DATA EXPLOSION
Humanity Has Entered an Era in Which Data Is Becoming One of the World's Most Important Strategic Resources
By Meridian | Sterling Atlantic
01 | The Explosion
Human civilization spent thousands of years creating information slowly. Knowledge was spoken, written on stone, recorded on paper, printed in books and eventually stored electronically. For most of history, producing information required deliberate human action. Someone had to write the sentence, take the photograph, make the measurement or record the transaction.
That world has disappeared. We have entered an era in which machines, people, businesses and physical infrastructure generate data continuously. Every financial transaction, satellite image, search query, industrial sensor, medical scan, GPS coordinate, online purchase, connected automobile, security camera, social-media interaction and artificial-intelligence query contributes to an expanding digital record of human activity.
It is frequently said that humanity has created more data during the last two years than during all previous human history. The exact formulation is difficult to verify because definitions of "data created" vary and much digital information is duplicated, transmitted and discarded rather than permanently stored. But the larger conclusion is unmistakable: humanity is producing information at a rate without historical precedent.
The Data Explosion is not simply about having more computer files. It represents a fundamental change in our ability to observe the world.
What Caused the Data Explosion?
Smartphones put billions of data-generating computers into human hands. Photographs, locations, messages, purchases, searches and app interactions continuously create information.
Cloud computing made enormous-scale storage and processing economically practical, allowing organizations to purchase computing capacity on demand.
The Internet of Things turned factories, vehicles, aircraft, power grids, farms, buildings and logistics networks into continuous information sources.
Digital commerce transformed transactions, inventories, customer behavior and supply chains into machine-readable information.
Satellites and remote sensing expanded observation of agriculture, weather, transportation, mineral exploration, military activity and environmental change.
Artificial intelligence accelerated the cycle again: AI consumes enormous datasets and also produces text, images, software, simulations, predictions and analysis at machine scale.
More connected devices create more data. More data improves AI. Better AI creates more applications. More applications generate even more data.
The infrastructure required to process this information is becoming strategically important. The International Energy Agency estimated that data centers consumed approximately 415 TWh of electricity globally in 2024 and projected consumption to reach roughly 945 TWh by 2030, with AI an important driver of the increase.
The Data Explosion is therefore becoming a physical phenomenon as much as a digital one. It requires semiconductors, fiber networks, data centers, electricity and increasingly artificial intelligence capable of making sense of information volumes that humans could never analyze themselves.
DATA EXPLOSION
02 | From Data to Intelligence
The real value of the Data Explosion is not the data itself. The value comes from discovering patterns inside it.
A dataset containing trillions of observations is useless if nobody can determine what those observations mean. Artificial intelligence, machine learning and advanced analytics are changing that equation. For the first time, humanity possesses both enormous quantities of information and increasingly sophisticated machines capable of examining it.
Better Predictive Analysis
Perhaps the most obvious consequence is better prediction. Traditional forecasting frequently relied on relatively small historical datasets. Today, algorithms can analyze millions or billions of observations simultaneously.
Insurance companies can combine claims histories, weather, geography, building characteristics, cybersecurity behavior and economic activity to estimate risk.
Banks can examine transaction patterns to identify fraud.
Manufacturers can analyze equipment telemetry to predict when a machine is likely to fail.
Retailers can anticipate customer demand and utilities can forecast electricity consumption.
Agricultural systems can combine satellite imagery, weather, soil conditions and crop history to improve planting and harvesting decisions.
The fundamental principle is simple: more observations can reveal patterns that were previously invisible.
Understanding Complex Systems
An equally important consequence is our improving ability to understand problems containing thousands—or millions—of interacting variables. Climate systems, financial markets, human biology, supply chains, cybersecurity networks and cities are all complex. Historically, researchers simplified these systems because human beings could analyze only a limited number of variables simultaneously.
