India’s Growing AI Ecosystem | Gist of Rajya Sabha TV / RSTV (now Sansad TV) - UPSC PDF Download

Why in News? 

 India's advancements in artificial intelligence (AI) for public welfare and national development have gained recognition, especially after the Prime Minister's address at the AI Action Summit, 2025 in Paris. 

 The country is making significant progress in promoting ethical AI practices, developing foundational models, and enhancing data access. 

•  India's efforts in AI are considered crucial for global technology collaboration and tackling societal challenges. 

Artificial Intelligence (AI) Action Summit, 2025 

AI Action Summit, 2025

 The AI Action Summit, 2025 is a global event where leaders, policymakers, tech experts, and industry representatives come together to discuss important issues related to AI governance, ethics, and its impact on society.

 This summit in Paris is the third in the series, following the Bletchley Park Summit in the UK (2023) and the Seoul Summit in South Korea (2024). 

Key Highlights from Previous Summits:

• Bletchley Park Declaration: Involving 28 countries, this declaration advocated for safe, human-centric, and responsible AI practices. 
• Seoul Summit: Participating 27 nations reaffirmed the importance of international cooperation and proposed the establishment of a network of AI Safety Institutes. 

How is India Advancing AI for Development Across Various Sectors? 

 India is making significant strides in its AI journey through the India AI Mission, backed by a budget of Rs 10,372 crores. The mission aims to enhance AI development by focusing on seven key areas, including improving access to Graphic Processing Units (GPUs), creating AI-ready data sets, and supporting AI application development. 

 One of the mission's priorities is to build a skilled workforce in AI. This involves offering fellowships to students at various levels and setting up data labs across the country. These labs will train young people as data scientists and annotators to meet the increasing demand for AI-related jobs. 

•  The mission also includes plans to assist startups at different stages, from pre-seed to mature, to foster innovation in the AI sector. 
•  Additionally, the government is working on developing its own large language model (LLM) under the IndiaAI Mission, aiming to address specific Indian contexts and biases. 
•  A domestic foundational AI platform tailored to India's unique needs, languages, and cultures is expected to launch by the end of 2025. 

 The government is actively engaging with multiple developers for this initiative, with initial funding directed towards AI-based applications in agriculture, learning disabilities, and climate change. 

 In a bid to strengthen its AI capabilities, India plans to develop its own GPU within the next 3-5 years, utilizing open-source or licensed chipsets. 

•  The government is also rolling out 18,000 high-end GPU-based computing facilities for AI development, with 10,000 already in place. 
•  These GPUs are being procured under the India AI Mission, with Rs 2,000 crore allocated in the 2025-26 Union Budget for the mission. 
•  A common facility is set to be launched, allowing startups and researchers to access high-end GPUs at Rs 150 per hour, with a 40% subsidy for end users. 
•  This initiative aims to provide affordable access to computational power for AI development, particularly benefiting smaller entities and academic institutions. 
•  India's collaboration with NVIDIA seeks to enhance AI computing capabilities through the establishment of data centers. 

 At the AI Action Summit co-chaired by India and France, significant announcements were made, including the establishment of a foundation for public interest AI with a €400 million investment and a Coalition for Sustainable AI to promote energy-efficient AI development. 

 India is positioning itself as a global leader in ethical AI practices, emphasizing energy-efficient solutions and inclusive development during its G20 presidency. Through initiatives like AI for India 2030, the country aims to advance its socio-economic goals while contributing to the global dialogue on responsible AI governance. 

 Ongoing projects in collaboration with academic institutions focus on watermarking, identifying deep fakes, and machine unlearning, a technique that allows AI systems to intentionally discard specific data, particularly incorrect, biased, outdated, or sensitive information. 

 To drive India's AI ecosystem forward, the government has established several AI centers of excellence in collaboration with top academic institutions, targeting sectors such as agriculture, healthcare, and smart mobility. 

•  In addition to existing centers, a new Centre of Excellence for AI in education will be set up with an outlay of Rs 500 crore. 
•  The government also plans to establish five National Centres of Excellence for Skilling to equip youth with relevant industry skills in collaboration with global partners. 

 India is expanding its digital public infrastructure solutions globally, with countries adopting biometric identity platforms similar to Aadhar. The Unified Payments Interface (UPI) is being used worldwide, and countries like Brazil are developing similar digital payment systems. 

 India is sharing its digital solutions in areas like data storage, healthcare, and AI with global partners, particularly targeting low- and middle-income countries. 

What are the Challenges India Faces in the Field of AI? 

• Computational Access: One major challenge is the high computational costs associated with large AI models. As models grow, so do the expenses, making them unaffordable for widespread adoption in India, especially for tasks like inferencing. For instance, the average cost of computing is expected to climb 89% between 2023 and 2025, driven by the increasing use of generative AI. 
• Data Availability: Another challenge is the scarcity of AI-ready data sets, particularly for Indian applications. This limits the ability to train and develop effective AI models tailored to local needs. 
• Dependency on Foreign Models: India currently depends on AI models developed abroad, limiting the ability to fully leverage homegrown technologies. Proprietary models like GPT-4 require licensing, making India reliant on external pricing and policy changes. This dependency can lead to increased costs and reduced control over AI applications. 
• Infrastructure:. significant challenge lies in accessing the necessary AI computing power. India relies on foreign companies like NVIDIA for critical AI chips and GPUs, which creates limitations in scaling AI solutions. This reliance on imported hardware can hinder the development and deployment of AI technologies. 
• Diversity: India’s vast linguistic, cultural, and geographical diversity makes it challenging to build AI solutions that cater to all regions. Variations in accents, dialects, and languages across states add complexity to developing effective AI applications, especially in areas like speech recognition and translation. For example, AI models need to accommodate 22 official languages and numerous dialects to be effective across the country. 
• 6. Ethical Issues: Ethical concerns and the potential misuse of AI, such as deepfakes or misinformation, remain significant. Ensuring that AI is used responsibly and ethically is a major challenge, given the rapid advancements and potential for misuse. 

Way Forward 

• Cost-Effective Models: India aims to develop affordable AI models and infrastructure to reduce high computational costs. The government plans to launch an indigenous AI model costing under Rs. 100 per hour, with a 40% subsidy, making it accessible to startups and researchers. 
• Data Availability: Enhancing data availability is crucial for AI innovation. The India AI Datasets Platform aims to provide seamless access to high-quality non-personal datasets, creating a unified platform for AI-ready datasets. 
• Sovereignty: Developing a sovereign foundational AI model is essential to reduce dependency on foreign models. The IndiaAI Mission focuses on building such a model to cater to India's diverse linguistic and cultural needs. 
• Infrastructure: To overcome limitations in computational infrastructure, India plans to invest in building its own AI computing power. The government aims to procure 10,000 GPUs within the next 18-24 months to boost AI research and development. 
• Inclusive Models: AI solutions need to be tailored to India's diverse linguistic, cultural, and geographical landscape. The AI for India 2030 initiative emphasizes inclusive and responsible AI adoption to address the nation's socio-economic fabric. 
• Ethical AI: Ensuring ethical AI use involves establishing robust guidelines and frameworks. India's Responsible AI for All framework by NITI Aayog provides a comprehensive approach to AI governance.