Category: 3. Business

The US labor market picked up in March as employers showed signs of resilience amid the US-Israel war in Iran.

After an extraordinary contraction in February, employers added 178,000 jobs last month, ahead of economists’ expectations of about 70,000.

chart showing monthly change in US jobs

The unemployment rate fell to 4.3%, according to data from the US Bureau of Labor Statistics. In February, the economy lost 133,000 jobs, according to revised figures. Job figures for January were revised up, from 126,000 to 160,000. With revisions, total employment in January and February is 7,000 lower than previously reported. .

Previous data painted a mixed picture of the US labor market, which economists say has been in a static “low-fire, low-hire” state, where both layoffs and new hires are down.

Outplacement firm Challenger, Gray & Christmas found that employers announced 217,362 job cuts in the first quarter of 2026 – the lowest total for that period since 2022. But hiring in February slowed to a six-year low, according to data released earlier this week, with dips seen in construction and leisure and hospitality.

The so-called “quits rate” fell to 1.9%, the lowest since 2020, suggesting that uncertainty in the labor market has prompted more workers to stay put at their jobs.

The trend follows sluggish overall growth in the US jobs market since last year. In 2025, just 116,000 jobs were added to the economy for the entire year – around the same number that was added per month in previous years.

The slowdown points to caution among employers, particularly as consumer inflation experienced whiplash over the last year. US inflation dipped down to 2.3% in April 2025 before jumping to 3% in September. Price increases have been steady at 2.4% since the start of this year, though the US-Israel war with Iran is expected to drive inflation higher if the fallout continues to grow. Last month, US average gas prices broke through $4 a gallon, and the squeeze on oil and gas is expected to trickle into other industries.

The oil price shock is reminiscent of higher prices that were seen in 2022, after Russia invaded Ukraine. US average gas prices reached $5 a gallon at the time while inflation reached a generational high of 9%. Experts say that every $10 increase in the price of a barrel of oil can lead to 0.2% climb in inflation.

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Data center construction is expanding rapidly across the U.S., driven by surging artificial intelligence (AI) adoption and the resulting need for computing power. Investment is accelerating alongside construction, with annual data center project spending reaching $14 billion in July 2025 — a 100% increase over the prior year. 

Comprehensive tax and financial forecasting helps prevent overspending and leaving potential savings on the table, making it essential for projects with such high levels of investment. Depreciation planning plays a central role in those efforts because data centers contain numerous specialized and redundant systems, all of which depreciate at different rates. Neglecting to account for those differences can cause companies to miss strategic tax planning opportunities and could increase their overall tax burdens. 

This installment of BDO’s Data Center Dangers series explores how facility owners can leverage cost segregation analyses to help conduct depreciation planning, reduce their total tax liability, and capture all available tax savings.

Understanding Depreciation Schedules 

At a basic level, depreciation is the act of expensing the cost of an asset over its usable life. Under federal tax rules, nonresidential real property, such as commercial property, is expensed over 39 years, but some individual building elements can be depreciated using five-, seven-, or 15-year recovery periods. Assigning the appropriate depreciation methods and recovery periods to property is crucial because depreciation can significantly affect after-tax costs and long-term project economics. 

Data centers combine real estate, industrial infrastructure, and advanced technology systems under one roof. Because those elements depreciate at different rates, depreciation planning can be more complex for data centers than other commercial projects such as office building or retail spaces. 

Recent tax law changes add another layer of complexity to depreciation planning. The One Big Beautiful Bill Act (OBBBA), passed in 2025, restored 100% bonus depreciation, which had been slated to sunset. Bonus depreciation allows companies to immediately deduct 100% of the purchase price of eligible assets, so its reinstatement opens the door to substantial savings for data center owners that set themselves up to claim them. 

Tangible property, computer software, and other assets with a class life of no more than 20 years — categories that encompass many of a data center’s systems — are eligible for bonus depreciation. Common data center assets that fall under this umbrella include specialized components (for instance, electrical and HVAC systems), as well as office equipment, such as computers and AI chips. 

Bonus depreciation eligibility also extends beyond new construction. Many data center projects involve renovations to existing structures, which can be treated as 15-year, bonus eligible qualified improvement property (QIP). 

However, data center owners must also consider state-level variations on bonus depreciation. California, for instance, does not conform to federal bonus depreciation rules. Further, states must determine whether they will decouple from the OBBBA, with several states having already decoupled in whole or part. Those decisions will affect bonus depreciation options for data centers. 

