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Most AI data centers may never be built. Blame the 'bragawatts.'

Kevin O'Leary speaks during the Romain College of Business Innovative Speaker Series at the University of Southern Indiana Wednesday, Sept. 23, 2026.
Kevin O'Leary speaks at the University of Southern Indiana.

MaCabe Brown / Courier & Press / USA TODAY NETWORK via Imagn Images/Reuters

  • Newcomers like Kevin O'Leary face skepticism due to a lack of experience in data center development.
  • Bernstein analysts dubbed O'Leary and others "bragawatts."
  • Most announced projects will never happen. "Press releases are cheap…concrete is not."

The AI industry has a problem with bragging.

Companies are announcing enormous new data centers to power the AI boom. Some promise facilities bigger than anything the industry has built before.

There's just one problem: Most of these projects may never happen.

Bernstein Research analyzed thousands of planned US data centers and concluded that only about 35% of the announced capacity is likely to get built. That's roughly 170 gigawatts of data center capacity out of a total of almost 500 gigawatts.

The rest? A significant chunk of it belongs to a category the industry has a wonderfully dismissive name for: "Bragawatts." These are ambitious announcements, often from newcomers with little experience building data centers, that have a slim chance of becoming reality.

"Press releases are cheap…concrete is not," Bernstein analysts wrote in a research note.

Among 8,268 tracked US facilities: Announcement 4,377; Active 2,126; Construction 861; Not Approved/Withdrawn 744; Delayed 89; Land Bank 61; Cancelled 10.

Bernstein began its analysis with more than 7,000 data center projects across North America, drawing on information from Aterio, a company that tracks construction through satellite imagery, permits, and other records. The analysts narrowed that to more than 5,000 projects (partly by excluding those already canceled).

Then they assessed the chances of these remaining projects being completed. The analysts considered factors such as whether construction had started, whether electricity was available, and whether the companies involved had successfully built data centers before.

The results revealed a striking divide.

The 'bragawatt brigade'

Kevin O'Leary
Kevin O'Leary.

Daniel Delgado Jr./Disney via Getty Images

Experienced operators including Amazon, Google, Microsoft, and Meta landed at the top. Bernstein gave these companies perfect scores of 5 out of 5 for their development credentials. Other data center specialists, such as Digital Realty, Equinix, and CoreSite, got top marks, too.

O'Leary Digital, associated with celebrity investor Kevin O'Leary, ended up at the bottom, with a credibility score of 0.35 out of 5, according to Bernstein. His company has announced 15 gigawatts of data center projects, and Bernstein estimates that only 489 megawatts, or about 3%, will actually materialize.

"Sorry, Kevin," the analysts wrote.

Although the term "bragawatts" has been doing the rounds in the data center industry lately, it's unclear who coined it, Bernstein analyst Madison Rezaei told me.

"I wish I could take credit for that," she said. "I believe I originally heard it from an Equinix executive, but I don't think he owned it either."

She said that while some ambitious newcomers could succeed, they haven't yet demonstrated they can deliver.

"It's not that all of these guys are sort of terrible and not going to deliver, but we just have lower confidence because we don't know them," Rezaei said.

O'Leary Digital responds

O'Leary Digital disputed Bernstein's assessment, saying the research doesn't account for substantial work that occurs before construction begins.

While acknowledging that O'Leary Digital is a young company, CEO Paul Palandjian said the team has decades of experience building major infrastructure projects and that its proposed 15 gigawatts of capacity would be built in stages over several years.

The company said it has secured binding agreements covering about 11,000 acres in Utah and 13,000 acres in Alberta, obtained a 30-year development agreement in Utah, and made progress on planning, engineering, and permits at both sites. It also said the projects would generate their own electricity.

The company said its early development work is funded, additional capital is committed to reaching key milestones, and experienced engineering and construction partners are involved.

"We would rather be judged on milestones than on a model," Palandjian said.

'An announcement in search of a project'

Opponents of the proposed La Osa data center attend a Pinal County Board of Supervisors meeting in Florence, Arizona, on Aug. 26, 2026.
Opponents of the proposed La Osa data center attend a Pinal County Board of Supervisors meeting in Florence, Arizona, on August 26.

