As data center backlash grows, cities turn to AI to lower housing costs
The article highlights the growing national backlash against data center development due to environmental and utility concerns, exemplified by Monterey Park, California, enacting a permanent ban. Simultaneously, cities like Jacksonville, Florida, are exploring AI, which is powered by data centers, to streamline permitting and reduce housing costs. This creates a paradox as communities grapple with high housing costs and soaring utility bills caused by data centers.
The New York Post reports on a growing national "housing rebellion" against data center development, driven by concerns over water supplies, spiking electric bills, and other environmental impacts. This backlash is exemplified by Monterey Park, California, which recently became the first city to permanently ban data centers. Mayor Elizabeth Yang celebrated this "landslide win," noting resident opposition centered on the lack of long-term community benefits and serious risks. This comes as Monterey Park faces a state mandate to build over 5,000 new residential units by 2029, with high housing costs exacerbated by regulatory burdens.
Paradoxically, some cities are turning to AI, a technology heavily reliant on data centers, to alleviate housing crises by reducing regulatory red tape. Jacksonville, Florida, Mayor Donna Deegan announced an eight-point plan in August 2025 to streamline review and permitting processes, aiming to address a shortage of 50,000 affordable housing units. Point four of her strategy involves AI-driven tools for comment analysis and permitting efficiency, with partners like Microsoft and SwiftGov already reporting significant time savings. Jacksonville Chief Information Officer Wanyonyi Kendrick stated the goal is to make the process faster and more transparent.
However, the article points out the tension in this approach: while AI could cut housing costs by streamlining bureaucracy, the very data centers that power AI are simultaneously creating their own crises through resource consumption and utility strain, leaving communities to question whether AI truly solves affordability or simply redefines the problem.