India’s National Strategy for Artificial Intelligence

June 2018

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Strategies and Action Plans

The National Strategy for Artificial Intelligence (AI) in India outlines a comprehensive framework aimed at positioning the country as a leader in AI on the global stage, with a unique focus on inclusive growth and societal transformation. This strategy, developed by NITI Aayog, is centred around leveraging AI to drive economic growth, improve social outcomes, and address key national challenges across various sectors.

The strategy identifies three main pillars:

  1. Opportunity: Economic Impact
    AI is recognized as a new factor of production that can augment traditional factors like labor, capital, and innovation. AI’s potential lies in enabling intelligent automation, enhancing labor and capital productivity, and driving innovation across sectors. This could significantly boost India’s economic growth. According to research by Accenture, AI could increase India’s annual growth rate by 1.3 percentage points by 2035​.
  2. AI for Greater Good: Social Development and Inclusive Growth
    Beyond economic gains, AI is seen as a transformative technology that can address societal challenges. For example, AI can improve access to quality healthcare, provide real-time advisory to farmers to enhance productivity, facilitate inclusive financial growth, and contribute to building smart cities and efficient infrastructure. This approach aligns with the government’s development philosophy and aims to ensure that AI benefits are widely distributed, enhancing the quality of life for all citizens.
  3. AI Garage for 40% of the World
    India aims to position itself as a global hub for developing scalable AI solutions that can be applied in other emerging and developing economies. The diverse and complex challenges faced by India make it an ideal testing ground for AI technologies that can later be adapted for use in similar contexts worldwide.

Key Sectors for AI Intervention

The strategy focuses on five key sectors where AI can have the most significant impact:

  • Healthcare: AI can enhance access to healthcare services, improve diagnostic accuracy, personalize treatment plans, and predict disease outbreaks.
  • Agriculture: AI technologies can help increase crop yields, predict pest attacks, and provide real-time market price information to farmers.
  • Education: AI can improve educational outcomes through personalized learning, enhance teacher training, and increase access to quality education.
  • Smart Cities and Infrastructure: AI can optimize urban planning, improve public services, and enhance resource management in cities.
  • Smart Mobility and Transportation: AI can lead to smarter traffic management, enhance road safety, and promote the development of autonomous vehicles​.

Challenges to AI Adoption

Despite the potential benefits, several challenges hinder the widespread adoption of AI in India:

  • Data Availability and Ecosystems: There is a need for robust data ecosystems to support AI development. This includes access to high-quality, annotated data sets.
  • AI Expertise and Skilling: The shortage of AI experts and inadequate skilling opportunities for the existing workforce pose significant barriers.
  • Research and Development: India’s AI research capabilities need enhancement, both in quantity and quality.
  • Infrastructure: The high cost and limited availability of computing infrastructure necessary for AI development and deployment are major hurdles.
  • Ethics, Privacy, and Security: Addressing ethical concerns, ensuring data privacy, and establishing robust security frameworks are critical for responsible AI deployment​.

Strategic Recommendations

To overcome these challenges and harness AI’s full potential, the strategy recommends several initiatives:

  • Promoting AI Research: Establishing Centers of Research Excellence (COREs) focused on fundamental AI research and International Centers for Transformational AI (ICTAIs) for application-based research. These centers will collaborate with the private sector and international institutions to drive innovation.
  • Skilling and Reskilling: Implementing large-scale reskilling programs to prepare the workforce for AI-driven job transformations. This involves integrating AI education into the curriculum at various educational levels and promoting interdisciplinary research.
  • Data Democratization: Developing large foundational data sets and creating multi-stakeholder marketplaces for data and AI models to facilitate innovation and lower entry barriers for startups.
  • Ethical and Responsible AI: Establishing frameworks to ensure ethical AI development, protecting data privacy, and promoting transparency and accountability in AI systems​.

Conclusion

The National Strategy for Artificial Intelligence aims to create an ecosystem where AI can thrive, benefiting both the economy and society at large. By focusing on strategic sectors, addressing key challenges, and promoting collaborative efforts between the government, private sector, and academia, India aspires to become a global leader in AI, driving inclusive growth and solving some of the world’s most pressing challenges​.