UBS models $4.1T in AI infrastructure spending by 2028 - it assumes the power just shows up

Everyone talks about chip supply as the bottleneck on AI buildout, but power interconnection is turning into the harder constraint in several major markets, and it works nothing like a chip shortage. A chip shortage is a supply problem: fabs run flat out, backlogs clear eventually, prices come down. Grid interconnection is a queue problem: a new data center has to get in line behind every other proposed generation and load project in that region, and studies for that queue routinely take years, not quarters. You can't buy your way to the front by paying more, and you can't build your way out of it by ordering more GPUs. Three things happened just this month that show the queue problem getting worse, not better. The Tennessee Valley Authority created a rate class specifically for AI data centers, an admission that normal industrial rates and normal queue treatment don't fit this load anymore. Denmark's grid operator started putting new data center interconnection requests behind other categories of demand entirely, rather than processing them in the order they arrived. And PJM's board overruled its own stakeholder vote on curtailment rules, which tells you the fight over who gets priority access to constrained transmission capacity is now happening at the top of the largest grid operator in the US. None of this shows up in a capex forecast. $4.1 trillion assumes the megawatts show up when the money does. In a growing number of regions that assumption is the thing to watch, not the chip supply chain. Curious what people closer to the utility/regulatory side are seeing: is interconnection actually the binding constraint now, or is that overstated relative to chips and cooling?