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NEW YORK, July 10, 2026 /CNW/ -- Every great economic era has been defined by a fight over a single resource. In the 19th century, it was coal, and the British Empire was built on top of it. In the 20th century, it was oil, and the modern Middle East and American postwar dominance were both shaped by who controlled the flow. In the early 21st century, semiconductors became the world's most critical asset, sparking the rise of Taiwan, growing trade tensions with China, and the creation of several multi-trillion-dollar tech giants. The next fight is already underway, and almost nobody is talking about it in those terms yet. Companies mentioned in today's commentary includes: Bitzero Holdings Inc. (AIBZ), Broadcom Inc. (NASDAQ: AVGO), Palo Alto Networks, Inc. (NASDAQ: PANW), SpaceX (NASDAQ: SPCX), Oracle Corporation (NYSE: ORCL), Palantir Technologies Inc. (NASDAQ: PLTR).
The resource in contention this time is electricity. Specifically, the kind of clean, secure, large-scale electricity that AI workloads consume by the gigawatt. The companies that control electricity may likely be able to dictate terms to the rest of the AI economy for the next two decades. The countries that hold it are about to find themselves with strategic leverage they have not enjoyed in a century. And the small handful of players who locked in AI-grade power capacity before the surge may soon look very different from what they do today.
One of these players is Bitzero Holdings Inc. (AIBZ), a Canadian-listed Bitcoin miner with infrastructure across Scandinavia and in the United States that just signed a binding letter for a 15-year, $2.6 billion lease to host enterprise AI workloads at its Norway site. The deal is one of the early visible moves in a war that is going to define the next era of the global economy.
The Resource That Decides the AI Century
To understand why power has become the new strategic chokepoint, start with what the AI economy actually consumes. A single ChatGPT query consumes roughly 10 times the energy of a Google search. Training the next generation of large language models requires the equivalent power draw of small cities. Industry forecasts from McKinsey now put AI data center capital expenditure at roughly $5.2 trillion between now and 2030. Goldman Sachs Research projects global data center power demand will surge up to 165% by 2030 compared to 2023 levels.
That kind of growth has no historical analog. The closest comparison is the early industrial era, when entire economies reorganized around coal. The difference is speed. The industrial revolution played out over a century. The AI buildout is being attempted in a decade.
The world simply does not have enough clean, reliable, large-scale electricity to deliver on what the AI industry is promising. Not in the United States. Not in Europe. Not in Asia. The shortage is everywhere, and the timeline to fix it through new generation, transmission, and interconnection runs ten to fifteen years at a minimum.
Which means the people who already hold AI-grade power capacity, in the right jurisdictions, with the right cost structure, are sitting on something that the rest of the AI economy needs and cannot replicate. The war is being fought on four fronts. Each one matters in its own right. Together, they explain why the AI power economy of 2035 is being decided right now.
Front One: The U.S. Hyperscalers Are Already Spending Billions
The most visible front of the war is in the United States. The hyperscalers have looked at the grid, looked at their AI roadmaps, and concluded that the gap between what they need and what the utilities can deliver is unbridgeable on any reasonable timeline. So they are bypassing utilities entirely.
Microsoft signed a 20-year deal to restart the Three Mile Island nuclear plant, a facility offline since 2019, specifically to feed AI workloads. Amazon paid $650 million for a single data center campus co-located with the Susquehanna nuclear station in Pennsylvania. Google announced agreements with Kairos Power for small modular reactors. Meta has issued a request for proposals seeking up to 4 gigawatts of new nuclear capacity.
These are companies committing billions of dollars to lock in clean electricity ten and twenty years in advance. Not because power markets are functioning well, but more likely because the hyperscalers have concluded that without long-term secured power, their entire AI strategies may fall apart.
Front Two: Europe Is Quietly Closing the Door
While the U.S. hyperscalers scramble for nuclear plants, the European jurisdictions with the best AI power profiles in the world are quietly making sure their capacity stays in domestic hands. Nowhere is this clearer than in the Nordic countries. Norway, Finland and Sweden sit on top of massive hydroelectric and nuclear generation, in cold climates that slash cooling costs, with stable governments and EU data sovereignty protections built in. For AI workloads, the combination is close to perfect.
This is the front where Bitzero (AIBZ) sits. The company is a licensed grid operator in Norway with direct connections to hydroelectric power plants, all-in power costs of roughly 3 to 4 cents per kilowatt-hour and more than 1 gigawatt of secured capacity across four sites in Norway, Finland and the U.S. It built that position years before the AI boom turned Nordic power into a strategic asset, and the regulatory door has closed behind it.
Front Three: The Middle East Is Buying Into Both Sides
A third front is opening up that very few American investors are watching carefully. The Gulf states, sitting on sovereign wealth that runs into the trillions, have looked at the AI power race and decided they want a position in it.
The UAE, in particular, has been moving aggressively. Phoenix Group, the publicly-listed Bitcoin miner ranked tenth globally by market capitalization and based in Abu Dhabi, has been quietly building positions in critical AI and crypto infrastructure for years. Phoenix holds a 20.8% equity stake in Bitzero and a board seat. That is sovereign Gulf money taking a long position in Nordic power infrastructure that hosts AI workloads, and it is a pattern likely to repeat across other AI-power assets globally.
