Summary of The Cost of Not Building Data Centers by Vittorio Quaglione (Project Syndicate, 27 July 2026)
Core issue
Amid the global AI infrastructure boom, strong local and political pushback in the US has led to at least $85 billion worth of data center projects being cancelled over the past three years. In July 2026, New York became the first US state to impose a statewide moratorium on new large-scale data centers, with other states and federal policymakers now weighing similar restrictions. While concerns over energy use, water consumption, grid strain, and community impacts are valid, the author argues that opponents and markets alike overlook the far larger, long-term cost of failing to build this critical capacity.
Key arguments
- Markets are good at calculating the direct costs of construction and operation, but poor at pricing the opportunity and strategic costs of inaction—especially for investments that deliver broad economic and national benefits beyond private returns.
- As former White House official Josh Zoffer notes, data centers are a “crucial test of US industrial resolve”: building future strategic strength almost always requires short-term trade-offs and acceptance of some costs today.
- Historical parallels: Past US delays and underinvestment in critical sectors like electrification and rare-earth processing created lasting competitive disadvantages, lost economic leadership, and forced reliance on foreign supply chains—risks that now apply equally to AI infrastructure.
Recommended approach
The author does not call for unlimited, unregulated construction. Instead, he urges policymakers to replace blanket bans or moratoriums with thoughtful planning: set clear environmental and community standards, upgrade grid capacity, streamline permitting, and ensure developers fairly fund local impacts and infrastructure needs. Blocking development entirely risks ceding technological leadership, economic growth, and industrial competitiveness to other nations—costs that will prove far harder to reverse than short-term local disruptions.

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