The Invisible Inflation: How Corporate Data Hoarding Is Distorting the Global Economy

By Haruto Watanabe Dec. 27, 2024

The world is obsessed with inflation—but not all inflation is visible. While central banks fixate on consumer prices, a hidden form of inflation is quietly reshaping the economy: data inflation. Corporations, governments, and AI systems are hoarding unprecedented volumes of digital information—driving up its value, restricting its circulation, and creating a world where access to truth is a luxury good.

According to the OECD Digital Capital Markets Review (2025), the global data economy is worth US$15.2 trillion, exceeding the GDP of China. Yet, less than 10 percent of this data is openly accessible. The rest sits behind paywalls, proprietary servers, and cloud ecosystems owned by fewer than a dozen multinational firms.

In a world where knowledge is capital, monopolizing data is the new inflationary pressure—one that central banks can’t print their way out of.

The New Gold Standard: Data as Money

The 20th century’s monetary systems revolved around tangible scarcity: gold, oil, or land. The 21st revolves around informational scarcity. Tech companies treat data as both currency and collateral. Amazon’s recommendation logs, Google’s search archives, and Meta’s social graphs are not passive databases—they are the basis of valuation, market control, and AI model dominance.

The World Bank Digital Commodities Index (2025) calls this phenomenon “data monetization elasticity”—a measure of how information’s marginal utility grows faster than traditional capital. Unlike physical resources, data gains value through accumulation, not depletion. The more one owns, the more valuable it becomes.

It’s not just about owning information—it’s about owning context.

The Data Supply Chain

Data travels through global supply chains much like oil or steel. It is extracted (from users), refined (through algorithms), distributed (via cloud infrastructure), and sold (as analytics or predictive tools). But unlike oil, the supply is not infinite—and it is now being cornered.

The International Monetary Fund (IMF) Information Asset Report (2025) estimates that 83 percent of global AI training data originates from just 12 countries. Africa contributes less than 1 percent. This creates a form of informational imbalance where economic power increasingly depends on one’s digital export capacity.

The invisible hand of the market is now an algorithm holding a dataset.

Inflation Without Prices

Traditional inflation reflects rising costs of goods and services. Data inflation manifests differently: as rising barriers to access and falling informational authenticity. As more information becomes commodified, the average cost of reliable data increases.

Academic journal paywalls, proprietary APIs, and AI models with tiered subscription access are symptoms of this phenomenon. The Harvard Digital Knowledge Inequality Study (2025) found that the average university in the Global South spends 27 times more per capita than North American institutions to access equivalent research databases.

When information becomes expensive, ignorance becomes structural.

The Monopoly of Measurement

Big Tech’s grip over data has turned statistics into strategy. Corporations now control many of the metrics that governments use to regulate them. For instance, Google’s advertising dominance allows it to define what counts as a “view,” while Facebook sets the parameters for “engagement.”

The London School of Economics Governance Metrics Review (2025) warns that this privatization of measurement enables “algorithmic inflation”—the artificial creation of economic growth indicators within closed digital ecosystems. GDPs appear to rise through productivity software and data sales, while real output stagnates.

Data inflation, in short, distorts not only prices—but perception itself.

The AI Feedback Loop

Artificial intelligence has made data inflation self-reinforcing. AI systems generate synthetic data to fill gaps in training material, which in turn inflates the apparent size of datasets without improving quality. The Stanford Institute for Human-Centered AI (2025) estimates that by 2027, 60 percent of all “new data” will be AI-generated.

This flood of synthetic content drives up demand for authentic human data, much like counterfeiting increases the value of genuine currency. Authenticity becomes the new scarcity.

We are witnessing the birth of an economy where truth trades at a premium.

Data as an Inflationary Externality

Just as carbon emissions distort climate systems, data accumulation distorts economic systems. Every byte stored consumes energy, bandwidth, and hardware resources. The International Energy Agency Digital Infrastructure Report (2025) found that data storage accounts for 2.8 percent of global electricity consumption—more than aviation.

Information is no longer weightless; it has a carbon cost. As data multiplies, its physical and financial burden does too.

This inflation is not in money—it’s in meaning.

The Hidden Victims: Small Firms and Developing Nations

Data inflation widens inequality. Small enterprises and startups, priced out of data access, cannot compete with firms that already possess massive informational advantages.

The World Economic Forum Global Competitiveness Index (2025) shows that companies with proprietary data infrastructures grow 47 percent faster than those reliant on open datasets. Meanwhile, nations lacking digital governance mechanisms are becoming “data colonies”—providers of raw user information exported to foreign AI platforms with no local benefit.

The digital divide is no longer about connectivity—it’s about custody.

Regulating the New Inflation

Economists and policymakers are proposing a Data Transparency Compact, modeled after international trade frameworks:

1. Open Data Quotas – Require firms to make a fixed percentage of proprietary data public.

2. Data Tariffs – Levy digital taxes on cross-border data exports to prevent exploitative extraction.

3. Information Anti-Trust Laws – Break up monopolies controlling essential data flows.

4. Data Quality Audits – Mandate periodic verification of dataset authenticity and bias.

According to the OECD Fair Data Economy Framework (2025), implementing these measures could reduce data concentration by 33 percent within a decade—lowering systemic risk and restoring transparency.

Inflation control in the digital age is not about interest rates—it’s about access rates.

The Moral Cost of Hoarded Knowledge

In the industrial era, hoarding gold created wealth. In the information era, hoarding truth creates inequality. As data becomes the foundation of AI, governance, and finance, those who control it will not only predict the future—they will own it.

The invisible inflation of information is not just an economic distortion. It is a moral one.

Works Cited

“Digital Capital Markets Review.” Organisation for Economic Co-operation and Development (OECD), 2025.

 “Digital Commodities Index.” World Bank, 2025.

 “Information Asset Report.” International Monetary Fund (IMF), 2025.

 “Digital Knowledge Inequality Study.” Harvard University, 2025.

 “Governance Metrics Review.” London School of Economics (LSE), 2025.

 “Human-Centered AI Report.” Stanford University, 2025.

 “Digital Infrastructure Report.” International Energy Agency (IEA), 2025.

 “Global Competitiveness Index.” World Economic Forum (WEF), 2025.

 “Fair Data Economy Framework.” Organisation for Economic Co-operation and Development (OECD), 2025.

 “Data Ethics and Equity Review.” United Nations Development Programme (UNDP), 2025.