The Next DPI: Can India Build Public AI for All?
After successfully creating public digital infrastructure for identity, payments, and data, the next frontier for India could be 'commoditising' Artificial Intelligence. But the challenges are formidable.
The Groundwork: Understanding India's Digital Revolution
To grasp the debate around a public Artificial Intelligence (AI) infrastructure, one must first understand the ecosystem that makes such a conversation possible in India. The country's success with Digital Public Infrastructure (DPI) over the past decade provides the blueprint and the ambition for this next technological leap.
(1) KEY TERMS
- Digital Public Infrastructure (DPI): A set of shared, open, and interoperable digital systems (like digital ID, payment rails, and data exchanges) built and managed by the public sector to deliver essential services and serve as a platform for private sector innovation.
- Unified Payments Interface (UPI): An instant real-time payment system developed by the National Payments Corporation of India (NPCI) that facilitates inter-bank peer-to-peer and person-to-merchant transactions. It was launched in April 2016.
- Data Empowerment and Protection Architecture (DEPA): A framework within the 'India Stack' that aims to give individuals control over their data. It allows them to share their data securely with third parties through licensed Account Aggregators, regulated by the Reserve Bank of India (RBI).
(2) BACKGROUND & TIMELINE
The foundation of India's DPI was laid over several years. The Unique Identification Authority of India (UIDAI) was established in 2009, receiving statutory backing with the Aadhaar Act in March 2016. That same year, two other pivotal events occurred. In April 2016, the NPCI launched UPI, which transformed digital payments. Later, the demonetisation of high-value currency notes in November 2016 provided a massive, albeit disruptive, push towards digital transactions.
A crucial catalyst was the dramatic fall in data costs. Following the launch of Reliance Jio's 4G services in September 2016, the price of one gigabyte of data in India fell from around $4 to under 30 cents by 2019. This affordability revolution brought an estimated 500 million new users online in half a decade, creating the mass user base upon which the DPI could thrive. The final piece of the current stack, the Account Aggregator framework based on DEPA, became fully operational after the RBI licensed the first operators in September 2021.
(3) INSTITUTIONAL FRAMEWORK
Several key bodies oversee India's DPI ecosystem:
- Ministry of Electronics and Information Technology (MeitY): The nodal ministry for driving the 'Digital India' programme and formulating policy on IT, electronics, and the internet.
- Unique Identification Authority of India (UIDAI): A statutory authority established under the Aadhaar Act, 2016, responsible for issuing Aadhaar numbers and managing the identity database.
- National Payments Corporation of India (NPCI): An umbrella organisation for operating retail payments and settlement systems in India, established by the RBI and the Indian Banks' Association (IBA) in 2008. It is the entity that owns and operates the UPI platform.
What is the core idea of an 'AI DPI'?
The central proposition is to extend the principles of India's successful Digital Public Infrastructure (DPI) model to the domain of Artificial Intelligence. The 'India Stack'—a set of open APIs and digital public goods—has already 'commoditised' three critical layers: identity (Aadhaar), payments (UPI), and data sharing (DEPA). The argument, as articulated by proponents like Srivatsa Krishna in The Hindu, is that 'intelligence' itself should be the fourth layer. This would involve creating foundational AI models, curated public datasets, and accessible computing infrastructure as a public utility. The goal is to lower entry barriers for AI development, allowing startups and researchers to build applications without the prohibitive costs of training large models from scratch. This approach aims to make AI affordable and ubiquitous, much as UPI made digital payments a near-zero-cost service.
What is the government's position and existing framework?
The Government of India has signalled strong intent to become a global leader in AI. This strategy is being operationalised through the IndiaAI Mission, which received Cabinet approval in March 2024 with a total outlay of ₹10,372 crore for five years. The mission's objectives include establishing large-scale AI compute infrastructure, developing indigenous Large Language Models (LLMs), and creating datasets platforms. According to a Press Information Bureau release dated March 7, 2024, the mission will establish a scalable AI computing ecosystem of at least 10,000 GPUs (Graphics Processing Units) through public-private partnerships. Furthermore, an 'IndiaAI Datasets Platform' will be developed to provide researchers and startups with access to quality non-personal datasets, a critical component for training AI models. The government's rationale is rooted in fostering domestic innovation, ensuring technological self-reliance (Atmanirbhar Bharat), and harnessing AI for public services in sectors like agriculture and healthcare.
