Using AI to Streamline 404 Permits and NEPA Processes

The federal environmental permitting process can often be bureaucratic and frustrating requiring new studies, biological opinions (BO), and jurisdictional determinations (JD) for sites that have previously been studied. Although well-meaning, these processes can lead to significant delays, even for critical projects.

In response, the Trump Administration issued a Presidential Memoranda to accelerate federal environmental permitting by incorporating technology, including artificial intelligence (AI), into the process. This directive is particularly impactful for two major regulatory processes: Section 404 permits and the National Environmental Policy Act (NEPA) reviews.

Streamlining Section 404 Permits with AI

The Section 404 permitting process, administered by the U.S. Army Corps of Engineers (USACE) requires applicants to attain federal approval before discharging dredged or fill material into “waters of the United States” (WOTUS), including wetlands, streams, and rivers. (The debate surrounding the definition of WOTUS is beyond the scope of this blog.) This law aims to safeguard water quality and aquatic ecosystems from potential harm while balancing needed development activities. However, the approval process can be lengthy and requires detailed review from federal, state, and tribal agencies. AI can significantly enhance this process by automating data analysis and improving the accuracy and speed of environmental assessments. As an example, machine learning algorithms can be used to process satellite imagery, water quality reports, biological opinions, and environmental impact statements to assess the potential impact of the proposed projects on the aquatic ecosystems.

By automating routine tasks such as data collection and comparison, AI enables agencies to identify potential environmental risks more quickly, reducing delays in the permitting process. This efficiency allows for faster decisions while ensuring that projects still meet environmental protection standards.

Enhancing NEPA Reviews with AI

The NEPA review process requires federal agencies to evaluate the environmental impacts of proposed projects. This often involves the creation of Environmental Impact Statements (EIS) which can be extremely detailed and lengthy documents. The review process typically includes public comments, expert consultations, and data analysis, all of which can slow down the timeline for approval.

AI offers several ways to expedite the NEPA process. Natural language processing (NLP) tools can be used to analyze large volumes of documents, identify key environmental concerns, and compare proposed projects with historical data from similar projects and/or projects in the same watershed. AI can also assist in organizing and categorizing public comments, helping agencies address stakeholder concerns more effectively. By automating these tasks, agencies can focus on more complex aspects of the review and accelerate the overall process.

The Path Forward

The Trump Administration’s memoranda on permitting technology signals a shift toward more efficient, technology-driven approaches to environmental permitting. By integrating AI into the Section 404 and NEPA processes, delays can be reduced while still maintaining strong environmental protections. Right now, applicants can use off the shelf AI tools to assist in developing their applications. Furthermore, existing BOs and JDs can be fed into AI tools and then compared with an applicant’s site data. Although challenges remain such as ensuring data quality and standardizing processes across agencies, the potential for AI to streamline these critical reviews is undeniable.

Col. (Ret) Edward R. Fleming

Executive Vice President

A member of the Dawson team since 2022, Col. (Ret) Edward R. Fleming spent 25 years in the US Army and commanded the Corps’ New Orleans and Charleston Districts.