USA TODAY Network via Reuters Connect

Other low scorers in the "bragawatt" brigade included Vermaland and Joule Capital Partners, according to Bernstein analysis based on Aterio data.

Joule has announced 50 data center projects with a combined capacity of 11.7 gigawatts. Bernstein estimates that only about 11% of that capacity will actually get built. Almost all of Joule's planned capacity remains at the announcement stage, with little evidence of construction progress or of major customers committing to use the facilities, Bernstein wrote in a July note to investors.

The analysts gave Joule a credibility score of 2.05 out of 5, placing it among the lowest-ranked developers in its database.

"An announcement in search of a project," the analysts wrote.

Vermaland has announced plans for a massive data center project in Arizona. Bernstein estimates that only 4% of its proposed 2.2 gigawatts of capacity will get built. The company is primarily a landowner, not a data center developer. Its proposed $33 billion La Osa project near Eloy had already been sharply scaled back amid local opposition and without construction approval. In late August, regulators formally rejected the project. Even before that, the analysts gave Vermaland a credibility score of 0.75 out of 5.

Joule and Vermaland didn't respond to emails seeking comment this week.

A yawning gap for data centers

Sergio Toro, CEO of Aterio, sees similar patterns in his firm's voluminous, detailed data.

Aterio's tracking shows that roughly 30 to 40 gigawatts of new data center capacity get announced each month. Yet only about 7 gigawatts begin construction each month, while 2 to 3 gigawatts actually start operating.

This leaves a yawning gap.

Many announced projects get withdrawn before construction begins — and before real money has been spent.

"They just make the announcement, but they didn't get their approvals. Or they make multiple filings in multiple locations to see which one gets selected," Toro told me. "That's why we track with satellite if there's real movement on the ground or not."

Indeed, Bernstein analysts wrote recently that the amount of "stranded" data center capacity has surged. These are projects that are either canceled, delayed, or not approved.

Column chart showing total stranded data center capacity rising from 14.2 gigawatts in August 2025 to 49.6 gigawatts in August 2026. Stranded capacity means projects canceled, delayed or not approved. Monthly totals are 14.2, 18.1, 20.0, 20.9, 21.2, 24.7, 25.5, 28.9, 32.4, 34.3, 38.2, 43.1, and 49.6 gigawatts.

The AI boom's three tiers

Toro sees three broad groups competing to build AI infrastructure.

At the top are the established technology giants, including Amazon, Microsoft, and Google. They've built data centers for decades and generally deliver on their commitments. Most of their projects will get done, he said.

In the middle are "neoclouds," newer companies such as CoreWeave that rent out computing power specifically for AI. Although they're more vulnerable to financing problems and delays, many are making solid progress, especially because some of these players already have access to electricity.

"We see them advancing quite well," Toro said. "Sometimes we see some delays, but it's not something significant or any kind of big capacity that is at risk."

Then come the newcomers making extraordinary promises. That's where most delays and cancellations happen, Toro said.

Even Amazon needs a backup plan

NEW CARLISLE, INDIANA - OCTOBER 2: In this handout provided by Amazon, a technician works at an Amazon Web Services AI data center in New Carlisle, Indiana on October 2, 2025.
A technician works at an Amazon Web Services AI data center in New Carlisle, Indiana.

Noah Berger/Getty Images via Amazon Web Services

Not every project that disappears was a fantasy, though. Even a top player like Amazon struggles sometimes to secure electricity and other supplies on time for these huge projects.

Business Insider's Eugene Kim reported exclusively this week on the challenges Amazon faces with its record AI buildout.

The biggest, most experienced tech companies deliberately pursue more potential data center capacity than they need because they know some developments will fail or get delayed.

Major AI companies were committing to three or four times the space and electricity they needed over the following two years, Jeffrey Moerdler, a data center lawyer, estimated during an interview with Bernstein analysts.

His reasoning: Of data center projects that haven't started construction, roughly a third will arrive on schedule, another third will be delayed, and the remainder won't happen.

Rezaei and Toro estimate that the top players don't over-commit that much — more like double the capacity they need at most.

