India’s path to AI autonomy

India’s unique approach to AI autonomy: A three-pillar strategy

India is taking a distinctive approach to the global race for artificial intelligence (AI) supremacy. While the United States and China focus on AI for economic dominance and national security, India’s vision revolves around AI autonomy through the development of homegrown AI solutions that are closely linked to its development goals. This approach seeks to position India as a prominent global AI leader through a three-pillar strategy that distinguishes it from other major nations. India’s vision of AI autonomy is based on:

• Democratizing AI through open innovation: Leading the development of open-source models and platforms that make AI more accessible and adaptable to India’s local needs including the Bhashini platform, which incorporates Indian languages in large language model processing, and the iGOT Karmayogi online learning platform for government training.
• Public-sector-led development applications: Implementing AI solutions to address critical development challenges through government-led initiatives in healthcare, agriculture, and education, ensuring that technology meets societal needs.
• Global leadership in AI for sustainable development: Championing the integration of AI to achieve the Sustainable Development Goals (SDGs) on a global scale while pushing ethical AI governance and South-South collaboration.

This strategy seeks to establish India as a global AI leader while addressing pressing social issues, closing economic gaps, and improving the quality of life for its diverse population of over 1.3 billion people.

India’s journey toward AI autonomy goes beyond technological independence; it creates a narrative in which innovative AI technologies drive inclusive growth. This philosophy is reflected in the “India AI” mission and its National Strategy for AI, which positions India as both an adopter and developer of AI technologies and a global hub for ethical and development-oriented AI innovation.

India’s AI landscape: A vision of innovation and strategy

The Indian AI ecosystem is a dynamic landscape shaped by government initiatives, private-sector innovation, and academic research. There has been a notable increase in AI-focused start-ups in recent years, with the National Association of Software and Service Companies (NASSCOM) reporting over 1,600 in 2023. This growing sector highlights India’s technological capabilities and entrepreneurial spirit in tackling local challenges.

Several strategic government initiatives at the core of this ecosystem have paved the way for India’s advancements in AI. The India AI mission, launched in 2023, is a government initiative to build a comprehensive ecosystem to foster AI innovation across various sectors in India. Spearheaded by the Ministry of Electronics and Information Technology (MeitY), it focuses on developing AI applications to address societal challenges in healthcare, education, agriculture, and smart cities while promoting responsible and ethical AI development.

IndiaAI reflects the country’s ambitions to become a global AI powerhouse and is supported by the National AI Strategy, created by the National Institution for Transforming India (NITI Aayog). The strategy provides a comprehensive road map for AI adoption in those sectors targeted by IndiaAI.

What sets these initiatives apart from AI strategies in other countries is their emphasis on using AI for social good. For instance, the government of India organized the Responsible AI for Social Empowerment (RAISE) initiative in 2020, preceding the current AI hype. This demonstrates India’s commitment to ethical AI development, and such initiatives align with India’s National Development Agenda 2030, positioning AI as a driver of economic growth and a crucial enabler for achieving SDGs.

Democratizing AI through open innovation

India is making significant progress in promoting open-source AI development, fostering inclusivity and collaboration within the global AI community. Open-source frameworks, driven by collaborative innovation, offer transparency, interoperability, and scalability—essential qualities for a diverse country like India.

The Bhashini initiative, led by the MeitY, exemplifies this commitment by leveraging open-source frameworks to build natural language processing (NLP) models that support twenty-two official Indian languages and numerous dialects. This project goes beyond basic language processing; it signifies India’s dedication to AI democratization by making these models and datasets freely available to developers and start-ups.

The iGOT Karmayogi platform showcases the scalability of open-source AI solutions to improve digital literacy in government. Designed to upskill twenty million employees, it utilizes open-source AI tools to provide personalized learning pathways, reducing costs while ensuring continuous improvement based on user feedback.

Leading academic institutions like the Indian Institute of Science (IISc) in Bangalore and the Indian Institute of Technology (IIT) Madras actively contribute to open-source AI research through global public platforms such as TensorFlow and Hugging Face. Their work encompasses various fields, including computer vision for healthcare, autonomous vehicles, and environmental monitoring.

For Indian start-ups, using open-source AI models or systems provides significant benefits such as lower costs, greater customization flexibility, access to a larger developer community, the ability to tailor models to specific Indian languages and dialects, and enhanced data security by allowing deployment on premises, making it ideal for building localized AI solutions while maintaining control over sensitive data.

In August 2024, Meta’s open-source Llama model reached a significant milestone of 350 million cumulative downloads since the release of Llama 1 in early 2023.. India has emerged as one of the top three markets globally for this model. Several Indian start-ups and well-known consumer apps, including Flipkart, Meesho, Redbus, Dream11, and Infoedge, have announced their integration of Llama into their applications.

Additionally, IBM Elxsi, a partnership between IBM and Tata Elxsi, India’s largest technology company, focuses on designing local digital engineering solutions, like using open-source models to develop AI-powered edge network solutions for rural and remote areas, enhancing AI accessibility while reducing latency and energy consumption.

The democratization of AI through open-source initiatives is critical to India’s development trajectory and technological autonomy. This approach enables rapid, cost-effective AI adoption across India’s diverse sectors and regions, with tangible results already visible: The development cycle for AI solutions has been reduced from years to months, as evidenced by the rapid deployment of language models via the Bhashini initiative, which now serves millions in their native languages. Unlike the West, where most AI development is primarily driven by private companies with proprietary technologies, India’s adoption of an open-source-first approach has led to an independent ecosystem in which government initiatives, academic institutions, and private-sector innovations coexist.

