Data-led infrastructure: Powering shift from scale to intelligence

India’s digital public infrastructure is no longer a concept under construction. It is used every day, everywhere. Aadhaar has become the backbone of identity across banking, welfare, and travel.

UPI processes billions of transactions a month, placing the power of digital finance in the hands of both a roadside vendor and a national retailer.

DigiLocker has eased reliance on paper records. ONDC is providing micro and small enterprises with a path to digital commerce. Public Wi-Fi is steadily expanding, with more access points being added across the country.

This foundation has transformed lives, but the difficult question is what comes next. A nation of 1.4 billion cannot rely solely on scale. It requires infrastructure that adapts in real time, protects against emerging risks, and responds to citizens in ways that feel personal.

That shift is already underway. Across energy, cities, identity systems, agriculture, and healthcare, technologies such as artificial intelligence (AI) and the Internet of Things (IoT) are transforming static services into responsive, intelligent networks.

#1 Energy Systems

Energy offers one of the clearest illustrations of this shift. As of March 2025, more than 22.9 million smart meters had been installed nationwide. For households, this meant bills they could finally trust. For utilities, it meant something they had never possessed before—a live view of demand across the grid.

Once this data was fed into predictive models, operations began to change. Blackouts were no longer repaired only after the fact; they were prevented before they occurred. This transition from reactive to anticipatory management marks a decisive turning point in how India manages its power networks.

#2 Urban Civic Management

Cities tell a similar story. Across 100 Smart Cities, Integrated Command-and-Control Centres are now operational. IoT sensors stream constant updates on traffic, water supply, sanitation, and waste. Administrators no longer wait for manual reports; they act on real-time evidence.

The Mumbai Metro has taken this approach further, deploying predictive maintenance tools to monitor trains and tracks. The result is safer journeys and fewer delays for millions of commuters. This is what smarter infrastructure looks like in practice—decisions guided by data before crises emerge.

#3 Identity and Financial Systems

The country’s core public platforms are also evolving. Aadhaar, UPI, DigiLocker, and ONDC are no longer static utilities. They now integrate AI to offer multilingual services, automated translation, and stronger fraud detection. Citizens who once struggled with digital systems due to language barriers can now use their own language.

Payment fraud, a long-standing concern, is being addressed more effectively through AI-driven anomaly detection. Sensitive data is increasingly hosted within national cloud systems, often built on sovereign frameworks that retain control within India. For citizens, these steps translate into a sense of trust. For policymakers, they open new pathways for inclusion.

#4 Agriculture, Healthcare, Supply Chain

The impact extends far beyond urban centres. Agriculture is beginning to benefit from sensors placed directly in fields that capture soil moisture, crop health, and micro-weather conditions. AI converts this data into actionable insights that farmers can apply immediately.

Healthcare is following a similar trajectory. Connected devices enable doctors to remotely monitor patients, while predictive tools help detect health risks earlier. Medicines moving across supply chains are tracked more accurately, reducing spoilage and shortages.

The industry and logistics sectors are also adopting connected systems to detect problems early. These are no longer pilot projects. Instead, they are becoming part of how critical sectors function every day.

Connectivity: The Enabling Backbone

All of this relies on the networks that carry the data. BharatNet has extended fibre deeper into rural districts, laying a robust foundation for the last mile. Additionally, 5G coverage now extends to 99.6% of districts in India. Together, they provide the high-speed, low-latency backbone required for real-time IoT deployments at a national scale.

Without this layer, none of the applications in cities, farms, hospitals, or factories would function reliably. Connectivity may not always be the headline, but it remains the base upon which every modern system depends.

Navigating Risks and Structural Gaps

The gains are substantial, but so are the risks. Privacy remains the most pressing concern. DPI platforms store vast amounts of personal information, making any breach potentially damaging to public trust. Local storage requirements and frameworks such as MeghRaj are steps forward, but safeguards must continue to evolve as threats become more complex.

Integration is another challenge. Many legacy systems were built long before AI and IoT became mainstream. Getting them to work together is not easy. Without common standards, platforms risk operating in isolation, weakening the broader ecosystem.

Talent, too, is critical. Running AI- and IoT-enabled platforms at a national scale demands deep technical expertise. India does not yet have this workforce at the required scale. Investments in training and capacity building must keep pace with investments in hardware, cloud, and software.

India now has the Data Protection Act and device standards in place. The next challenge is to accelerate regulatory implementation and establish clear accountability mechanisms in public services. Without these, innovation will continue to outpace governance.

Economic Value and Global Relevance

The economic implications are vast. Projections indicate that India’s digital economy could account for 20% of the country’s GDP by 2026, with AI expected to contribute as much as USD 400 billion by 2030. But there is also strategic value. India’s DPI model—an approach that blends open public platforms with private-sector innovation—is attracting global attention. Several countries at the 2025 G20 Summit expressed interest in adapting India’s governance frameworks. DPI is no longer merely a domestic project; it is emerging as a global reference model.

Government policy still sets the course. The India AI Mission provides a structured plan for the application of AI in governance. Digital India 2.0 expands the vision, with emphasis on inclusion, resilience, and security. But policy alone is not enough. The ecosystem matters as much. Public–private partnerships, startup innovation, and sovereign cloud adoption are what translate intent into results. The balance between state leadership and private execution is what keeps DPI responsive to citizens rather than static on paper.

India has already demonstrated its ability to build digital infrastructure at an unmatched scale. The challenge now is to ensure this infrastructure remains adaptive and future-ready. AI and IoT sit at the heart of this evolution—shaping how electricity is supplied, how cities are managed, how farmers receive advice, how patients are cared for, and how payments are made.

The next phase will be more complex. Systems will increasingly connect healthcare, transport, public safety, and everyday services. The priority will be to ensure that these systems remain reliable, secure, and user-friendly. Digital public infrastructure is already reshaping lives. It links cities and villages, evolving with purpose. At the centre of it all are people—and the real question is how India ensures this transformation reaches everyone.

The author is the CEO and Managing Director of SCS Tech India.

Also Read

Cloud CDN architecture: Scaling secure, high-speed delivery
Intelligent observability: The answer to enterprise data overload
Enterprises rethink AI infrastructure as systems take control
10 Deep-tech shifts shaping India’s digital networks in 2026