Computing power is becoming a new global resource, an invisible force that divides states into those that think for themselves and those that rent someone else’s mind
In every historical era there is one key question. Which resource really holds the world by the throat? Once it was coal, then oil, and today we might say lithium or rare metals. But in the background, quietly and without much fanfare, a new resource is emerging — one that might not look like a resource at first glance, especially to those used to strictly tangible things: computing power.
At first sight it seems rather abstract. Artificial intelligence, “the cloud,” apps… it sounds invisible, almost magical. But behind every “smart” service are very concrete halls full of machines, kilometers of cables, rivers of electricity, and chip factories that run 24 hours a day. This is not a “virtual world,” even if that’s how we, the end users, often experience it. It is a (relatively new) multibillion-dollar industry, with its own mines, factories, and geopolitical tensions.
In this text we will try to explain one key idea that is necessary for understanding everything that is coming — and already exists around us — and to show that computing power is a real, limited resource, just like oil. And that states which lack enough of it will increasingly depend on those that have it. Which means a new division of power, a new kind of dependence, and a new question of sovereignty (namely, who actually owns “the machines that think”?)
The birth of a new strategic force: Computing power
If the 20th century was the century of oil, then the 21st century is becoming the century of computing power. Oil powered tanks, trucks, and factories. Today, computing power drives something even more sensitive: decision-making systems. It runs algorithms that control traffic, assess creditworthiness, assist doctors in diagnostics, and determine what we see on our phones and social networks. It may not sound as “powerful” as oil in a truck, but that’s mostly due to our own perception if we grew up in a world without the internet or smartphones. In practice, this new resource is far more powerful.
Imagine a patient coming for an exam, and the doctor uses an AI-powered system to analyse an X-ray. For the user, it’s just a click on a screen. But for that click to exist, huge models trained on millions of images operate in the background, housed in data centers that consume electricity like a small city. That is computing power in action.
The same goes for navigation, weather forecasting, stock trading, military technology, and political campaigns. Whoever has greater computing power can process more data, learn from it faster, and react quicker. This is a new kind of speed — no longer the speed of vehicles or transport, but something we might call the thinking speed of an entire society.
That’s why computing power is no longer just a technical term. It is becoming a strategic resource. Some states and corporations are stockpiling it, building their “digital refineries,” while others can only rent someone else’s capacities — as if renting someone else’s intelligence. Needless to say, those with the “resource” will dominate those without it.
What computing power actually consists of
When we say “computing power,” many think of a stronger computer or faster phone. But behind that term is an entire complex ecosystem, something like a combination of a refinery, power plant, factory, and university all in one.
The first layer is the chips and processors — tiny pieces of silicon where calculations take place. A special category is GPUs, which have become fundamental for training AI. Their production requires ultra-precise machinery, large supply chains, and years of development.
The second layer is data centers — large facilities filled with racks of servers. They must be connected to a powerful electrical grid, have cooling (often using vast amounts of water), and reliable connectivity. These are the “factories” of computing power: most of the calculations that run today’s digital life happen there.
The third layer is energy. Computing power is not free. Every calculation uses electricity. Training a single large AI model can consume as much electricity as thousands of households over a certain period. The more “smart” systems we want, the more we must think about where that energy comes from. Of course, few consumers think about this: the system “just works,” like magic — but what we see is only the front of the stage.
The fourth layer is knowledge. Experts who know how to design chips, build data centers, write algorithms, and maintain everything. Without the people who understand these systems, the equipment is worth little — like a refinery without engineers. And while some claim AI will soon replace all “thinking workers,” that is not quite true. It’s true that beginner programmers are facing tough times. But the architects of entire systems are people, not machines — and they will remain indispensable for a long time.
And finally, there is capital. Everything described, from chip factories to global data-center networks, requires hundreds of billions of dollars. The story of resource concentration repeats itself, which is why computing power is ending up in the hands of a small number of states (and an even smaller number of corporations).
Put together, the picture is clear. Computing power is neither “magic” nor an abstract idea. It is a very concrete resource made of metal, silicon, energy, land, buildings, and knowledge. And that is why in the coming years we will increasingly see competition not only for oil, gas, or lithium, but for access to this new digital form of power.
The global map of digital power
If we look at the world through the lens of computing power, the map looks different from the one we know. It is not divided simply into a “rich North” and “poor South,” but into a few dense hubs of digital power and a large periphery connected to them.
The biggest concentrations of computing power today are found where three expected factors intersect: advanced chip industry, large capital, and global tech companies. These are states that have invested in research for decades, have strong universities, and can afford data centers that cost as much as modern power plants. They don’t buy ready-made services — they literally own “the machines that think.”
The next group consists of large but partially dependent countries. They may have strong industries or large markets, but they must import advanced chips or rent computing capacity from others. In some areas they can be very strong, but in the key links of the chain — advanced processors or AI models — they still depend on others.
And finally, there are many smaller or less developed countries that have neither chip industry nor large data centers (it’s not hard to guess which group we belong to). They rely entirely on the cloud — infrastructure controlled by someone else. At first this seems practical: you pay for a service and everything works. But, as always in history, the one who provides the service has more power than the one who uses it.
Computing power as an instrument of domination
Why does it matter who has computing power? Because it is increasingly becoming political, economic, and even cultural power.
