India’s AI strategy marked a significant step forward as Union Minister Rajeev Chandrasekhar shared progress, with seven committees presenting a roadmap. This comprehensive plan includes the development of the India Datasets platform and indigenous AI infrastructure, operating through a public-private partnership. The key focuses are creating foundational AI models using anonymized data and establishing substantial GPU capacity for AI model training. Additionally, India AI is set to support AI chip development in collaboration with the Semicon India program, reflecting India’s commitment to responsible AI advancement.
While highlighting India’s commitment to AI advancement, it also recognizes challenges, especially the scarcity of structured data in local languages, which hampers large AI model development and concerns researchers. Chandrasekhar mentioned that the India AI report has opened consultations for the draft National Strategy for Robotics until October 31. Additionally, the expansion of AI datasets, their monetization and AI-related technology regulation will be governed by the upcoming Digital India Act, which is set to begin consultations soon.
The formal India AI report is the linchpin of the nation’s AI strategy, charting an extensive multi-year roadmap aimed at propelling India toward a $1 trillion digital economy. AI applications are set to transform various sectors including agriculture, healthcare, education, fintech, cybersecurity and digital governance, alongside linguistic advancements through the Bhashini program. Chandrasekhar also emphasized AI’s vital role in Industry 4.0 and robotics with the draft National Strategy for Robotics now open for public consultation.
Corporate concerns have emerged around AI development in the country and they are mainly focusing on accessibility and cost of compute resources. In the new India AI strategy, academia and industry including tech giants like Google and Zoho Corp will be instrumental in developing AI datasets and infrastructure. Chandrasekhar highlighted the significance of curated datasets in the strategy to support startups, researchers and businesses in building foundational AI models.