The public-sector role in developing applications to address India’s unique challenges

The profound socioeconomic challenges that India’s 1.3 billion people face have fundamentally shaped its approach to AI.

India faces critical healthcare challenges: 70 percent of healthcare infrastructure is concentrated in urban areas serving only 30 percent of the population, and the doctor-patient ratio stands at 1:1,511, far below the World Health Organization’s recommended 1:1,000.

The education sector struggles with fundamental gaps, as 250 million Indians lack basic literacy skills, with only 27 percent having access to internet-enabled devices for online learning, further complicated by the country’s diversity of twenty-two official languages and 1,600 dialects.

Agricultural challenges are particularly acute, with the sector employing 42 percent of the workforce but contributing only 18 percent to gross domestic product; 86 percent are small and marginal farmers with less than two hectares of land, and 40 percent of food production is lost due to inefficient supply chains.

Financial inclusion remains a significant barrier to development, with 190 million unbanked adults, 70 percent of rural transactions being cash-based, and a stark digital gender divide where only 33 percent of women have mobile internet access compared to 67 percent of men.

The size and complexity of these challenges necessitate innovative technological solutions that are both scalable and relevant to India’s specific issues.

India’s development-focused AI vision strategically responds to these pressing issues. Rather than viewing AI solely as a tool for economic competition or technological advancement, India has positioned it as a transformative tool for closing fundamental development gaps.

AI is closing critical gaps in access and the quality of care in healthcare. Through the government’s eSanjeevani platform—India’s national telemedicine service offering patients access to medical specialists and doctors remotely via smartphones—has been revolutionary, with over one hundred million teleconsultations in 2023 and the aim of closing the urban-rural healthcare gap. The platform developed AI/machine learning models to improve data collection, quality of care, and doctor-patient consultations on eSanjeevani. The Indian Council of Medical Research’s collaborations with AI start-ups for disease prediction models in tuberculosis and diabetes paved the way for preventive healthcare interventions.

The agricultural sector is experiencing an AI revolution, driven by government initiatives, particularly through two key platforms. The mKisan portal gives more than fifty million farmers personalized SMS access to critical agricultural information, while the Agristack initiative lays the groundwork for precision agriculture by providing AI-powered advisory services for crop planning, pest control, and weather forecasting. The Indian Meteorological Department’s use of AI has improved monsoon forecast accuracy by 20 percent, significantly impacting agricultural planning.

In education, state governments have contracted with Embibe, a company that offers AI-powered learning for basic education to bridge the learning gaps and expand access to quality education. It identifies gaps in knowledge and creates content that addresses them by studying data from student interactions. FutureSkills Prime, an initiative of the National Association of Software and Service Companies, provides AI skills training—and has developed a large AI talent pool, with more than 2.5 million technology professionals trained in AI in India. According to the 2025 Global Workplace Skills Study by Emeritus, 96% of Indian professionals are using AI and generative AI tools at work, significantly higher than the 81% in the US and 84% in the UK. This workforce advantage has made India a preferred destination for global companies seeking skilled AI professionals.

India’s public-sector-led approach to AI development uniquely integrates technology with development priorities. The government’s strategic leadership in deploying AI solutions in healthcare, agriculture, education, and finance demonstrates a unique model in which technology acts as a force multiplier for development efforts. Unlike many developed countries, where private-sector innovation drives AI advancement, India’s government-led initiatives ensure that AI solutions address fundamental development challenges on a large scale.

By combining scale, accessibility, and local relevance, India’s public-sector leadership in AI deployment is a unique model for other developing countries facing similar challenges, demonstrating that technology can effectively accelerate inclusive development when guided by clear public-policy goals.

Shaping tomorrow: India’s position in global AI leadership and development

India’s global AI leadership position is uniquely shaped by proactive government policies and collaborative initiatives. As a founding member of the Global Partnership on Artificial Intelligence (GPAI), India has used its presidency in 2024 to advance key priorities such as democratizing access to AI skills, addressing societal inequities, promoting responsible AI development, and applying AI in critical sectors such as agriculture and education.

AI plays a critical role in India’s vision to achieve all seventeen SDGs by 2030. India also aims to be one of the top three countries in AI research, innovation, and application by 2030, which reflects a larger ambition: to create a more equitable and sustainable global AI landscape. This unique approach balances technological autonomy and inclusive development, by aligning AI initiatives with socioeconomic priorities to address India’s unique challenges.

However, the expansion of India’s AI ecosystem faces several critical challenges, including the demand for an advanced AI compute infrastructure, developing accessible AI tools, ensuring data privacy, and mitigating algorithmic bias at scale. Addressing these issues requires multistakeholder collaboration between the government, local industry leaders, and academic institutions.

As India progresses in its AI journey, its experience provides valuable insights into how to use AI to drive socioeconomic development. The country’s development-focused approach to AI adoption and governance may serve as a model for other developing countries looking to capitalize on AI’s potential for inclusive growth.

Mohamed “Mo” Elbashir is a nonresident senior fellow at the ’s GeoTech Center, as well as Meta Platforms’ global infrastructure risk and enablement manager. With over two decades of experience, he specializes in global technology governance, regulatory frameworks, public policy, and program management.

Kishore Balaji Desikachari is the executive director for government affairs at IBM India/South Asia. With over thirty years of leadership experience at Microsoft, Intel, and Hughes, he is a recognized regional policy commentator on AI, quantum computing, semiconductors, trade, and workforce strategies.

Image: Credit: blackboard via Adobe Stock