What are the potential benefits of this approach?
A public AI infrastructure could replicate the bottom-up innovation spurred by UPI. With 1.4 billion people enrolled in Aadhaar and UPI processing over 14 billion transactions monthly (as of mid-2024, per NPCI data), the existing DPI has demonstrated its capacity for scale. An AI DPI could similarly democratise access to powerful technology. Small and medium enterprises could leverage public AI models to improve efficiency, create new products, and compete with larger corporations. For instance, an agri-tech startup could use a government-trained agricultural AI model to provide crop disease diagnostics to farmers via a simple mobile app. This would help prevent the concentration of AI power in the hands of a few global tech giants, fostering a more equitable digital ecosystem. It also holds the potential to create India-specific solutions trained on diverse local data, addressing unique challenges in regional languages and governance.
What are the significant challenges and criticisms?
Despite the ambitious vision, the path to an AI DPI is fraught with challenges more complex than those faced during the creation of Aadhaar or UPI. A primary concern is the immense financial cost. The approved ₹10,372 crore for the IndiaAI Mission is a starting point, but building and maintaining state-of-the-art AI infrastructure is a continuous, multi-billion-dollar endeavour. Researchers at the Centre for Internet and Society, for instance, question whether public funds can sustainably compete with the R&D budgets of global technology corporations. Another significant hurdle involves data privacy and ethics. The creation of massive public datasets, even if anonymised, carries re-identification risks under the framework of the Digital Personal Data Protection (DPDP) Act, 2023. Concerns have been raised about provisions like Section 7(b), which allows for deemed consent for state functions, and how they will be reconciled with the Supreme Court's K.S. Puttaswamy v. Union of India (2017) judgment affirming the Right to Privacy. Finally, there is a risk that a dominant, state-sponsored AI platform could inadvertently stifle private sector innovation and create a single point of failure.
How does India's proposed model compare globally?
India's approach is distinct from the two dominant global models. The United States has a largely private-sector-led model, where companies like OpenAI, Google, and Meta drive foundational AI research. The government's role is primarily in funding basic research and, increasingly, in regulation. In contrast, China employs a state-driven model, where the government works closely with national tech champions like Baidu and Alibaba, leveraging vast state-held data to achieve strategic AI dominance. India's proposed AI DPI is a 'third way'—an attempt to use public infrastructure to create a level playing field for the private sector, much like it did with payments. While countries like Estonia have a strong digital identity system and Brazil has the successful Pix payments platform, no other country has integrated identity, payments, and data into a cohesive public stack at India's scale, making its potential AI layer a globally unique experiment.
Why This Matters Now
The global competition for AI leadership has significant economic and geopolitical dimensions. For India, developing sovereign AI capabilities is a strategic imperative to avoid becoming a 'digital quarry'—a passive provider of raw data for foreign AI models while the economic value is captured elsewhere. The push for a domestic AI infrastructure aims to move the country up the value chain from a data source to an 'intelligence' hub. This policy choice is critical as India's digital economy is at an inflection point, with the potential to add trillions to its GDP, making the architecture of its AI ecosystem a foundational choice for future growth.
Likely Trajectory in the Next 1-5 Years
The path forward will likely be incremental. The IndiaAI Mission, with its five-year timeline ending in 2029, will be the primary vehicle. The initial phase is expected to focus on building the core compute infrastructure (the 10,000+ GPU cluster) and launching the 'IndiaAI Datasets Platform'. The government will likely partner with academic institutions and private consortiums to develop foundational models, particularly for Indian languages. Simultaneously, the regulatory landscape will evolve. A comprehensive Digital India Act, intended to replace the two-decade-old Information Technology Act, 2000, is anticipated to be tabled in Parliament and will contain significant provisions governing AI. The evolution of this legislation, alongside judicial interpretations of the DPDP Act, 2023, will shape the guardrails for the AI DPI.
Governance and Societal Implications
A successful public AI infrastructure could unlock immense productivity gains and improve public service delivery. However, a state-controlled AI ecosystem also raises complex questions about surveillance, algorithmic bias, and the concentration of power. The core governance challenge is to create a system that is open, accountable, and respects fundamental rights, particularly the Right to Privacy. The project's success will therefore be not just a technological feat, but a test of India's democratic institutions to build guardrails that ensure 'AI for All' does not come at the cost of individual liberties. This represents a defining challenge between the promise of collective progress and the imperative of individual freedom.