The strategy provides a "Plan B," as Toro put it, in case of delays involving electricity, equipment, permits, local opposition, or other factors.

Texas has a ghost problem

AUSTIN, TEXAS - JULY 03: In an aerial view, the Decker Creek Power Station is shown on July 03, 2024 in Austin, Texas. The state of Texas is developing plans to double its Texas Energy Fund of $5 billion. The move seeks to bolster an expansion of the power grid, as new predictions of surges in electricity usage loom.
The Decker Creek Power Station in Austin.

Brandon Bell/Getty Images

This helps explain another extraordinary number.

Data center companies have requested connections for roughly 450 gigawatts of electricity demand on Texas' main power grid, more than five times the grid's roughly 85 gigawatts of existing capacity, according to Toro and others. 

Many of those requests are placeholders rather than firm construction plans. Toro calls them "ghost projects."

These speculative projects clog the waiting lists for electricity connections, making the electricity shortage look a lot worse than it actually is.

"Developers routinely spam projects across several sites, and many are speculative builds with no customer yet," Ryan McEntush, a partner at venture capital firm Andreessen Horowitz, wrote in a recent blog. "Often these new developers have never even plugged in a GPU, let alone a power plant."

Texas has paused applications to review and weed out projects that aren't serious. Toro, from Aterio, expects this to favor the established players at the expense of the bragawatts.

The real AI boom

None of this means the AI infrastructure boom is imaginary.

Aterio tracks thousands of buildings, including major projects already under construction. Bernstein estimates that nearly 80% of the capacity the largest technology companies are directly developing is credible.

And when speculative projects disappear, Rezaei doesn't expect a wave of unpaid debt. Many will fail before building begins, the stage when developers borrow serious money through project financing.

Some of those missing data centers were never really coming in the first place.

Sign up for the AI Insider newsletter here. Reach out to me via email at abarr@businessinsider.com

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Tesla outsells all other brands combined as America's EV market resets

SpaceX and Tesla CEO Elon Musk mingles with guests as U.S. President Donald Trump hosts a state dinner for President of China Xi Jinping and first lady Peng Liyuan and in the East Room of the White House on September 24, 2026 in Washington, DCDC. Trump is hosting Xi for a three-day state visit to
Tesla CEO Elon Musk.

Kevin Dietsch/Getty Images

  • Tesla accounted for more than half of US electric-vehicle sales in the third quarter.
  • Its quarterly sales increase exceeded the entire market's gain, Cox estimates show.
  • High gas prices are helping EVs compete, though sales remain below last year's levels.

Tesla is taking a bigger slice of America's electric-vehicle market as high gas prices give drivers another reason to consider ditching the pump.

The company sold an estimated 144,094 vehicles in the US in the third quarter, up from 124,800 in the previous three months, according to Cox Automotive's latest sales report.

That increase was bigger than the gain for the rest of the US EV market. Put another way: Tesla drove the recovery. Everyone else, taken together, went backward.

Horizontal bar chart of the ten best-selling US electric-vehicle brands in Q3 2026. Tesla led with 144,094 sales, followed by Rivian with 19,239. Tesla sold more than all other brands combined, which totaled 118,555.

The figures offer a new twist on the EV comeback I wrote about in July. Back then, sales had finally improved after the slump that followed the end of federal incentives in the US. Several manufacturers were benefiting, but only those with the fortitude to stick with EVs after federal government support waned.

While recovery continued in the third quarter, it became more dependent on Tesla.

Americans bought 262,649 new EVs during the period, about 6% more than in the second quarter. Sales outside Tesla fell roughly 3%, based on a comparison of Cox's latest counts with its second-quarter report.

Tesla's own sales rose about 15% from the second quarter. It supplied 54% of the country's new EVs in the third quarter, extending its lead from the previous period.

High gas prices help make the case for going electric, according to Cox.

"With gas prices well above $4 a gallon, electric vehicles look better than ever," Stephanie Valdez Streaty, Cox's director of Industry Insights, said in the company's analysis of the quarter.

Expensive gasoline and diesel make running a conventional vehicle more painful. For drivers who can charge cheaply, particularly at home, an EV offers a valuable alternative to repeated trips to the pump.

