Hyperscale data centers built to train and run artificial intelligence (AI) systems are driving one of the fastest sustained increases in US electricity demand in decades. The International Energy Agency (IEA) projects global data center electricity consumption to roughly double by 2030, with AI-optimized facilities driving most of that growth and data centers accounting for nearly half of US electricity demand growth over the same period (IEA, Energy and AI, 2025). Whether this demand growth is already raising the prices households and businesses pay is contested. Recent causal analyses reach opposite conclusions depending on geographic scope and time horizon, with one finding a modest local price increase concentrated in industrial rates (Rana et al., 2026) and another finding a modest decline in the national average retail rate (Watten et al., 2026). Beyond price, a parallel literature has begun documenting environmental and health concerns tied to facility siting, including air pollution from fossil-fuel generation and backup diesel generators, water use for cooling, and noise. Virginia's dense data center corridor has served as an early case study of these concerns (Gour, 2026), and facility-level modeling shows that how a campus sources its power materially shifts who bears the resulting air-quality burden (Gujral & Dominici, 2026). Here we ask four research questions. (1) Do hyperscale data centers raise the retail electricity prices paid by industrial and residential customers of the utilities that host them? (2) Does the size of a utility's data center exposure, beyond its presence, predict a larger price effect? (3) Does the type of developer, large hyperscalers building their own campuses versus other developers, change the size of any effect? (4) Does a utility's price respond to data center capacity sited in neighboring utility territories, not just its own? A companion analysis asks a fifth, related question at the county level. (5) Do host counties show any measurable local economic benefit, such as higher employment or income, that might offset these costs?