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Power Shortages Threaten to Derail the Trillion Dollar AI Boom
PR Newswire
NEW YORK, June 29, 2026
FN Media Group Presents Oilprice.com Market Commentary
NEW YORK, June 29, 2026 /PRNewswire/ — You might think that Shark Tank’s “Mr. Wonderful,” Kevin O’Leary, is betting it all on AI, but he is not. He is betting on the $5+ trillion in infrastructure required to run it, and that’s where big capital is flowing now. And he’s betting on Bitzero (AIBZ) to be one of the first to break AI’s biggest chokepoint: power. Companies mentioned in today’s commentary includes: Bitzero Holdings Inc. (AIBZ), Microsoft Corporation (NASDAQ: MSFT), NVIDIA Corporation (NASDAQ: NVDA), International Business Machines Corporation (NYSE: IBM), Digital Realty Trust, Inc. (NYSE: DLR), Quanta Services, Inc. (NYSE: PWR).
Bitzero was looking further ahead while most of the rest of the market was narrowly focused on AI software and semiconductors.
As a result, on May 5th, Bitzero signed a binding letter for a 15-year lease deal for AI power as it makes its first official leap from low-carbon bitcoin mining to being a power provider for a $5-trillion data-center industry that is desperate for cheap electricity.
Amazon alone projects $200 billion in 2026 capital spending, with most of it tied to data centers. Microsoft is expected to be around $190 billion. Alphabet is also projected near $190 billion, and Meta has laid out a $600 billion U.S. infrastructure plan through 2028. Current estimates now put combined 2026 capex for Amazon, Microsoft, Alphabet, and Meta as high as $725 billion, driven largely by AI data centers, chips, power, and long-lived infrastructure. McKinsey estimates another $5.2 trillion will be deployed into AI infrastructure this decade. That capital is funding land, power, facilities, substations, and equipment before AI capacity can operate.
The AI Build List Is Under Duress
A large share of the AI data centers being announced today may never reach completion because power is not available when projects need it. That creates an advantage for companies like BitZero (AIBZ) that already control gigawatt-scale electricity.
Artificial intelligence demand is expanding quickly, but the electricity required to run it is becoming harder to secure, slower to connect, and more expensive to deliver.
More than 70% of interconnection requests are withdrawn, and only a small portion reach operation. At the same time, global data center electricity demand is projected to approach 945 terawatt-hours by 2030, roughly equal to Japan’s total consumption.
While many were previously focused on semiconductor chips as the make-or-break element of the AI boom, it’s now clear that it’s a question of power above all. And that’s exactly why a forward-thinking cryptominer like Bitzero is well positioned to take advantage of the AI-power gap.
“As electricity prices climb across the U.S., driven in large part by soaring demand from both Bitcoin mining and the rapid expansion of AI data centers, Bitcoin miners are at a distinct advantage because we locked in power access well ahead of the curve,” Mohammed Bakhashwain, founder and CEO of Bitzero Holdings, Inc., told Oilprice.com in a recent interview.
Full Speed Ahead on the Biggest Boom in Computing History
Earlier this month, Bitzero (AIBZ) completed engineering due diligence for up to 520 megawatts at its Kokemäki, Finland campus, eyeing up to 1GW at full ramp. An initial 80MW phase is targeted for the first half of 2027, with 400MW to 800MW expected to follow in later stages as the full buildout advances. And that’s just one venue.
Bitzero’s Norway operations are already running as a fully built industrial platform. The company is operating Bitcoin mining at power costs below four cents per kilowatt-hour, which keeps the site active and monetized while additional infrastructure is layered on top.
At Namsskogan, the next 70MW tranche is scheduled for energization in the fourth quarter of 2026, tied directly to a defined 325MW expansion corridor that follows existing grid capacity. And here, in Norway, is where Bitzero’s great leap into data center power just became official.
On May 5, Bitzero signed a binding letter of intent with OneQode Networks covering the full 110 MW capacity of its Namsskogan, Norway data center site under a 15-year lease tied to GPU-based AI workloads. The agreement carries an implied value of roughly $2.6 billion over the lease term, and marks Bitzero’s formal entry into the large-scale AI data-center infrastructure market.
When it mines in Norway, Bitzero uses its own electricity to generate revenue from the Bitcoin it produces. Under the AI agreement, Bitzero generates revenue by leasing the site’s power capacity and infrastructure to OneQode. Simultaneously, OneQode pays the electricity bill tied to running the AI systems inside the facility.
That means Bitzero captures the recurring infrastructure revenue from the site without directly absorbing the massive ongoing power costs associated with operating large-scale AI workloads.
According to Bitzero management, at full utilization of 110 MW, the Namsskogan site could generate roughly $176 million to $178 million in annual revenue. A recent shareholder analysis modeling the agreement estimated potential annual NOI of roughly $151 million based on an 85% margin profile tied to the lease structure.
It’s the plentiful, low-cost, low-carbon energy Bitzero has harnessed in Scandinavia that OneQode is after.
Norway is served by hydro power, and Finland is served by a cocktail of low-cost hydro, nuclear, solar and wind energy.
Finally, the North Dakota footprint gives Bitzero a second operating lane tied to U.S. demand. The company controls power-backed sites there that position it inside a different pricing and regulatory environment from its Nordic assets.
