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As India advances towards full compliance with the Digital Personal Data Protection (DPDP) Act and Rules, infrastructure choices define whether privacy builds or erodes trust. In a world where data is continuously generated through payments, commerce, healthcare, education, and public services, trust is now inseparable from growth.
Data privacy can no longer be treated as a policy exercise that follows digital transformation. It has become a business and societal expectation shaped by the systems organisations build, the partners they choose, and the operational discipline they enforce.
The foundation is built upstream
This shift is particularly relevant in India, where digital adoption accelerates alongside a rapidly evolving technology backbone. As data volumes surge with data centers set to power a $100B digital infrastructure decade and AI embeds across sectors, trust in data handling emerges as a defining factor for long-term growth.
Public discourse has largely focused on consent mechanisms, legal frameworks, and compliance obligations. While necessary, these alone do not determine outcomes. Privacy is shaped by where data resides, how it moves across environments, who can access it, and how long it persists. These decisions must be made early at the architecture and operating model stage, not retrofitted during compliance sign-off.
Governance is moving closer to the core
The Digital Personal Data Protection Act reflect this evolution, mandating accountability, purpose limitation, encryption, access logging, and real-time breach reporting while encouraging organizations to strengthen governance over personal data. Introduced amid rapid digitization, cross-border flows, and AI’s rise, the framework demands responsible handling at scale.
While regulatory discussions can feel like checklists, leaders should heed the broader signal: data localization, cross-border transfers, processing responsibility, and auditability are infrastructure design questions. The Act’s phased rollout recognizes that operationalizing privacy requires policy-infrastructure alignment. With guidance evolving, data center-level clarity is vital for investment decisions and sustainable growth.
Inference makes privacy more dynamic
Cloud and AI are fundamentally changing how privacy must be approached. Cloud has made infrastructure more distributed and flexible, while AI adds complexity by enabling systems to infer sensitive information from patterns, prompts, and behavioural signals, even without explicit identifiers.
As organisations deploy AI copilots, assistants, and recommendation systems, the privacy conversation must expand beyond databases to include prompts, logs, embeddings, caches, and monitoring traces. These layers can unintentionally retain personal context. The objective is not to slow innovation, but to ensure it is grounded in minimisation, purpose-driven design, and disciplined data retention from the outset.
Digital infrastructure at the core of privacy
Data accessed through digital interfaces, but it ultimately resides in physical infrastructure. As a core component of digital infrastructure, data centers support cloud platforms, enable AI workloads, and host sensitive personal and enterprise information, translating digital policy into operational reality.
India’s data center capacity is projected to grow from approx 1.5 GW today to nearly 14 GW by 2035, driven by AI, cloud, and 5G demand. As data volumes and sensitivity rise, decisions around location, resilience, access controls, and governance directly shape privacy outcomes. Data centers are therefore no longer neutral. They have become active enablers of privacy at scale.
Enforcing privacy across cloud and AI infrastructure
As cloud usage deepens and data center capacity expands to support always-on and AI-driven services, infrastructure increasingly determines privacy outcomes. This was underscored by an incident at a large Indian financial services platform, where unauthorised access to cloud-hosted systems exposed customer data. Public reporting noted that the breach triggered forensic investigations and access reviews, highlighting how gaps in credential management, monitoring, or access controls can rapidly escalate into large-scale privacy risk.
From a privacy standpoint, digitally anchored cloud environments enable:
- Alignment with data residency and localisation expectations
- Infrastructure-level visibility into data access and usage
- Isolation of sensitive workloads
- Continuous monitoring and auditability
AI inference workloads operate continuously on live, sensitive data, increasing the risk of information being retained, reused, or exposed beyond its original purpose. In this context, privacy cannot rely on static controls or post-facto compliance. It must be operationalised through infrastructure that enforces visibility, lifecycle governance, and clear boundaries around data use.
Security enables privacy, but does not replace it
Security remains the mechanism through which privacy commitments are upheld. Energy resilience, physical access controls, and workforce governance reduce exposure during disruption and limit insider risk. However, security alone is not a substitute for privacy-aware design.
As cloud and AI environments scale, access discipline, monitoring, and identity controls must extend beyond traditional perimeters. Without this, even well-secured systems can unintentionally retain personal context across prompts, logs, and traces. Privacy-first environments ensure these layers are governed with intent, not left as residual risk.
Resilience and energy readiness must eb privacy-aware
Operational resilience increasingly shapes privacy outcomes. In India’s always-on digital economy, measures such as failover, disaster recovery, and redundancy can unintentionally spread personal data across locations. Privacy-first resilience designs continuity with clear geographic boundaries and disciplined cleanup, ensuring recovery planning does not introduce new privacy blind spots under stress.
Edge scale increases governance demands
The physical location of infrastructure is regaining importance as edge computing moves data processing closer to users, particularly beyond major metros. While this improves performance, it raises new questions around data handling, access control, and oversight. Location is an operational concern, requiring governance to scale alongside expanding infrastructure footprints.
The human layer of privacy
Not all privacy risks are technological. Many stems from human factors, including misconfigurations, uncontrolled access, contractor exposure, and unclear accountability across vendors. Privacy-first organisations embed discipline into daily operations through role-based access, time-bound privileges, strong joiner mover leaver processes, training for privileged roles, and clear ownership across internal teams and partners. These are not soft controls. They form the human layer of privacy engineering.
Why privacy-first infrastructure is critical for India’s next decade
India’s next phase of digital growth will be defined by how confidently citizens and customers engage with digital services at scale. That confidence will not come from policy statements alone. It will come from infrastructure and operations designed to make privacy the default across cloud and AI workloads, resilient architectures, physical footprints, and the people who run these systems every day.
As India builds at unprecedented digital scale, the infrastructure choices made today will quietly determine whether trust compounds or fractures over the next decade. Privacy-first infrastructure will not only reduce risk, it will become a decisive competitive advantage for India’s digital ambitions.
The author is Avaneesh Kumar Vats, Vice President – Information Technology, Techno Digital.
Disclaimer: The views expressed are solely of the author and ETCISO does not necessarily subscribe to it. ETCISO shall not be responsible for any damage caused to any person/organization directly or indirectly.
