New reporting and analysis warn that universities’ ability to build and operate AI-capable computing infrastructure is increasingly defining institutional competitiveness. The argument centers on how data center capacity affects researcher recruitment, graduate admissions, sponsored research activity, and indirect cost recovery. The reporting highlights infrastructure constraints: AI racks can draw far more power than traditional academic server layouts, and campuses may need liquid cooling and facility upgrades that take time to plan and build. Institutions making investment decisions now may determine whether they can attract the next generation of researchers. Separately, coverage of data center opposition describes a broadening political backlash. Data Center Watch reports that opposition groups have surged in 49 states and that dozens of large projects were delayed or canceled in early 2026. Taken together, the two developments create a strategic risk for higher education: campuses seeking AI compute must manage both capital intensity and local permitting and community-relations challenges.