An op-ed from Google’s chief economist and Diane Coyle reframes AI as a task editor—and dares Washington to fund paid, portable, verifiable learning to make the edits stick.

Dylan Field just flipped AI from a cost cutter to a demand engine—and says that means more hires, not fewer.

Newsom’s veto didn’t kill bossware—it killed the speed limit, ushering in a year of fast, opaque AI in HR.

Amazon is recoding HR into a platform, signaling AI-driven cuts of up to 15% in PXT and a shift from people doing tasks to systems running them.

Labor just rewired workplace AI by dragging decisions into design and procurement, putting workers’ hands on the override and vendors on the hook.

Goldman used an earnings beat to roll out an AI-first operating plan that trims transaction roles, rewires workflows, and hires in deployment waves with risk and governance baked in.

Salesforce isn’t automating San Francisco; it’s trying to make the city the operating system for agents—and the jobs that run them.

India’s AI roadmap swaps layoff angst for agency, aiming to convert routine IT/CX roles into system-level AI work by pairing a national talent mission with an open compute commons.

If Gartner’s right, the next big AI constraint isn’t compute—it’s proving a qualified human actually took the risk.

When Google tells boards that AI widens service before it trims staff, the budget math—and the layoff timeline—shifts.