AI changes that limitation. Instead of asking only whether A causes B, researchers can increasingly investigate enormous networks of relationships among thousands of variables. This could materially accelerate scientific discovery.
Medicine Becomes More Individual
Medicine may eventually become one of the greatest beneficiaries. Imagine combining a patient's genetics, medical history, imaging, laboratory results, medications, wearable-device information and outcomes from millions of comparable patients. Medicine begins moving from population averages toward increasingly individualized predictions.
Which treatment is most likely to work? Which patient is most likely to develop a disease? Which drug combination produces the best outcome for someone with this particular biological profile? The Data Explosion makes these questions increasingly computational rather than purely observational.
The Rise of Digital Twins
Another important development is the creation of digital twins—virtual representations of physical systems continuously updated with real-world information. A factory, power grid, aircraft engine or mine can have a digital twin. Instead of experimenting exclusively on the physical asset, organizations can simulate potential decisions digitally.
The ability to test thousands of scenarios before acting could fundamentally improve decision-making.
DATA EXPLOSION
03 | The Second-Order Effects
Data Becomes a Competitive Moat
Companies historically built competitive advantages through factories, distribution networks, patents, brands and capital. Increasingly, proprietary data can become another moat. A company possessing twenty years of unique operating data may be able to train better predictive systems than a competitor entering the market today.
More customers generate more information. More information improves the product. A better product attracts more customers. Those customers generate still more information. This creates a data flywheel. The competitive advantage is therefore not merely possessing data, but possessing unique, relevant and continuously improving data that competitors cannot easily reproduce.
Decision-Making Moves From Reactive to Predictive
Most organizations historically operated reactively: something happened, management observed it, then management responded. Data-intensive organizations can increasingly identify the probability of something happening before it occurs.
The management question shifts from “What happened?” toward “What is likely to happen next, and what should we do before it happens?”
Scientific Discovery Accelerates
AI and large datasets allow researchers to explore enormous numbers of possible relationships computationally before committing resources to physical experiments. Drug discovery is one example: instead of physically testing every possible molecular candidate, computational systems can narrow enormous search spaces to candidates most likely to succeed. The same principle can apply to materials science, energy, chemistry and engineering.
Data therefore does more than document discoveries. It can increase the rate at which discoveries occur.
Infrastructure Becomes Strategic
The Data Explosion creates demand far beyond software. It increases demand for semiconductors, data centers, fiber-optic networks, subsea cables, satellite communications, electrical generation, transformers, cooling systems, energy storage, cybersecurity and cloud infrastructure. The digital economy ultimately rests upon an enormous physical foundation.
Data Creates New Risks
More information does not automatically produce a better world. The same datasets that improve medical diagnosis can compromise privacy. The same behavioral information that improves personalization can enable manipulation. Connected systems create cybersecurity vulnerabilities. Poor-quality information can produce confident but incorrect predictions. Biased datasets can reproduce historical biases. Concentrating enormous quantities of information in relatively few organizations can create new forms of economic and political power.
The central challenge therefore becomes not simply collecting information, but determining who controls it, how it is protected, how its accuracy is established and how it should be used.
The Next Scarce Resource Is Not Data
For most of human history, information was scarce. That scarcity is disappearing. We are approaching the opposite problem: information abundance on a scale beyond human comprehension. When data becomes abundant, something else becomes scarce: the ability to identify what matters.
Artificial intelligence is emerging at precisely the moment when the volume and complexity of information have exceeded the practical analytical capacity of human beings. Data provides the raw material. Computing provides the infrastructure. AI provides the analytical engine. Human judgment determines what should ultimately be done with the answer.
The next great divide may not be between those who have information and those who do not. It may be between those who are overwhelmed by data—and those who know how to turn it into intelligence.
Sources: International Energy Agency, Energy and AI (2025) and related data-center electricity updates. The commonly repeated “more data in two years than all prior history” formulation is presented as a description of exponential growth rather than a precisely verifiable statistic.