Newswise — RICHLAND, Wash.—An innovative public-private partnership has yielded powerful new tools to help federal agencies rapidly synthesize complex data, historical documents and more into draft environmental impact statements. The benchmark project, called DraftNEPABench, paired the Department of Energy’s Pacific Northwest National Laboratory with corporate partner OpenAI. PNNL’s PermitAITM research team worked together with OpenAI over the past year to evaluate whether AI agents originally designed for coding tasks could help draft complex sections of environmental impact statements. These major reports are often required under the National Environmental Policy Act (NEPA) when agencies consider major federal projects such as siting of new data centers or electricity infrastructure. “Our evaluation showed that AI coding agents can generate structured and domain-specific draft sections for environmental impact statements with promising results,” said PNNL data scientist and DraftNEPABench research lead Anurag Acharya. “While the systems still require human oversight, the benchmark highlights both the potential and current limitations of these approaches.” The research team presented the peer-reviewed research at the first annual Association of Computing Machinery Conference on AI and Agentic Systems, held May 27–29, 2026, in San Jose, Calif. PermitAITM began as a pilot project sponsored by the DOE’s Office of Policy to...

OpenAI has partnered with the U.S. Department of Energy’s Pacific Northwest National Laboratory to evaluate whether coding agents can accelerate federal permitting work, using PNNL’s PermitAI program as the delivery vehicle. A benchmark built around federal drafting work The collaboration produced DraftNEPABench, a benchmark OpenAI said is designed around National Environmental Policy Act workflows such as drafting environmental impact statements. According to the announcement, PermitAI is funded by DOE’s Office of Policy and was built with 19 subject matter experts on the NEPA review process. OpenAI described the benchmark around document-heavy work where reviewers must read technical reports running hundreds of pages, cross-check information across multiple sources and produce structured drafts that meet specified legal and technical criteria. In its description of the testbed, PNNL said PermitAI is building on a large dataset of past environmental reviews and permitting documents and is testing applications that speed up discrete tasks inside permitting workflows. How the agents were tested The evaluation used “generalized coding agents” through Codex CLI, which OpenAI said can extract performance from reasoning models such as GPT-5 on research, technical analysis and report-writing tasks that involve a file system. OpenAI’s developer documentation describes Codex CLI as a terminal-based coding...

RICHLAND, Wash.—An innovative public-private partnership has yielded powerful new tools to help federal agencies rapidly synthesize complex data, historical documents and more into draft environmental impact statements. The benchmark project, called DraftNEPABench, paired the Department of Energy’s Pacific Northwest National Laboratory with corporate partner OpenAI. PNNL’s PermitAITM research team worked together with OpenAI over the past year to evaluate whether AI agents originally designed for coding tasks could help draft complex sections of environmental impact statements. These major reports are often required under the National Environmental Policy Act (NEPA) when agencies consider major federal projects such as siting of new data centers or electricity infrastructure. “Our evaluation showed that AI coding agents can generate structured and domain-specific draft sections for environmental impact statements with promising results,” said PNNL data scientist and DraftNEPABench research lead Anurag Acharya. “While the systems still require human oversight, the benchmark highlights both the potential and current limitations of these approaches.” The research team presented the peer-reviewed research at the first annual Association of Computing Machinery Conference on AI and Agentic Systems, held May 27–29, 2026, in San Jose, Calif. PermitAITM began as a pilot project sponsored by the DOE’s Office of Policy to centralize NEPA...

Building the infrastructure we need to unleash American energy requires accelerating permitting. One particularly promising effort to make Federal permitting faster and better leverages artificial int...

The DOE’s PNNL has developed PermitAI to create a unified National Environmental Policy Act database called NEPA Text Corpus 2.0.

Newswise — RICHLAND, Wash.—For the first time in the over 50-year history of the National Environmental Policy Act, federal regulators now have vital information at their fingertips in a single database, thanks to an ambitious project called PermitAI, developed by...