Saudi Arabia, Qatar, and Kuwait are pursuing similar plays through their own sovereign wealth vehicles. The Gulf states understand exactly what is happening. The petrodollar century is winding down, and the AI power century is winding up. The capital that built the modern Gulf economy is being repositioned for the next era, and AI-grade power infrastructure sits high on the list of strategic targets.
Front Four: China Is Building Its Own Closed System
The fourth front is the most isolated and the hardest to assess from the outside. China has watched the global scramble for AI-grade power and concluded that it needs to build its own self-sufficient ecosystem, walled off from Western supply chains and Western capacity constraints.
Beijing has poured state capital into massive coal, nuclear, and renewable buildouts specifically targeted at supporting AI infrastructure within Chinese borders. The country has also imposed strict restrictions on cross-border data flows that effectively prevent Chinese AI workloads from running on Western infrastructure.
Why the Winners Are Already Set
The winners of the AI power war are not the companies that will start building tomorrow. They are the companies that locked in their positions years ago and are now executing on the demand wave.
Bitzero (AIBZ) is a clean example of what that looks like at the small-cap scale. The company built its Norway position years before the OneQode lease deal was conceivable. The infrastructure is in place. The power is secured. The regulatory protection is locked in. And in May 2026, the first major AI tenant signed a binding 15-year, $2.6 billion lease for the entire 110 megawatts at the Namsskogan site.
Every piece of the playbook is in motion. The power is locked in, the latest NVIDIA chips are running on it, a global cloud partner is moving the resulting compute to enterprise customers, and the first major AI tenant is already on the hook for an estimated $2.6 billion over fifteen years. This is the convergence trade the broader power war makes possible, and the market still has not priced what it adds up to.
Other companies to keep an eye on:
Broadcom Inc. (NASDAQ: AVGO) makes the custom AI accelerators -- XPUs -- that hyperscalers like Google, Meta, and ByteDance design to run specific workloads more efficiently than off-the-shelf GPUs. It also makes the networking chips that connect those accelerators inside large AI clusters. In Q1 FY2026, AI semiconductor revenue surged 106% year over year, with the company guiding Q2 AI revenue to $10.7 billion, a 140% jump from the same period a year earlier.
The custom chip story is different from NVIDIA's in an important way. Broadcom's customers are designing their own silicon precisely because they want a different price-performance profile than standard GPUs offer -- and Broadcom is the company that builds those designs at scale.
Palo Alto Networks, Inc. (NASDAQ: PANW) - Palo Alto Networks is the company most directly positioned to capitalize on that problem. Q3 FY2026 revenue grew 31% year over year to $3.0 billion, with Next-Generation Security ARR growing 60% to $8.1 billion. Remaining performance obligation grew 36% to $18.4 billion.
CEO Nikesh Arora framed the quarter directly: "The latest advancements at the AI frontier have increased the level of urgency around cybersecurity, and redefined the shape of the industry for the coming years." That's not just marketing language. As AI agents begin executing real tasks inside enterprise systems the attack surface expands by an order of magnitude.
SpaceX (NASDAQ: SPCX) - SpaceX completed the largest IPO in history on June 12, pricing at $135 a share for a $1.77 trillion valuation and topping $2 trillion in market cap on its first trading day. The listing raised roughly $75 billion and made Elon Musk the world's first trillionaire on paper. But the AI data center story here isn't really about rockets. It's about what SpaceX became after merging with xAI in February: a company that now describes itself in its own IPO filing as the operator of "the largest AI training data center clusters on Earth."
Those clusters are Colossus 1 and Colossus 2, the xAI supercomputers built near Memphis, Tennessee, originally to train Grok. In May, SpaceX struck a deal with Anthropic that hands over essentially the entire Colossus 1 facility -- more than 300 megawatts of capacity across roughly 220,000 NVIDIA GPUs, including H100, H200, and GB200 accelerators.
Oracle Corporation (NYSE: ORCL) - Oracle spent most of the last decade being written off as legacy enterprise software. The AI infrastructure buildout has turned that narrative upside down. Q4 FY2026 revenue hit $19.2 billion, up 21% year over year, with Cloud Infrastructure (IaaS) revenue up 93%. The figure that stops people in their tracks is the remaining performance obligation: $638 billion, up $85 billion in a single quarter .
Its CEO Larry Ellison has been direct on earnings calls: the company is building data centers specifically designed around AI training and inference, using natural gas fuel cells for cleaner on-site power generation, and reducing time from rack delivery to revenue by 60% through standardized designs and scaled installation processes.
Palantir Technologies Inc. (NASDAQ: PLTR) - Palantir sits in a different part of the AI data center stack than most names on this list -- it's the software layer that makes the data inside those data centers actionable for governments and large enterprises. Q1 2026 revenue grew 85% year over year to $1.633 billion, the company's fastest growth rate since going public in 2020.
The government side of the business is increasingly anchored by AI-enabled defense and intelligence programs. Palantir's Maven AI system -- which analyzes battlefield data and supports targeting and command decisions in real time -- is moving closer to becoming a formal U.S. Department of Defense program of record.
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