Imagine two countries. Both want to modernize healthcare, education, transportation. The first has its own data centers and enough computing power to train and run national AI systems. The second does not, so it must use cloud solutions from foreign companies. The difference is enormous. The first decides how its data is used and what values are embedded in the systems that issue recommendations. The second effectively imports someone else’s algorithms — and with them, someone else’s priorities.
In military terms, computing power means faster processing of satellite images, more precise guidance systems, and more efficient logistics. Whoever can analyse thousands of images or sensor data in seconds has an advantage over those who rely on manual or slow systems. As radar and airplanes once defined dominance, today it is the speed of “seeing” and “assessing.”
In the economy, computing power enables automation, predictive analytics, and supply-chain optimization. Large companies that possess major AI models can plan production better, target advertising more precisely, and detect trends faster. Small companies and states without their own infrastructure lag behind and often have to pay for the very tools that surpass them.
Even culturally, computing power becomes an instrument of domination. Language models that “understand” one language better than another, algorithms that push certain content, systems that filter information… All of this shapes how people perceive the world. If most such systems are developed in a few centers of power, the global narrative shifts toward their frameworks.
Private giants and the new “technological hegemony”
So far we have talked about states, but a crucial point remains: computing power today largely belongs to private companies. This is a relatively new situation. With oil, states ultimately had the final say through national companies and regulation. In the digital world we increasingly see the opposite — states depend on private “digital oil companies.”
Large tech corporations now own global data-center networks, undersea cables, AI labs, and teams building models that we can scarcely imagine. They don’t just control tools but the very infrastructure of “thinking” — who can run what, at what price, and under what defaults. States wanting modern digital services often choose them because it is cheaper and faster than building everything from scratch.
A state gets functional systems; the company gets a new client. But long-term dependency grows — and this may be the key point of the entire story. This dependency will be transformative, especially for countries like ours, those in the “category 3” group.
If key public services — from government administration to health registries — rely on the infrastructure of one or a few companies, political maneuvering space shrinks. Negotiations about prices or conditions start resembling negotiations with a monopolist.
Moreover, these companies increasingly decide who gets access to advanced models and computing power, and under what terms. This means that private actors, rather than democratically elected governments (or any government), determine who gets a “digital advantage” in the economy, science, or media. This is a new form of hegemony — not through bases or currency, but through control of the machines that process data and shape conclusions.
Thus, the conversation about computing power should no longer be just a technological question. It is a question of power — who controls the key resources of society, who sets the rules, and who ends up a user versus a subject in the digital order.
The global divide: who loses digital sovereignty
Digital sovereignty is simple to define: the ability of a society to decide where its data is, who processes it, and whose algorithms make recommendations and decisions.
Countries with little computing power are becoming “digital tenants.” Instead of owning their machines and models, they rent them. This works — until it doesn’t. What happens when the provider changes terms, prices, or political position? What if sanctions are imposed, chip exports banned, or access to advanced models restricted?
A similar divide emerges within societies. Large corporations can accumulate computing power and use advanced tools, while small businesses, public sectors, or schools are stuck with “lighter” versions. Inequality deepens. Those at the top gain stronger tools; the rest depend on their goodwill.
We are moving toward a world divided between those with their own “digital power plants” and those living off someone else’s socket. The first have maneuvering space; the second hope someone keeps the plug in.
Challenges for small states
Small states, even relatively wealthy ones, realistically cannot build full infrastructure from chip factories to global data centers. But they are not doomed to digital dependence. There is room to avoid subordination — with the right priorities.
The first step is to recognize computing power as a strategic resource, not just an IT expense. This means investing in basic national infrastructure: public or shared data centers, secure energy supply, education of experts, and clear data-governance rules. They don’t need “everything,” but they need something truly their own. Unfortunately, what do many countries do? Croatia is an example — we pile up weapons for pointless wars, whether against Russia or some new geopolitical reshuffling in the region. These are catastrophic decisions that will make us limp behind the world — and when it becomes too late, it will be too late forever.
The second step is alliances. Just as small states once cooperated on energy or transport projects, now they can join forces on computing infrastructure: shared AI clusters, regional centers, partnerships with open-model ecosystems and universities.
The third step is choosing battles wisely. Competing in everything is impossible, but building national niches is realistic. Specialized models for local languages, public administration, healthcare, education… Wherever sovereignty matters most, that’s where computing power should be invested.
Conclusion: The future in the age of thinking machines
Computing power may have no smell, it may not flow through pipes or sit in tanks, but its consequences resemble those of classic resources that defined eras. Those who have it accelerate development; those who don’t slip into the role of users of others’ decisions.
In coming years we will hear more about new AI models, stronger algorithms, bigger data centers. Behind all those headlines will be the same question: Who controls the machines that think, and who merely sends them prompts?
Recognizing computing power as a resource doesn’t mean panic — it means seeing reality clearly. We are still relatively early in this new era. Societies that understand what is really at stake — that technology is also power — will have a chance to be more than just “connected” users.
Ultimately, the story of computing power is a story about who will govern the collective intelligence of humanity. If we hand everything over to a few centers of power, we won’t just lose data or market share. We will lose part of our right to think about our own future — or, to be a bit dramatic, part of what makes us human.
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