This article is part of a series examining the geopolitics of technology, the theme of Carnegie India’s eighth Global Technology Summit (December 4–6, 2023), co-hosted with the Ministry of External Affairs, Government of India. The summit focused on artificial intelligence, digital public infrastructure, critical and emerging technology, national security, and more. Click here to watch all the discussions.

This piece is adapted from an essay by the author titled “The Economics of Data Businesses” that previously appeared in Carnegie India’s newsletter Ideas and Institutions.

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In our rapidly evolving digital era, the rise of advanced artificial intelligence and the dominance of large technology firms have reshaped the economic landscape. Understanding these firms is not just an academic exercise—it is essential for effective policymaking and fostering competitive markets. As these entities increasingly influence our daily lives, from the advertisements we see to the news we read, unraveling their workings becomes crucial for both consumers and policymakers.

The Essence of Data Businesses

Today’s corporate giants differ significantly from their predecessors. They are data-centric, meaning that data is their most valuable asset. Distinguishing these businesses, experts have categorized them into two main types: data-enabled and data-enhanced. Data-as-a-Service (DaaS) companies don’t just utilize data—they make it their primary product. This approach has revolutionized modern business, placing data at the center of new economic models. In contrast, data-enhanced businesses use data to refine and improve their existing operations and services, integrating data into their traditional business models to gain a competitive edge.

Building and Growing DaaS Companies

The journey to establish a DaaS company is challenging and multifaceted. Initially, these companies face significant investments in establishing robust data infrastructure. This foundational phase is both financially demanding and technically complex, requiring substantial resources and expertise. Once this infrastructure is in place, the ongoing costs of operation decrease, but challenges remain. Companies must continually adapt and update their data to maintain relevance and competitiveness in a rapidly changing digital landscape. This continuous evolution is a key characteristic of successful DaaS companies.

The economist Hal Varian highlights three significant characteristics of data in the context of business operations. First, data is non-rivalrous, meaning that its use by one entity does not preclude its use by another. This characteristic allows for wide-ranging applications and sharing of data without depletion of its inherent value. Second, the utilization of data, especially through advanced techniques such as machine learning, initially shows increasing returns. However, there is a natural limit to the effectiveness of data, beyond which the returns diminish. Finally, Varian challenges the notion that data markets are primarily driven by network effects. He suggests that continuous improvement and adaptation, rather than sheer size or user base, are more crucial for success in these markets.

The growth trajectory of DaaS companies is marked by a gradual but steady increase in value and influence. Starting from a point where they accumulate enough data to offer viable products or services, these companies enter a phase of accelerated growth. The value of their data products increases, attracting more customers and enabling further data collection and refinement. This virtuous cycle of growth and expansion enhances their market power and presence over time.

Policy Implications

The unique business model of DaaS companies poses significant challenges and opportunities for policymakers. Key questions arise regarding the structuring of open-data initiatives. Should the focus be on making raw data more widely available, or should efforts concentrate on facilitating the development of valuable data products and services? Additionally, the nature of these markets often leads to a few dominant players. This phenomenon raises important considerations for antitrust laws and strategies. What can competition policy do in a market where a handful of companies naturally tend to dominate due to the underlying economics of DaaS businesses?

Furthermore, there is a growing debate over how data should be perceived and treated. The traditional view of data as an unlimited resource, akin to oil, is being challenged. Instead, there is a shift toward recognizing data as a valuable commodity with unique characteristics. This change in perspective has far-reaching implications for policy and regulation, requiring a nuanced understanding of the intrinsic value of data and its role in the digital economy.

Expanding Understanding of Data Markets

Data’s unique characteristics challenge conventional theories and models, necessitating a fresh perspective on competition, market dominance, and value creation. As the distinction between DaaS and data-enhanced businesses becomes increasingly blurred, understanding the nuances and subtleties of these markets becomes crucial.

The rise of data-first companies has introduced new paradigms in how we view and interact with data. These companies are not just reshaping their respective industries—they are redefining the very fundamentals of economic and business models. Their growth and impact underscore the need for ongoing research and analysis to fully comprehend and effectively engage with these new economic forces.

In summary, as we navigate this new age of data-centric economics, a comprehensive and nuanced understanding of data-first businesses is vital. The dynamics of data-first companies are reshaping our world, making it imperative for us to stay informed and actively engaged in understanding these evolving trends.