The Economist counted about a million American jobs created by AI since 2023, and that count is solid. But look at what those jobs actually are: electricians, HVAC techs, equipment makers, data-centre technicians. People building and running the buildings, not people using the software. Only about one per cent of professional jobs are AI jobs. That matters, because a number like this tracks how much money companies are spending, not how good the technology is. If the models stopped improving tomorrow, hiring would keep going for a year because the contracts are already signed. If the models kept improving but three big spenders cut their budgets, the hiring would stop cold. So the figure is a spending indicator, not proof the technology works. And the people using it to say there’s no problem are missing that the office jobs going quiet and the construction jobs booming are two different labour markets with two different sets of people in them.

Three stories landed within hours of each other this week, and together they say more about the AI buildout than any single earnings call. BlackRock is leading a debt sale exceeding $12 billion to finance Meta’s new data center in El Paso, Texas. In a related move, Meta has signed a lease for a separate BlackRock-backed data center project in Pennsylvania. Meanwhile, on the supply side, TSMC is preparing to raise prices on both advanced and mature process nodes by as much as 10% in 2027, with an additional 10-15% premium layered on top for customers who exceed their original order forecasts. And Microsoft has signed a multibillion-dollar agreement with Mistral to build European data centers while folding Mistral’s models into Foundry, Copilot Studio, and Azure Local.

The May–June 2026 technology conference window is unusually dense, reflecting the sector’s attempt to process several simultaneous inflection points: the industrial deployment of AI beyond the pilot phase, the semiconductor supply chain’s geographic rebalancing, and the maturing of open hardware architectures from academic interest into commercial infrastructure. For investors and operators tracking these transitions, the conference calendar functions less as a social calendar and more as a forward indicator — announcement timing, speaker cancellations, and floor traffic are often more informative than the formal presentations.

The cloud versus on-premises debate has settled into a more nuanced position than its early framing suggested. The argument that all workloads should move to cloud and that on-premises infrastructure would become obsolete was oversimplified. The organizations that moved all workloads to cloud and discovered that certain workload categories are more expensive to run in cloud than on-premises have been quietly repatriating those workloads for several years.

The current reality is a hybrid infrastructure landscape where the economic decision about where to run a workload depends on its specific characteristics — compute intensity, data volume, access patterns, regulatory requirements, and predictability — rather than on a blanket preference for either delivery model. Server hardware investment in this context requires the same rigor as any capital investment: a specific business case for the specific workloads that the hardware will run.