To take advantage of depreciation opportunities and maintain compliance with state tax filing standards, data center owners need to know how much money they are spending on each depreciable asset. Conducting a cost segregation analysis allows companies to itemize individual project expenses and gain full visibility into their depreciation options. 

What is Qualified Improvement Property (QIP)?

Some building or structural upgrades, known as QIP, are QIP, are depreciable over 15 years, making them eligible for 100% bonus depreciation. But QIP comes with its own nuances that businesses must understand. Elevators, building expansions, or any exterior improvements do not count as QIP, while electrical systems, flooring, and HVAC systems inside a building — all common to data center projects — might qualify. 

State conformity related to QIP also varies. For example, consistent consistent with its decoupling from federal bonus depreciation rules, California also does not recognize QIP as 15-year property. As such, data centers in California risk losing both federal QIP treatment and the ability to properly classify five-year property for state purposes unless they conduct a cost segregation analysis. Doing so will allow them to break out costs in a format that is acceptable to federal and state taxing authorities, allowing for greater tax planning flexibility. 

Cost Segregation Analysis 

Cost segregation is a tax planning technique that can increase cash flow by accelerating the federal tax depreciation of construction-related assets over five-, seven-, and 15-years instead of 27.5 or 39 years. By breaking out individual costs rather than grouping them all together, data center owners can make more strategic tax planning decisions regarding when and how to depreciate an asset. Without a cost segregation study, property with a tax depreciable recovery period of less than than 20 years might be classified alongside longer-lived assets, eliminating eligibility for bonus depreciation and forfeiting potential tax savings. 

A final cost segregation study cannot occur until a project is completed, but companies should start preliminary analyses at the outset. Breaking out costs early in the process can reduce the need for retroactive work and allow for more precise spend tracking than a price tag that does not include per-item details. Ideally, owners should work with their general contractors — who will have the highest level of line-by-line cost visibility — to break out costs within initial construction contracts. 

From there, owners can elect into or out of bonus depreciation by class life, depending on their business and tax planning priorities. They can also use the cost segregation to properly classify spending categories for other federal and state tax purposes, as well as general financial planning and recordkeeping. For example, a company might not elect to take 100% bonus depreciation for every piece of data center property. Instead, it might choose to forgo bonus depreciation for specific asset classes to better align with business priorities such as cash flow or anticipated future income. Making such strategic decisions is not possible without a robust cost segregation analysis that assigns accurate dollar values to each asset category. 

Standing before a friendly crowd in March, Elon Musk laid out his plan for the future of his companies, and it was literally out of this world.

Musk announced that his space-launch company, SpaceX, which had recently merged with his artificial intelligence company, xAI, would put data centers into orbit around the Earth.

It all comes down to electricity, he explained. “You’re power constrained on Earth,” he said. “Space has the advantage that it’s always sunny.”

Musk envisions legions of data-crunching satellites spinning around the planet, powering the AI revolution from above. It’s the perfect pitch for taking SpaceX public. This week, Bloomberg reported that the company had filed documents confidentially to the Securities and Exchange Commission with the goal of going public this summer.

Musk also claims it makes financial sense. “I actually think that the cost of deploying AI in space will drop below the cost of terrestrial AI much sooner than most people expect,” he said. “I think it may be only two or three years.”

Others are skeptical. Musk’s timeline is “an optimistic interpretation,” according to Brandon Lucia, a professor of electrical and computer engineering at Carnegie Mellon University who specializes in putting computers on satellites. The napkin math looks appealing, and power is free up there after all — but it turns out there are a lot of obstacles to building a data center among the stars.

A global power problem

Here on Earth, the problem is glaring: AI is gobbling up electricity around the globe. Global data-center power consumption is expected to roughly double to nearly 1,000 terawatt-hours by the end of the decade, according to an estimate by the International Energy Agency.

To fill the gap, some companies are building dedicated gas turbines, while others are investing in nuclear technology. It’s not enough, according to Philip Johnston, CEO and co-founder of Starcloud, which is seeking to build orbital data centers.

“We’re very quickly running up on constraints on where you can build new energy projects terrestrially,” Johnston said. “Within six months, they’ll just be leaving chips in warehouses because they don’t have power for turning them on.”

Starcloud launched its first spacecraft last fall with an Nvidia H100 chip on board. The company demonstrated the ability to run a version of Google’s Gemini AI from space, and it plans to launch a second spacecraft in October. “That one has 100 times the power generation of the first one,” Johnston said, though it’s still expected to generate only around 8 kilowatts of power.

