OpenAI’s Project Camellia Appeared in Georgia Power’s Planning Records Months Before Its $20 Billion Public Launch

Months before OpenAI publicly unveiled its $20 billion, 3.2 GW Project Camellia campus, Georgia Power had recorded a new 3,200 MW customer commitment and was evaluating an anonymized 3,210 MW project with a closely aligned development timeline, according to filings with the Georgia Public Service Commission (PSC). The records do not identify OpenAI by name, but together they offer a rare public glimpse into how one of the world’s largest AI campuses entered utility planning well before its official debut.

A review of PSC filings shows Georgia Power logging the 3,200 MW commitment in its Q1 2026 Large Load Economic Development Report, which covers activity through March 31, 2026. The report notes that new customer commitments of that size were added in April 2026 and would therefore appear in the second-quarter report. Three months later, OpenAI announced Project Camellia as a 3.2 GW campus. An accompanying planning attachment adds another clue: among dozens of anonymized projects is one listed in “Technical Review” with a stated load of 3,210 MW and an initial in-service date of Q2 2028, ramping to approximately 3.2 GW by 2031 — broadly matching OpenAI’s plan to energize the campus in phases beginning in 2028. While the timing and scale align, utility planning experts caution that anonymized records cannot definitively confirm the customer.

For utilities, regulators, and grid planners, the filings provide more than a project chronology. They reveal how AI megacampuses can begin influencing long-term load forecasts, transmission planning, and resource decisions months — and sometimes years — before the public knows they exist. “A 3.2 GW single-site load is extraordinary from a utility-planning standpoint,” said Neil Osnato, founder of Persistence Analytics Group. “At that scale, customer behavior becomes system behavior.”

Georgia Power’s January 2025 Integrated Resource Plan (IRP) helps explain why such early evaluations are necessary. The utility told regulators it maintains “active engagement and discussions with large load customers” and incorporates a “growing pipeline of potential and committed large load customers” into its long-term forecasts. In that IRP, Georgia Power raised its forecast to 8,200 MW of load growth through the winter of 2030–31, more than 2,200 MW above its 2023 IRP Update, and projected nearly 6,000 MW of new demand by the winter of 2028–29 while proposing new generation resources and strategic transmission investments. Whether Project Camellia directly contributed to that forecast is unclear from public records, but a single 3.2 GW campus illustrates the scale of a customer capable of materially shaping a utility’s long-term load outlook and resource planning.

After Project Camellia became public, Georgia Power announced that OpenAI will pay the full infrastructure and electric service costs, provide financial assurances designed to protect existing customers, and participate in a 25-year agreement that includes up to 1,000 MW of flexible demand response — allowing the company to reduce power delivered to the campus during periods of high system demand. Georgia Power described the arrangement as among the nation’s largest single-facility demand response programs.

The PSC filings also reveal how Georgia Power manages its large-load pipeline. The utility told regulators that executed electric service contracts carry greater weight in its forecasts than requests for service. It also disclosed that it removed one proposed data center after the developer became unresponsive, failed to secure an operator, and stopped marketing the site for data center use. As of March 31, Georgia Power reported 12.4 GW of committed large-load customers, 76.2 GW in its economic development pipeline, and 31 committed projects — most of them data centers.

The PSC documents stop short of identifying Project Camellia and do not establish when the project became commercially certain. They do, however, document something rarely visible outside utility planning: how a multi-gigawatt AI campus progresses from confidential engineering studies and load forecasts into the public record. OpenAI has emphasized transparency as a guiding principle for Project Camellia, pledging to share water-use data, release annual independent audits, and maintain open communication with the community. The PSC filings provide another layer of transparency by showing how projects of this scale begin shaping utility planning well before they are publicly announced.

By the time hyperscale AI campuses are announced, portions of the generation, transmission, and load planning required for them may already be underway. In Georgia, the filings suggest that AI infrastructure can enter utility planning long before it enters the public conversation.