As AI scales in India, privacy and trust takes centre stage

The million- dollar puzzle for the Indian policymakers is no longer on AI adoption, but on how to do so responsibly, at scale and with public trust.

By 2035, Artificial Intelligence will add 1.7 trillion dollars to India’s Economy highlighting its role as a foundational driver of productivity and public value.

This is not a call to replicate India wholesale, but to adapt a core philosophy: AI must serve public value, respect citizen rights and remain accountable to democratic institutions. (AFP)

At the same time, CERT-In reports Cyber incidents have doubled (29.44+ lakh in 2025)² as of 2023.

Therefore, the million- dollar puzzle for the Indian policymakers is no longer on AI adoption, but on how to do so responsibly, at scale and with public trust.

From digital foundations to intelligent governance

The accelerated AI journey in India was fuelled by decade-long investment in the creation of a reliable User Internet Connectivity Highway; the use of connectivity has increased 4 times (i.e. 96.96 crores in 2024 from 25.15 crores in 2014).

India's approach towards AI has been pragmatic rather than speculative. Instead of focusing narrowly on frontier models, the emphasis has been on applied AI, solving real governance and service-delivery challenges across National, State, and City levels.

Public digital systems have created the rails for AI to deliver measurable outcomes.

For instance, DigiLocker crossed 53.92 crore users by June 2025, enabling authentic digital documents and verification at scale—reducing paper dependency while improving service efficiency.

In digital payments, the Unified Payments Interface demonstrates what population- scale adoption looks like in practice: April 2025 recorded 1,867.7 crore UPI transactions worth ₹24.77 lakh crore, underscoring how trusted digital rails can transform everyday life at national scale.

AI has found its footprint diversified public utilities such as:

a) Healthcare - AI- assisted screening and decision support can strengthen early detection and care pathways

b) Agriculture, AI-enabled advisories based on localized data can improve input efficiency and resilience.

In cities, AI-backed systems are being deployed for flood forecasting, environment monitoring, traffic management and rapid grievance resolution.

The trust deficit: Managing risk in an AI-driven era

This digital trajectory has significantly enhanced convenience and inclusion but has exposed the country's core fabric to secret emerging pill called ‘cyber-incidents’.

The Union Budget 2025–26 allocated ₹782 crore for enhancing digital trust in the country accelerated AI journey.

The proliferation of AI-generated content,particularly hallucinated information and deepfakes,has sharpened concerns around privacy, identity protection, and information integrity.

The enactment of the Digital Personal Data Protection Act, 2023, along with its rules, establishes a robust privacy framework grounded in consent, purpose limitation, accountability, and grievance redressal.

Thereby emphasising that digital systems must not only be technologically advanced, but also trustworthy by design

Trust as the cornerstone of scalable AI

As AI systems increasingly interact with sensitive citizen data, and hence its sustainability depends on trust.

In a democratic system, AI-assisted decisions must be explainable, contestable, and defensible, particularly where outcomes affect livelihoods, entitlements, or due process.

Algorithmic opacity is not merely a technical limitation; it represents a governance risk.

This evolving debate on trust, accountability, and scale will take centre stage at the upcoming India AI Impact Summit 2026 (16-20 February in New Delhi), envisioned as a global platform to align policymakers, technologists, industry leaders, and civil society on responsible AI pathways.

The Summit aims to move the discourse beyond innovation hype towards operationalising privacy-by-design, explainability, and risk-aware deployment of AI in public systems.

By foregrounding trust as a governance imperative, the Summit reflects India’s intent to shape not just domestic AI policy, but global norms for ethical and scalable AI adoption.

Privacy and accountability must therefore be treated as enabling infrastructure for AI, not as regulatory afterthoughts. India’s policy direction, anchored in lawful data use, auditability, and institutional oversight, reflects an emerging global consensus that trust is a prerequisite for scale.

This approach is reinforced through strategic investments. The Cabinet-approved IndiaAI Mission, with an outlay of ₹10,371.92 crore over five years, includes the creation of public AI compute infrastructure with 10,000+ GPUs, support for sovereign foundational models, and development of “safe, trusted, and ethical AI” tools.

This is not merely an innovation programme; it is a clear signal that India views trustworthy AI as a strategic imperative for governance, economic competitiveness, and national resilience.

Lessons for Global South

India's three-pronged approach, viz. a) AI Infrastructure, b) AI Talent, c) ‘Gamification for AI amplification’, helped it successfully navigate common challenges such as uneven digital infrastructure, varying digital literacy, and institutional capacity constraints shared across Global South countries - Africa, Latin America and parts of Asia.

This is precisely why India’s experience resonates: AI progress need not depend on unchecked data extraction, opaque surveillance, or dependency on externally controlled platforms; instead, context-aware AI built on sovereign digital infrastructure and clear public-interest guardrails.

During India’s G20 presidency, the Digital Public Infrastructure (DPI) agenda was elevated to achieve tangible outcomes. This global recognition strengthens the case for Global South nations to adopt scalable, interoperable, and rights-respecting digital approaches as the foundation for AI.

Federated approach

India's impetus on National Level Framework commanding AI-First, Cloud-Native, Mobile- first & Presenceless, Privacy-by-Design, Federated Architecture (IndEA Architecture) serves as Minimum Viable Reference Architecture (MVRA) for accelerated AI solution deployment.

These central standards and frameworks natures replication at scale at the State and City/Village levels grassroot administration.

National Digital Health Mission (NDHM’s) Health Stack is classic example of Centrally designed architecture which federated up to State and City/Village layer data to harness localised service delivery aligned to the National Framework.

This federal scalability matters because many high-impact AI use cases are inherently local: municipal services, disaster response, public health surveillance, education outcomes and policing.

A credible model is one where a national framework enables digital security, Privacy Compliance and interoperability, while State and City administrators retain execution autonomy, trusted and innovative service engines.

A blueprint for ‘Responsible AI’ - Global South

For governments across the Global South, the opportunity is clear. By adopting principle- based AI policy, investing in digital public infrastructure, and embedding privacy-by-design into AI systems, nations can leapfrog fragmented experimentation and move directly to responsible scale.

This is not a call to replicate India wholesale, but to adapt a core philosophy: AI must serve public value, respect citizen rights and remain accountable to democratic institutions.

As AI becomes the operating system of modern governance, trust will be its most valuable currency. India’s experience shows that it is possible to build AI systems that are powerful yet principled, innovative yet accountable, and transformative without being extractive.

In a world increasingly run by algorithms, rethinking privacy and trust is not optional, it is foundational to inclusive and sustainable AI progress for the Global South.

The writer is the Managing Director and Chief Executive Officer of the Digital India Corporation