Morgan Stanley: Electricity shortage is becoming the core bottleneck of AI infrastructure, and computing power expansion has entered the 'era of electricity constraints' According to BlockBeats, on June 15th, Morgan Stanley pointed out in its latest research that power shortages have risen from a supporting issue to a core limiting factor for AI infrastructure construction. The delivery cycle of power transformers has been significantly extended from 12-16 weeks before the epidemic to 128-144 weeks. The backlog of new energy grid connection in the United States has exceeded twice the existing installed capacity. At the same time, there is a shortage of 300000 electricians and 43% of data centers are in high water resource pressure areas, which are jointly suppressing the expansion speed of computing power supply. The expansion speed of the power system is much slower than the pace of data center construction, and the transmission network and key equipment supply chain cycle are significantly longer. The current average delivery cycle for power transformers has reached 128 weeks, and for generator step-up transformers it is about 144 weeks, compared to only 12-16 weeks before the pandemic. This means that even if AI data centers complete financing, site selection, and equipment procurement, they may not be able to start production on schedule due to delayed power access. In the grid connection stage, the backlog of new energy projects in the United States has exceeded twice the installed power capacity of the country, leading to a structural problem of "power generation completion ≠ available electricity". Electricity must be connected to the grid before it can be converted into usable supply for data centers, shifting the site selection logic from 'suitable for building computer rooms' to' areas where electricity can be quickly and stably connected '. At the same time, the financing boundary between AI infrastructure and energy systems is blurring, and some projects are adopting off grid or semi off grid solutions, including direct power supply paths such as gas turbines, energy storage, and fuel cells. AI companies are gradually shifting from relying on utility expansion to directly participating in power asset investment and locking in power supply capacity, promoting the integrated pricing of AI and energy assets in the capital market. Besides electricity, labor and resources also constitute constraints. The United States is expected to face a shortage of approximately 300000 electricians in the next decade, with over 20% of the workforce being aged 55 and above; Meanwhile, about 43% of data centers are located in areas with high water resource pressure, and cooling water and alternative solutions are becoming important limiting factors for new construction. In addition, multiple states have begun discussing or promoting restrictions and tightened approvals for data center construction, further increasing project uncertainty. Overall, electricity, grid connection, equipment, manpower, water resources, and policy approval are forming multiple overlaps and constraints, which may result in slower expansion of computing power than demand growth. The report suggests that this supply-demand mismatch will strengthen the scarcity of computing power, giving participants with stable and deliverable computing power stronger pricing power. The market is gradually shifting from "competition for computing power expansion" to "competition for available computing power control".