Google is also pursuing the idea of building data centers in space through a project known as Suncatcher. It envisions an 81-satellite cluster that it plans to build in partnership with the satellite-imagery company Planet. Two prototype satellites will launch in early 2027, according to the companies.

“Orbital data centers are an idea whose time has come,” Will Marshall, Planet’s CEO, wrote to NPR in an email. “When exactly it will be more cost efficient than terrestrial ones is debatable but now is the time to be working on this.”

Everything must get bigger

To go from a handful of prototype satellites to something useful is not so easy. For one thing, the power requirements of the microchips used for artificial intelligence are enormous.

To get a sense of just how much power is needed, consider the largest power-producing facility in space right now: the International Space Station (ISS).

The solar panels of the ISS are around half the size of a football field and produce around 100 kilowatts of average power, according to Olivier de Weck, a professor of astronautics at the Massachusetts Institute of Technology. “It’s basically the amount of power that a single big car engine produces.”

To replicate a 100-megawatt data center in space would require a facility that’s 500 to 1,000 times, depending on the orbit.

“Is that feasible? Yeah, I think it’s feasible, but not next year and certainly not in three years,” he said.

And power is not the only requirement; the satellites also have to provide cooling to the microchips. While it’s true that space is cold, it’s also a vacuum. This means that when a satellite gets hot, there’s no easy way to get rid of that heat — it just builds up.

“All of that heat that the computer generates has to be dispelled,” said Rebekah Reed, a former NASA official now at Harvard University’s Belfer Center for Science and International Affairs.

The best solution is radiators, which move liquids out to giant panels where the heat can be dissipated. So in addition to solar panels, an AI satellite would need another set of large radiators.

“When you put those massive radiators together with massive solar arrays that are required in order to power and cool, you’re actually talking about really large satellites, or very, very large satellite constellations,” Reed said.

An alternative is to build smaller satellites and fly them in preset formations called constellations. Such constellations allow the heat and power problems to be distributed, but to work, the satellites would need to send huge amounts of data back and forth. That likely means using lasers to beam data between satellites. But even moving at the speed of light, the time it takes to get data from one satellite to another is long enough to slow down computing.

Google’s Project Suncatcher proposes flying groupings of satellites in extremely tight clusters to reduce that latency. Musk, meanwhile, has proposed launching upward of a million satellites and placing them in orbit around Earth’s poles. He recently unveiled the first generation “AI Sat Mini” spacecraft — with solar arrays spanning roughly 180 meters (about 600 feet) — during his presentation.

Launching all that into space would cost money — lots of money. At the moment, it can cost around $1,000 per kilogram to launch a satellite into orbit. Google believes that cost must drop by at least a factor of five to $200 per kilogram before data centers in space will begin to make sense.

Musk thinks he can do it with his new Starship rocket, which is still in development. Starcloud’s Johnston says Starship is central to more than just SpaceX’s vision. He told investors: “If you don’t think Starship’s going to work, don’t invest in us — that’s totally fine.”

Upgrading the server

Even if a company could get a data center into space, running it would involve a lot more than just moving microchips into orbit.

Data centers on Earth are not just static buildings full of chips humming away, says Raul Martynek, the CEO of DataBank, a company that maintains 75 data centers, primarily located in the United States. They require constant maintenance and upgrades, all of which is done by workers.

Take DataBank’s IAD1 data center in Ashburn, Virginia. The facility is 144,000 square feet filled with rows and rows of black computer cabinets, which are filled with microprocessors. It’s fairly run-of-the-mill, as these facilities go, but it still consumes around 13 megawatts of power at any given moment (that’s 130 times more than the International Space Station).

“We have vendors here every single day,” says James Mathes, who manages IAD1.

Workers are constantly in and out of these data centers, installing new servers, upgrading microchips and fixing things. And to stay competitive, space data centers would need to do much of the same.

Some of that could be done through software, and Musk points out that chips can be rigorously tested on the ground before they’re sent aloft. But the fact remains that the companies that rent data centers often want to access them physically for one reason or another.

Martynek, who has spent decades in telecom, says he’s not worried about space data centers taking business from his company.

“It seems like there’s a lot of ifs and a lot of advancements that would have to occur, and I find it kind of hard to believe that all that could happen in two or three years,” he said. “No one in data center land is losing any sleep.”