Reporting archive
Evidence on AI and work
Reporting archive

Amazon just turned “AI strategy” from slideware into headcount, and every CFO took notes.

At Davos, the IMF reframed AI as a macro risk—erasing entry-level on‑ramps, minting augmentation premiums, and forcing policy to build guardrails before wage ladders collapse.

The layoff ledger now has an “AI” column—and the numbers, sectors, and CEO quotes show it’s more than a narrative device.

At Davos, Jamie Dimon quietly broke ranks, urging regulators to slow AI-driven layoffs—pricing civil unrest as the real risk and offering corporate buy-in to guardrails.

In Davos, AI’s top builders admitted they’re staffing without starters—compressing teams, erasing apprenticeships, and risking a brittle future unless policy buys real experience.

Ed Zitron’s Guardian interview flips the AI debate from capability to intent, arguing the boom is a spreadsheet-driven push to shrink headcount despite shaky models and missing ROI.

The layoffs aren’t proof AI works—they’re proof a valuation story needs bodies, and there’s a smarter way to stop becoming the accountability sink.

The AI boom has turned white-collar jobs into collateral, and whether models sprint or stall, the entry level gets thinner.

BlackRock’s memo flips the AI narrative: the real bottleneck isn’t GPUs, it’s the shrinking supply of certified tradespeople to wire, cool, and legally staff the data centers.

London’s mayor just turned AI rhetoric into policy, daring the City to rebuild the first rung of white-collar work before it disappears.