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Chronicles

The story behind the story

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Salt Lake City-based Zanskar, which uses AI to find overlooked geothermal fields to boost US electricity supply, raised $115M, taking its total funding to $180M

The startup uses AI to find overlooked geothermal fields and says its discoveries can help sate the U.S.'s thirst for electricity

Wall Street Journal Benoît Morenne

Context & Ripple Effects

Zanskar’s financing arrives as U.S. nuclear, geothermal and storage developers have been described as finding a new lifeline in AI data-center demand after a difficult capital environment. Its focus on identifying overlooked fields places AI not only on the electricity-demand side of the story, but also in the search for new supply.

The company’s larger funding base matters because geothermal development depends on converting resource identification into financeable projects. Zanskar is therefore a test of whether AI-led exploration can improve the development pipeline for firm power.

First-order effects

  • Zanskar gains $115M of fresh capital, taking disclosed funding to $180M and expanding its capacity to pursue AI-identified geothermal opportunities.
  • Its investors are backing resource-discovery software as a route to additional U.S. electricity supply, rather than treating AI solely as a source of incremental power demand.

Second-order effects

  • Other geothermal developers and exploration-technology providers face a clearer incentive to demonstrate that their field-identification methods can produce investable project pipelines.
  • The raise complements AI applications elsewhere in the power system, including AI-based detection of underused grid capacity, broadening the market for software that finds constrained or overlooked energy assets.

Third-order effects

  • If AI meaningfully improves the conversion of geological data into viable geothermal projects, capital allocation in power infrastructure could increasingly favor software-enabled asset discovery alongside physical development.
  • The pattern points toward a tighter coupling between AI infrastructure growth and investment in firm, grid-relevant generation—though project execution, not discovery alone, will determine whether that capital becomes supply.

The trend: AI is becoming both a driver of electricity demand and a tool for locating and unlocking the energy infrastructure needed to serve it.