Against the backdrop of the Global AI Summit, The Statesman spoke to BJP National Spokesperson Tuhin A. Sinha on several keys aspects concerning Modi government’s AI policy
Q: What are the key steps Modi government has taken towards advancement of AI in India?
A: Under Prime Minister Narendra Modi, India’s approach to Artificial Intelligence has steadily evolved from early vision- setting to mission-mode execution, with a clear focus on scale, inclusion, and global leadership. The foundation was laid with NITI Aayog’s National Strategy for Artificial Intelligence, which identified priority sectors such as healthcare, agriculture, education and governance, and framed AI as a tool for social empowerment rather than elite disruption. This vision has been decisively operationalised through the IndiaAI Mission, approved in 2024 with an outlay of over Rs 10,000 crore. The mission seeks to build a full-stack AI ecosystem by ensuring access to high-performance computing, shared GPU infrastructure and high-quality non-personal datasets for start-ups, researchers, and academia. A key emphasis is on developing indigenous, India-centric AI models, especially for Indian languages, public service-delivery, and sector-specific use cases, reducing dependence on imported technologies. Alongside infrastructure, the government has placed strong emphasis on human capital. Large-scale skilling initiatives, centres of excellence and integration of AI tools in education aim to prepare India’s youth for the AI economy, while fostering innovation and entrepreneurship. AI adoption in government workflows, agriculture advisories, healthcare diagnostics, and citizen services reflects a push to translate technology into everyday governance outcomes. Equally important is India’s distinctive approach to AI governance. Instead of heavy-handed regulation, the government has promoted a risk-based, ethical framework that encourages innovation while addressing concerns around transparency, bias, deepfakes and misuse. This balanced stance has strengthened India’s credibility globally. Internationally, India has emerged as a key voice in shaping inclusive AI norms, leveraging forums like the G20 and the Global Partnership on AI to advocate a “Global AI Commons” that benefits the Global South. Taken together, the Modi government’s AI strategy reflects a coherent blend of vision, investment, governance, and diplomacy-positioning India not just as an AI user, but as a responsible global AI leader.
Q: The PM has always spoken of democratisation of technology for the benefit of poor. Can you specify instances where AI has been used to benefit the poor?
A: Yes, there are concrete, on-ground instances where AI and allied digital technologies have been deployed in line with PM Modi’s idea of technology as empowerment, not privilege. What stands out is that these interventions are not urban-elite pilots but scale programmes touching rural and low-income Indians directly. One of the strongest examples is the SVAMITVA Scheme. Using AI-assisted drone mapping, geospatial analytics and automated land-record processing, the scheme has enabled millions of rural households to receive legal property cards for homes that existed for decades but had no formal recognition. For poor families, this has meant more than documentation — it has unlocked access to bank credit, crop loans, housing finance, and inheritance security.
AI-driven mapping drastically reduced disputes, human discretion and corruption that traditionally excluded the poor from property rights. In agriculture, AI tools have been integrated into platforms such as PM Fasal Bima Yojana. Satellite imagery, AI-based crop health assessment and automated claim verification have reduced delays and leakages in insurance payouts. Small and marginal farmers – the most vulnerable to climate shocks – now receive faster, more objective compensation without navigating bureaucratic hurdles. AI has also enabled precision advisories on sowing, irrigation, and pest control through vernacular apps and IVR systems, directly improving farm productivity for low-income farmers. Healthcare offers another compelling case. Under Ayushman Bharat, AI-assisted diagnostics are increasingly being used in district hospitals and health and wellness centres. AI tools for tuberculosis detection from chest X-rays, retinal screening for diabetes, and early cancer detection have significantly improved outcomes for patients who otherwise lack access to specialists. For the poor, this translates into early diagnosis, reduced travel costs, and life-saving interventions. In governance and welfare delivery, AI has strengthened targeting and reduced exclusion errors in schemes like PM Garib Kalyan Anna Yojana. Data analytics and AI-backed deduplication have ensured that subsidies reach genuine beneficiaries. Education is another frontier. AI-powered personalised learning platforms, integrated with initiatives like DIKSHA, help first-generation learners access quality content in local languages, narrowing the learning gap between rural and urban students. Taken together, these examples show that AI leadership has not been positioned as a luxury technology, but as a force multiplier for dignity, inclusion, and economic opportunity. This is the practical realisation of the PM’s long-held belief that when technology is democratised, it becomes the strongest ally of the poor.
Q: Has India started using IOT and blockchain technology as well for optimising governance?
