HR-9339-119
Ordered to be Reported by the Yeas and Nays: 44 - 0.
Sponsored by Diana Harshbarger (R-TN)
What it does
This bill would require the Secretary of Energy, within 90 days of enactment, to conduct an assessment — in consultation with the Federal Energy Regulatory Commission (FERC) and the Electric Reliability Organization (ERO) — on how artificial intelligence and high-performance computing technologies could improve the capacity, reliability, and efficiency of the bulk-power system (the high-voltage transmission grid). The assessment would specifically examine AI's potential to speed up the studies required before new generators or large electricity users can connect to the grid, current adoption levels of these technologies, and any technical, cybersecurity, regulatory, or operational barriers to wider use. Within one year of enactment, the Secretary would submit a report to Congress with recommendations for overcoming those barriers and facilitating broader adoption.
Who benefits
Electric utilities and grid operators who would receive a federal roadmap for adopting AI tools. Renewable energy developers and other generators waiting in long interconnection queues, who could benefit if AI speeds up the required studies. Technology companies and AI vendors who could see expanded market opportunities if the report recommends broader adoption. Electricity consumers broadly, if grid efficiency improvements eventually reduce costs or improve reliability. Rural and underserved communities that experience more frequent outages and could benefit from a more reliable grid.
Who is hurt
Traditional grid engineering and consulting firms whose business model depends on manual interconnection studies may face competitive pressure if AI tools are widely adopted. Workers in those firms could see reduced demand for their services. Cybersecurity concerns identified in the assessment could lead to new compliance costs for utilities. No group faces direct, immediate harm from a study-and-report bill, though the recommendations, if acted upon, could create future winners and losers.
Supporters argue
Supporters argue that the U.S. interconnection queue has grown to over 2,600 gigawatts of pending projects — a backlog that takes years to process — and that AI-assisted modeling could dramatically accelerate these studies, unlocking new generation capacity faster. They contend that a targeted federal assessment is a low-cost, low-risk first step that gathers the evidence base needed for sound policy, ensuring any future action is grounded in data rather than speculation about what technologies can actually deliver.
Opponents argue
Opponents argue that the bill produces only a report with no binding requirements, meaning it may consume agency resources and time without producing actionable change if Congress does not follow through with legislation. They contend that FERC and DOE already have ongoing grid modernization initiatives and that duplicating those efforts with a new mandated study could divert staff attention from active rulemakings — such as FERC Order 2023 on interconnection reform — that are already addressing the same queue backlog problem through regulatory action.