2. Adopt a Full-Stack Approach: Successful deployment requires software, skilled people and supporting institutions working together, rather than technology operating in isolation.
3. Test Through Evidence: India’s scale makes rigorous evaluation feasible, allowing policymakers to test applications under real-world conditions before expanding them.
4. Scale What Works: Successful interventions should be expanded across states and ministries, while ineffective approaches should be discontinued.
5. Share Lessons and Failures: Systematic sharing of results can help governments learn from experience instead of repeatedly rediscovering effective approaches or repeating mistakes.
6. Adapt AI to Local Needs: India should prioritise cost-effective tools suited to its languages and development priorities rather than trying to match frontier AI companies’ enormous investments.
7. Strengthen Public Institutions: Governments must improve their capacity to evaluate, procure and regulate AI while remaining flexible as the technology evolves.
8. Ensure Inclusive and Responsible Adoption: AI policies should preserve competition, contain risks, build public trust and ensure that productivity gains reach citizens, enterprises and institutions widely.

Conclusion

India’s AI opportunity lies in turning technological advances into broad-based productivity gains. This requires affordable access, local adaptation, strong infrastructure, skilled people and capable institutions. By evaluating solutions, scaling what works and governing AI responsibly, India can spread benefits across sectors and communities and offer useful lessons for the Global South.

Question for practice:

Discuss how India can maximise the economic benefits of artificial intelligence while ensuring that its gains are distributed widely across society.

Source: Indian Express; PIB