AI is big business, and so is development of the digital infrastructure needed to power it. Goldman Sachs estimates that the AI buildout will require $7.6 trillion of capex between 2026 and 2031 across compute, data centers, and power. Data centers alone will require $2.15 trillion of that spend.

There’s uncertainty, though, about whether data center developers will be able to handle the surge in demand for these facilities used to train and operate AI models.

Where’s the risk? There’s no shortage of challenges awaiting a data center project. Experts cited power generation, materials backlogs, and growing community opposition as some of the big ones.

To say the stakes are high in building out data center networks is putting it too lightly for experts like Mike Mathews, global digital infrastructure practice leader at Marsh, who told CFO Brew, “AI isn’t a new technology as much as it is a new utility,” like electricity. The digital infrastructure serves more than AI, he added. Everything from tap-to-pay technology to military drones relies on networks of data centers and fiber-optic lines.

Power “is the bottleneck in sort of getting these projects online,” according to Olivia Wang, research analyst at market intelligence firm Sightline Climate. Wang told us back in March that her firm observed median wait times of about five years to get sites powered, with that queue stretching as long as seven years for high-demand areas like the state of Virginia. Developers may also find themselves waiting a long time—as long as two years—for certain electrical equipment like transformers, she said.

Read more about the data center risks developers are grappling with.—AZ

In May 2025, Anthropic CEO Dario Amodei made headlines by predicting that AI would eliminate half of entry-level office jobs in the next one to five years.

While it would be folly to claim that any trend in the year since proves what will happen four years from now, for 2025 at least, a wave of AI-driven layoffs did not materialize, according to Gartner research.

Gartner studied nearly 1,400,000 jobs and found that only 21% of layoffs in the first half (H1) of 2025 were related in any way to AI. That percentage dropped to 13% in the second half of the year (H2).

What’s more, the bulk of those layoffs involved what Gartner terms “repositioning,” or making cuts to legacy business units to devote more resources to AI, VP Analyst Nate Suda said during a session at Gartner’s 2026 Finance Symposium/Xpo.

Gartner finds scant evidence of AI productivity gains causing layoffs.—CV

It’s a tough time for women in the workforce.

The gender pay gap has widened in recent years, women are leaving the workforce in record numbers, and systemic issues continue to inhibit career advancement.

There’s “a false narrative” of women’s progress in the workplace because many issues still persist, Stefanie O’Connell, author of The Ambition Penalty: How Corporate Culture Tells Women to Step Up―and Then Pushes Them Down, told HR Brew.

O’Connell sat down with HR Brew to talk about her book and the barriers that keep women from earning more and advancing their careers.

Why did you write this book?

I started the proposal in 2023, so certainly before the last presidential election…I thought I was going to be dismantling the narrative that just because a woman is the president doesn’t mean that gender inequality is any less prevalent…I thought I was going to be writing a book about how that was a fallacy.

Women have made progress but there’s more to be done, author tells HR Brew.—MC

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