There's an important caveat to the comeback story: Sales are improving from a depressed level.

Total US EV sales were down almost 40% from a year earlier. Last year's third quarter was unusually strong because buyers rushed to claim federal incentives before they disappeared.

Tesla's sales were down about 20% against that comparison. The company remains heavily dependent on two vehicles. The Model Y and Model 3 accounted for roughly 97% of its US sales in the latest quarter.

The Cybertruck sold over 4,300 units, and Tesla has stopped making the Model S and X. (There's a Roadster, though not until 2028).

So Tesla's growing dominance isn't a story of every model flying out of showrooms, or of selling more cars than a year ago.

For now, it is winning a larger share of a smaller market. As Americans return to EV shopping, Tesla is capturing more of their business.

Sign up for the AI Insider newsletter here. Reach out to me via email at abarr@businessinsider.com

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AI companies scraped the web. Now they want to learn how you work.

An office in action before the rise of generative AI.
An office in action before the rise of generative AI.

Kirn Vintage Stock/Corbis via Getty Images

  • A version of this story originally appeared in the AI Insider newsletter.
  • Sign up for Business Insider's weekly AI Insider newsletter here.

AI companies have already scraped much of the web. Now they're chasing something even more valuable: data that shows how humans actually work.

That's the focus of Business Insider's new series, The AI Data Grab. This week, we published three stories showing how the race for workplace data is accelerating.

One piece, from Charles Rollet, Tom Carter, and Stephen Council, examines the booming market for company records. AI firms are offering businesses six- and even seven-figure sums for anonymized Slack messages, emails, presentations, and internal documents.

The goal is to teach AI systems how people solve problems, collaborate, make decisions, and complete long, multi-step tasks. Those real-world workflows are becoming the fuel for the next generation of AI agents.

Another story, from Melia Robinson, explores how law firms are building AI systems around decades of legal knowledge, turning their own experience into a competitive advantage rather than relying solely on off-the-shelf AI models and tools.

A third piece, by Rya Jetha, reveals how AI companies pay people to record real-world work, such as cooking dinners and packing warehouses, to teach robots how humans perform everyday physical tasks.

Together, these stories point to a major shift in AI development. The first wave of generative AI was mostly about bigger models and faster chips. The next chapter is about machines understanding how work gets done, so AI can help us do it better and quicker.

Sign up for the AI Insider newsletter here. Reach out to me via email at abarr@businessinsider.com

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When AI and robots work together, Anthropic says these jobs are at risk. Should gardeners worry?

A gardener's gloved hands tend a wet flowerbed among tulips and other plants.
A gardener tends a flowerbed.

cbarnesphotography/Getty Images

  • Anthropic examined what might happen when AI and robots are combined.
  • That could put more hands-on jobs, including gardening, in the path of automation, Anthropic warned.
  • I'm skeptical that robots can handle the messy reality of pulling weeds.

Remember when Anthropic's AI jobs report suggested gardeners were among the safest workers because AI couldn't pull weeds or tell a rose from a dandelion? I joked about that in AI Insider earlier this year.

Well, Anthropic updated the research to freak us all out a bit more.

This time it asks a bigger question: What happens when you combine AI with robots? That change pushes many hands-on jobs much higher on the disruption scale. On paper, it makes sense. In practice, I'm skeptical.

For instance, anyone who's spent time working in a garden knows how hard it is to identify the right plant, kneel in awkward spots, and pull a weed out properly by the roots without damaging everything around it.

Robots are improving. But if you've ever watched one tackle a messy real-world task, you'll know there's a long road between a research chart and reality.

The chart below illustrates how adding robots could change job-task exposure across selected job categories. Cleaning & maintenance includes gardeners along with janitors and similar roles.

Qualitative estimates of added job-task exposure when robots are combined with AI models. Cleaning and maintenance: 5 dots. Food preparation and transportation: 4 each. Construction, farming, installation and repair: 3 each. Healthcare support: 2. Computer and math, business and finance, legal, management, arts and media: 1 each. More dots indicate a larger estimated increase. These are editorial estimates, not Anthropic-issued scores, percentages or job-loss forecasts.
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