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Permit hurdles push up costs for AI data centers; Oracle pivoted from gas turbines to costlier fuel cells for its Project Jupiter in NM, costing billions more

Building an AI supercampus increasingly means paying more than you bargained for.  Oracle's attempt to salvage a proposed $165 billion project …

The Information Ann Davis Vaughan

Context & Ripple Effects

Oracle’s AI infrastructure plans were already carrying unusually large construction and financing commitments: related coverage describes gas-powered capacity in Texas, chip purchases for an OpenAI-linked site, and difficulty distributing loans tied to Oracle-leased data centers.

The New Mexico permitting issue adds a non-compute constraint to that buildout. It follows reported financing disputes that halted a Texas expansion, making the cost and deliverability of new power a central part of Oracle’s infrastructure execution risk.

First-order effects

  • Oracle must redesign Project Jupiter’s on-site power approach around higher-cost fuel cells, adding billions to the proposed project’s cost base and complicating its economics.
  • Permitting agencies and power-equipment providers become immediate gatekeepers for the project’s schedule and viable generation mix.

Second-order effects

  • Higher project costs and more uncertain delivery increase pressure on Oracle’s financing structure, after lenders had already struggled to distribute risk on data-center loans tied to the company.
  • Other developers pursuing large AI campuses may place greater value on sites with clearer power and permitting paths, while fuel-cell and other approved on-site-power options gain strategic importance.

Third-order effects

  • If permit constraints repeatedly force redesigns, AI data-center competition will be shaped less by announced campus scale than by the ability to secure financeable, permitted power.
  • The pattern would make AI infrastructure increasingly resemble utility-scale development: long lead times, local approvals, and power configuration become durable limits on capacity expansion.

The trend: AI infrastructure is shifting from a chip-procurement race toward a power, permitting, and project-finance execution race.