India's ambition to build inclusive and trustworthy artificial intelligence (AI) for governance will depend on overcoming structural constraints around data, computing infrastructure, indigenous foundation models and skilled talent, Kavita Bhatia, Scientist G at the Ministry of Electronics and Information Technology (MeitY), said on Wednesday.
Speaking during the "AI Governance for All" panel at the 29th National Conference on e-Governance, Bhatia outlined the country's AI roadmap while highlighting the challenges that must be addressed to ensure AI benefits citizens at scale.
"Building trustworthy and scalable AI for governance requires addressing structural resource constraints while maintaining integrity and fairness in how AI systems learn and make decisions," she said during her presentation.
1 June 2026
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Four Pillars Holding Back AI Adoption
Bhatia identified four critical resource constraints that continue to limit AI adoption in governance—access to quality datasets, affordable computing infrastructure, indigenous AI foundation models and skilled AI professionals within government departments.
She said India still faces challenges due to siloed government datasets, limited availability of AI-ready data, inadequate access to scalable and secure compute resources, and the absence of large AI models trained on India's languages, cultural contexts and socio-economic realities.
She also stressed that ministries and government departments require a larger pool of AI and data professionals to successfully integrate artificial intelligence into public service delivery.
India's AI Momentum
Despite these challenges, Bhatia said India has made significant progress in strengthening its AI ecosystem following the launch of the IndiaAI Mission in March 2024.
Citing global AI vibrancy rankings, she said India improved from seventh place in 2023 to fourth in 2024, before climbing to third globally in 2025, reflecting the country's rapidly expanding AI capabilities.
She added that India's digital transformation has been built on population-scale digital public infrastructure, a large technology workforce and a thriving startup ecosystem.
According to Bhatia, India today has a technology workforce of around six million professionals, the world's second-largest pool of AI, machine learning and big data talent, and more than 200,000 startups working across AI, electronics, cybersecurity, space technology and other emerging sectors.
She also noted that domestic capabilities in electronics design, manufacturing and systems integration continue to expand, while a large share of Indian enterprises have already begun deploying AI solutions.
AI for Public Healthcare
Bhatia also underscored AI-powered healthcare solutions that are already being deployed across the country. She said AI-enabled computer vision systems are helping automate chest X-ray analysis for tuberculosis detection, while the same technology is being used to identify diseases such as breast cancer and diabetic retinopathy.
She added that AI is also being used to predict patients who are at risk of dropping out of TB treatment programmes, enabling healthcare workers to intervene earlier.
Bhatia said AI tools are increasingly being adopted to support ASHA and Anganwadi workers in disease surveillance and community healthcare, with AI-based TB diagnosis systems already being implemented across nearly 25 states.
She stressed that India's AI strategy must remain focused on inclusive governance, ensuring that digital public infrastructure, indigenous AI capabilities and responsible innovation work together to improve citizen services while advancing the country's vision of Viksit Bharat 2047.