A: Certainly. India has actively begun using both IoT and blockchain to optimise governance, and importantly, these are not lab experiments but deployed at population scale, often benefiting ordinary citizens directly. Much like AI, the Modi government has treated these technologies as instruments of trust, transparency, and efficiency. One of the clearest examples is Jal Jeevan Mission. IoT-enabled sensors are being installed in rural water supply systems to monitor water flow, pressure, and quality in real time. This allows district and state authorities to detect leakages, downtime, and contamination instantly. For rural households, this means reliable tap water, reduced dependence on tankers and accountability in service delivery. Urban governance has also seen large-scale IoT deployment through Smart Cities Mission. Cities use IoT sensors for traffic management, smart street lighting, air-quality monitoring, waste collection, and flood alerts. Automated traffic signals reduce congestion and fuel wastage, while sensor-based waste management optimises collection routes – cutting costs and improving sanitation in low-income neighbourhoods. In agriculture, IoT devices such as soil moisture sensors and automated weather stations are being used under precision farming initiatives supported by state governments and ICAR. Small farmers receive real-time advisories on irrigation and fertiliser use, lowering input costs and improving yields — a direct productivity gain for marginal cultivators. Blockchain’s biggest impact has been in land records and property governance. Maharashtra has piloted blockchain-backed land registries to create tamper-proof, time-stamped ownership records. This sharply reduces disputes, forgery, and middlemen. In welfare delivery, blockchain is being explored to track end-to-end flow of benefits in schemes such as Public Distribution System. Immutable transaction records help curb diversion of food grains and ensure entitlements reach genuine beneficiaries. Blockchain has also been integrated into the digital document ecosystem via DigiLocker, ensuring authenticity of certificates, licenses, and academic records.
Q: One of the crucial enablers in India’s AI success story has been the mammoth investment in data centres, with Vizag emerging as India’s data city. How do you see this shaping India’s global leadership in the AI space?
A: India’s push for AI leadership would have remained incomplete without solving the hard infrastructure question, and that is where the massive expansion of data centres becomes a decisive enabler. In this context, Visakhapatnam emerging as India’s data city is not incidental – it reflects a deliberate strategy to anchor AI capabilities in sovereign, scalable and globally competitive digital infrastructure. At a fundamental level, AI leadership today is inseparable from compute power, data proximity, and energy security. By attracting hyperscale data centres, Vizag positions India to host large-scale AI model training , inference workloads, and cloud services domestically. This reduces dependence on foreign jurisdictions for sensitive datasets.
Vizag’s rise is also strategically significant because it breaks the older metro-centric model of digital infrastructure. Backed by proactive policies of the Government of Andhra Pradesh, competitive power tariffs, submarine cable connectivity and port-led logistics, Vizag offers global firms a low-latency gateway between India and Indo-Pacific data routes. This makes India not just a consumer market, but a regional AI and cloud hub serving Southeast Asia, the Middle East and Africa. From an AI ecosystem perspective, data centres act as gravity wells. Their presence catalyses parallel investments in GPU clusters, AI start-ups, research labs and skilling institutions. When aligned with national initiatives like the IndiaAI Mission, this infrastructure ensures that start- ups and researchers are not priced out of compute access. In effect, the data centre boom – symbolised by Vizag – transforms India from an AI participant into an AI platform nation, giving substance to its ambition of leading not just in innovation, but in the architecture of the global AI economy.
Q: AI like all new technology carries its own perils and challenges. PM Modi has in fact been one of the early proponents of “Responsible AI” usage. Can you outline this vision?
A: Prime Minister Modi has consistently articulated a vision of Responsible AI that seeks to balance technological ambition with ethical restraint, social trust, and human dignity. For him, AI is not merely a productivity tool or a geopolitical asset; it is a civilisational technology whose impact must be guided by democratic values. At the core of his approach is the belief that AI must augment human capability, not replace human agency. The PM has repeatedly cautioned against unchecked automation that could deepen inequality, displace livelihoods or concentrate power in the hands of a few global actors. Instead, he has argued for AI systems that are inclusive, transparent, and accessible – particularly to developing societies and the poor. A second pillar of his Responsible AI vision is trust and accountability. He has emphasised safeguards against bias, misinformation and deep fakes, stressing that technology which erodes public trust ultimately weakens democracy. This has translated into India’s preference for risk-based regulation rather than blanket bans – encouraging innovation while insisting on transparency, traceability and human oversight. Third, PM Modi has framed Responsible AI as a global responsibility. At multilateral forums, he has called for international cooperation, shared norms and a “Global AI Commons” to prevent monopolisation of data, compute and models by a few countries or corporations. Ultimately, PM Modi’s Responsible AI vision reflects India’s broader governance philosophy: technology should empower the weakest, respect human values, and serve as a force for collective good-never as an unaccountable master of society.