Guiding hyperscale data centers for fair AI futures

The article by Genave King Rogers Dean Akhilesh Bajaj outlines governance recommendations for how cities and states should negotiate with hyperscale data center operators to ensure fair, transparent and community-beneficial AI infrastructure development.

• Key recommendations include: independent impact analyses (grid, water, land use, environmental justice), early community engagement (including tribal nations), co-ownership of upside via AI dividends and CBAs, cost-reflective tariffs and demand-response participation, conditional tax incentives tied to ISO 50001/14001 and reporting, and reinvesting hyperscaler tax revenues into public-interest AI and workforce pipelines.
• Context and background: using Virginia’s ~13% share of global data center capacity as an example, the article notes pressures on electricity demand (40–100% projected growth), water use (billions of gallons possible with evaporative cooling), land and neighborhood impacts, and frames hyperscalers (Amazon Web Services, Microsoft Azure, Google Cloud, Meta, Tesla, OpenAI) as an early test of whether AI-driven economic gains become concentrated corporate power or support a broader social contract.