By Vijayant Rai
India’s Viksit Bharat goal sets 2047 as the milestone for shared prosperity, capable governance, and technology that closes the gap between policy intent and what citizens actually experience. The infrastructure choices made today will determine how that target is achieved, especially by building a data foundation for AI, digital public infrastructure, financial services, healthcare, governance platforms, and citizen-facing applications.
India has already demonstrated what well-designed digital infrastructure can achieve at scale. Aadhaar, UPI, Diksha and eSanjeevani have each translated strong data foundations into tangible outcomes for millions. The economic dividend is real: Digital public infrastructure is projected to contribute between 2.9% and 4.2% to India’s GDP by 2030, highlighting its role in accelerating national development.
The AI wave demands a comparable investment, on a tighter schedule. Organisations that build AI-ready data foundations in the next few years will train better models, move faster, and build institutional knowledge over time. For India to reach 2047 as a first-mover economy, we must build the foundation now and build it correctly. The real risk is not moving too slowly, but moving fast on the wrong foundations.
The AI gold rush without a data strategy is a liability
India’s AI spending has accelerated sharply, with enterprises across BFSI, retail, healthcare, and manufacturing deploying AI models, agents, and analytics. Yet the underlying issue remains: data is fragmented, inconsistently labelled, governed by pre-AI policies.
Enterprise data volumes are growing two to three times annually; however, most organisations cannot answer three basic questions: what data they hold, where it lives, and what it is actually suited to do. Many assume they are AI-ready because modern tools or cloud platforms are in place, but real readiness depends on clean, integrated, accessible enterprise data. The “ROI of Gen AI and Agents” report by Snowflake and Omdia notes that Indian enterprises plan to allocate 28% of their technology budgets to generative AI in the next 12 months, compared to the global average of 22%, similarly, 66% of Indian organisations are already using or planning agentic AI within a year.
For this to translate into strong ROI, enterprises need cloud-based data platforms and interoperable architecture to enable seamless data exchange. Without it, integrating structured and unstructured data will remain slow, costly, and fragile. For AI to deliver, data literacy, mobility, and action must work together – but most enterprises have not closed this gap, leaving many AI investments stalled.
That stalling has concrete costs. A bank deploying a credit risk model on incomplete data cannot justify its predictions or retrain the model; a hospital automating clinical triage on siloed patient records cannot reduce diagnostic errors. In both cases, the issue is not AI performance but weak data foundations and governance.
The three foundations that cannot be deferred
The lack of a data strategy reflects a structural gap that requires a system-wide response. The first is data democratisation. Data often sits within IT teams or siloed business units, limiting access and slowing decisions. Enabling governed and self-service access allows organisations to learn faster where their data is usable and where it is not.
The second is an AI-ready data architecture. Democratisation only works if supported by a clean, standardised pipeline that integrates structured and unstructured data in real time. The third is trust and governance. Privacy-by-design, regulatory compliance, and ethical safeguards are essential to ensure AI systems are fair, accountable, and reliable. Responsible data use is what sustains trust and long-term value.
These shifts cannot work in isolation. Data without literacy creates noise, literacy without access creates frustration, and infrastructure without trust eventually fails. To achieve impact, all three need to work together.
Building for 2047
Roads, ports, and power grids shaped India’s economic geography for decades. The data and AI infrastructure choices enterprises make today will determine the ROI and growth of their organisations and cement their role in India’s Viksit Bharat journey.
The opportunity is not in collecting more data. India already has more data than it can use. The real opportunity is in building the foundations that turn what already exists into a sustained national advantage. In the race to 2047, leadership will not be defined by who has the most data or the fastest AI, but by who builds the most trusted, interoperable, and future-ready data foundations to scale AI.
The writer is managing director – India, Snowflake
Disclaimer: The views expressed are the author’s own and do not reflect the official policy or position of Financial Express.