How Information Pricing Could Reshape Digital Economies As the economy becomes increasingly digitized, information is often undervalued and poorly managed. Companies are prone to dealing with misinformation and mixed signals and, as such, lack clear ways to measure the reliability or economic worth of the information they need.

Businesses of all kinds depend on data (like customer behavior analytics, market demand forecasts, supply chain metrics, and financial performance indicators) to make important product decisions, guide investments, and shape strategies. Yet as the economy becomes increasingly digitized, information is often undervalued and poorly managed. Companies are prone to dealing with misinformation and mixed signals and, as such, lack clear ways to measure the reliability or economic worth of the information they need.

The result is a growing gap between the volumes of available data and its actual usefulness in helping businesses make confident decisions.

This is the challenge Chaikesh Chouragade has set out to address. An artificial intelligence research scientist at ZZAZZ AI Solutions India with a master's from IISc Bangalore and experience at Microsoft, he's working on developing automated systems for the emerging field of information pricing, a discipline focused on measuring and assigning economic value to data. His work aims to develop a broader framework that treats information as a tradable asset, assigning it real and dynamic value so businesses can manage and monetize their data with full trust.

Chaikesh's Early Work

Chaikesh's interest in technology took root at an early age. Growing up, he was captivated by electronics, curious about how devices worked and what powered the signals behind them. He'd spend hours dismantling toys and digital gadgets, drawn to the invisible systems that carried information from one point to another.

This interest carried on over the years, and as AI began moving from research labs into real-world applications, Chaikesh recognized the potential to layer intelligence on top of connectivity. At IISc Bangalore, during his master's in artificial intelligence, he focused on mathematics and modeling principles, seeking to understand the foundations that make these advanced systems possible.

After IISc, Chaikesh joined Microsoft India R&D as a data and applied scientist, where he first learned to apply the theoretical principles he was taught to real-world systems. That's where he understood that, more than technical capabilities, the systems that people use need to be easy to follow and intuitive to regular users. "I learned that adaptability is as important as technical depth," he said, describing how the experience taught him to design systems that work reliably under real-world constraints.

His View On The Digital Economy's Data Dilemma

Throughout his career, Chaikesh has been working to address the challenges businesses face when trying to make sense of the information they depend on. In today's digital economy, data moves quickly but is rarely given a clear or consistent value. Companies struggle to measure their accuracy or reliability, while misinformation and low-trust ecosystems create costly blind spots.

When information is undervalued, markets become inefficient, decisions get shaped by incomplete or low-quality data, and businesses often take on reputational and financial risks without realizing it. Attention-driven systems only add to the complexity, rewarding speed and volume over substance and clarity.

Chaikesh sees this as a structural issue as much as a technical one. Without tangible, usable tools that can assign dynamic, market-aware value to information, businesses are left dealing with uncertainty and have little more than instinct regarding how to use their data. As he puts it, "Information is the currency of the digital age, and pricing it fairly, based on supply and demand, could be the foundation for a more trustworthy future."

Building Trustworthy Models At ZZAZZ AI Solutions

Working as a research scientist for India's division of ZZAZZ AI Solutions, Chaikesh leads the development of models that can effectively make this vision practical.

Large pricing models, for instance, take streams of real-world data (market demand signals, information quality metrics) and calculate a changing price for that information as relevant conditions shift. Businesses using these models can see, in real-time, what their data is worth and make decisions about how they could better use it to their advantage. Quantitative market value models go a step further by packaging these calculations into practical tools like internal dashboards and automated pricing systems, so businesses can integrate relevant information valuation directly into their operations.

Perhaps most ambitious is the integration of Complex Adaptive Reinforcement Learning (CARL), a method for teaching systems to learn and adapt in real-time, particularly useful in information platforms where data quality and economic conditions change constantly.

Together, these tools promise more than just monetization opportunities; they seek to build a type of digital ecosystem where truth and transparency carry measurable rewards.

These types of systems can be greatly advantageous to many industries. Publishers can price content dynamically, advertisers can align campaigns with information quality, and companies can design incentives for their clients, favoring accuracy over virality. As Chaikesh describes it, "Our mission is clear: to establish information as a recognized, tradable economic asset, one that benefits customers, empowers businesses, and reshapes markets."

The Road Ahead

While information pricing remains a young field, its potential reaches far beyond early experiments. Chaikesh considers how, much like financial markets once coalesced around accounting standards and reporting norms, the next phase of finance in a digital world involves setting up collaborations spanning different industries in international locations to ensure that this type of technology has access to the right information to work accurately and safely.

"Though the field is still young," he says, "the path forward is coming into focus. With the foundational work of our research partners and contributors, ZZAZZ is shaping a future where the value of information is no longer hidden but harnessed."

As digital economies continue expanding, the question of information's value will only grow more pressing. With researchers like Chaikesh leading the charge, businesses may soon find that pricing information fairly is not just a technical challenge but the cornerstone of a more trustworthy digital era.