The AI Investment Model Is Outrunning The Grid
It takes up to 7 years to build out a large-scale power source to feed a data center. Still, the market has been operating on a massive assumption: That the power will magically be there once all the data centers are built. This is where the data center hype meets an electrification reality. But securing power isn’t that easy. At a bare minimum, it requires grid studies, transmission access, permitting, utility negotiations and long-term pricing frameworks. And demand is bursting.
The IEA expects global data-center electricity use to grow 4X the growth rate of total electricity demand from every other sector combined. The agency is eyeing data center power demand of roughly double to around 945 TWh by 2030. Similarly, Goldman Sachs has forecast data-center power demand soaring 175% by 2030 compared to 2023 levels.
The business of sourcing power is not keeping pace with the business of building out data centers. We will need $6.7 trillion in capital by 2030, including $5.2 trillion for AI infrastructure alone, in order to make the data center hype a reality. Yet, so far, grid investment expected to support that demand is only around $720 billion.
Why Bitzero’s Model Is Getting Attention
Bitzero (AIBZ) is building large-scale campuses backed by secured, low-cost power and positioning them for AI and high-performance computing demand. It’s not choosing between crypto and AI. It is running both. Bitcoin mining keeps capacity active and generates cash flow, while the same sites are being developed to support AI and HPC workloads as that demand scales.
“We see a really big opportunity in HPC,” CEO Mohammed Bakhashwain said, pointing to an engineering team that has already worked on deployments with Microsoft and Nscale in Norway. The company controls land, power, and infrastructure in place to deliver large campuses, and is already moving to market that capacity to AI tenants.
The model is built to capture two revenue streams off the same megawatts. Mining today and higher-value AI and colocation tomorrow.
“We’re hoping to get the best of both worlds—the long-term, investment-grade cash flows from HPC and AI, while having exposure to Bitcoin,” Bakhashwain said. That keeps sites operating while capacity is repositioned for larger, longer-term contracts.
The company is building capacity that can be deployed into whichever market pays more at a given time. That is how the same infrastructure can generate cash flow today and scale into larger contracts as AI demand continues to build.
Other companies to keep an eye on:
Microsoft Corporation (NASDAQ: MSFT) is in the middle of the largest infrastructure build-out in its history. The company pledged roughly $80 billion toward AI-enabled data centers in fiscal year 2025, with more than half targeted at U.S. facilities, and has already begun scaling a new AI campus in Wisconsin at a cost exceeding $7 billion. The Mount Pleasant facility alone is designed to house hundreds of thousands of Nvidia GPUs in clustered formations for training frontier AI models.
The financial results back up the ambition. In Q1 FY2026, Microsoft posted $77.7 billion in revenue, up 18% year over year, with Azure and other cloud services growing 40%. The company’s commercial backlog hit $392 billion, up 51%, meaning future revenue is largely already booked.
If there’s a single company that sits at the center of the AI data center story, it’s NVIDIA Corporation (NASDAQ: NVDA). The chipmaker reported record Q1 FY2027 revenue of $81.6 billion, up 85% year over year, with data center revenue alone hitting $75.2 billion, a 92% jump from the same period last year.
The driver is agentic AI. Where conversational AI tools are relatively token-efficient, coding agents and multi-agent systems can consume anywhere from 5 to 30 times more compute per task. That multiplier effect is running straight through NVIDIA’s order books. Hyperscalers made up slightly over half of NVIDIA’s data center revenue, but the rest of the customer base is growing faster, a sign that enterprise adoption is broadening.
International Business Machines Corporation (NYSE: IBM) is the most contrarian name on this list in the context of an AI data center article, and that’s exactly what makes it interesting. Q1 2026 revenue hit $15.9 billion, up 9% year over year, with Software revenue of $7.1 billion, up 11%, and free cash flow of $2.2 billion — the strongest Q1 FCF in a decade. Software ARR reached $24.6 billion, up 10%.
The AI connection runs through Red Hat OpenShift, which hit a $2 billion ARR run rate, and IBM’s watsonx AI orchestration platform, which enterprises use to deploy and govern AI agents across hybrid environments. CEO Arvind Krishna has been explicit that AI is a tailwind for the mainframe business, where the IBM Z17 cycle is driving a 48% year-over-year surge in infrastructure revenue as enterprises move AI inference workloads onto on-premises infrastructure for latency, cost, and data sovereignty reasons.
Digital Realty Trust, Inc. (NYSE: DLR) is the other name that dominates the data center REIT conversation, though it operates in a different part of the market than Equinix — focused more heavily on large-scale wholesale hyperscale leases rather than colocation and interconnection. In Q1 2026, the company signed the largest hyperscale lease in its history — a 200 megawatt deal in Charlotte — and delivered double-digit growth in constant-currency core funds from operations per share. Annualized base-rent bookings hit $707 million in the quarter.
The strategic context matters here. AI tenants in 2026 are signing commitments that are materially different from the hyperscale deals of a few years ago — larger in size, longer in duration (15-year terms are now the norm), and pre-leasing 24 to 36 months before facilities deliver.
Quanta Services, Inc. (NYSE: PWR) builds and maintains the electrical infrastructure that connects data centers to the grid — transmission lines, substations, high-voltage distribution systems, and the last-mile electrical work that no data center can operate without. CEO Duke Austin has pegged the company’s addressable opportunity at $2.4 trillion through 2030, driven by data center electrification, grid hardening, and renewable interconnection combined.
The constraint driving Quanta’s order book is simple physics: large transformers for high-voltage substation connections have lead times of two years or more, and the skilled labor to install them is in short supply nationally.
By. Charles Kennedy
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