Commoditisation: Let’s treat data as an asset

To commoditize data is not to strip it of privacy or ethics. It is to unlock its potential while building in guardrails. Just as electricity became the backbone of the industrial age, commoditized data is the foundation of the AI age. Countries like China and the US are already far ahead in this race. India cannot afford to be left behind.

Data fuels AI applications in healthcare, agriculture, education, finance, and logistics. Commoditizing it allows start-ups and businesses, especially SMEs, to access datasets that were once trapped within silos. Governments can use data to improve service delivery, urban planning, and disaster response. Sharing anonymized data across departments breaks down bureaucratic walls and leads to smarter policies. When handled with consent and transparency, commoditized data can give individuals more control over their digital lives, and even create opportunities to earn from their own data.

Apart from the government, a few companies, mostly foreign, control the majority of Indian data. This creates monopolies, stifles innovation, and risks a form of digital colonialism. A well-regulated data economy will democratize access.

What the world is doing and why India must act

Let’s consider how global powers are approaching this. China has declared data as a “factor of production”, just like land or labour. It has launched state-run data exchanges in cities like Shanghai and Beijing. With strict laws controlling how data is collected and shared, China’s model is highly centralized, designed to support national goals in AI and smart manufacturing.

The U.S., by contrast, takes a market-driven approach. Private tech giants collect, analyze, and monetize data with minimal federal regulation. This fuels rapid innovation but comes at the cost of user privacy and transparency.

India is still defining its model, although we have laid down strong foundations. We have the Digital Personal Data Protection Act (2023), strong digital public infrastructure (DPI) like Aadhaar and UPI, and open government data platforms. But we lack standardized, interoperable, and tradeable data markets and that’s where our focus must shift.

Building India’s data economy: A roadmap

To responsibly commoditize data, India must adopt a multi-pronged strategy across infrastructure, law, standardization, and trust. India’s DPI stack, from Aadhaar and DigiLocker to ONDC, is already world-class. The next step is to create secure data exchanges where anonymized datasets can be bought, sold, and accessed by start-ups, researchers, and businesses.

Government ministries hold valuable administrative datasets from GST to health records, but their access is limited. Releasing these in standardized, anonymized formats can transform AI development across sectors. The DPDP Act has laid the foundation for privacy and consent. But we must move further to define clear ownership rights, especially for non-personal data like traffic patterns or crop yields. Consent-based frameworks like the Account Aggregator model in finance should be replicated in other sectors. Individuals must have the right to control, and benefit from, their data.

For data to be traded or used across platforms, it must be standardized. India must adopt common formats, metadata practices, and open APIs. This enables interoperability between different datasets and prevents fragmentation.
Incentives matter

A functioning data economy needs more than infrastructure, it needs incentives. India should establish regulated data marketplaces, where public and private players can exchange anonymized data. Innovative monetization models can be explored for instance, if a firm profits from government data, a portion of the value could go back to the public or relevant agencies. Without trust, data cannot flow. Auditable data trails, possibly using blockchain, can ensure that data usage is ethical and traceable. Independent data trusts can manage and safeguard shared data on behalf of communities, farmers, or consumers.

Data is only useful when we know how to use it. India must invest in data literacy, R&D in anonymization, and AI applications that are ethical and scalable. Our public universities, research institutions, and AI start-ups can lead the way, but they need access to data to build and test solutions.

India has the scale and public data depth to become a leader in sector-specific data applications such as (i) Agriculture: Weather, soil, and mandi data can drive precision farming, (ii) Healthcare: Anonymized health records can improve diagnostics and public health, (iii) Finance: Account Aggregators can expand financial inclusion, (iv) Mobility: Data from FASTag and EV stations can improve urban transit planning, (v) Education: Skilling and learning outcome data can guide better policy.

A model for the world

India doesn’t need to copy China’s surveillance-heavy model or America’s free-for-all. Instead, we have the opportunity to create a hybrid model that combines public digital infrastructure, strong legal safeguards, and open innovation ecosystems. Done right, this model can become a global benchmark: democratic, inclusive, and innovation-led.

Commoditizing data is not just a technology issue. It is a strategic requirement for economic growth, citizen empowerment, and global competitiveness. India has the tools. What it needs now is the willpower, cross-sector coordination, and a clear roadmap. If we get it right, data will not only power AI products or GDP numbers, it will empower citizens, create new markets, and define India’s digital future.

Shamika Ravi is Member, Economic Advisory Council to the Prime Minister (EAC-PM)

Views are personal and do not represent the stand of this publication