Journal archive
Deep dives into AI applications, environmental planning methods, and regulatory compliance strategy for CEQA and NEPA teams.
Generative AI is now embedded in real environmental review work: summarizing baseline studies, drafting significance narratives, preparing response matrices, and generating public-facing materials. Th...
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Most NEPA research workflows are too slow for real-world decision cycles. Teams spend hours digging through precedent records, reconciling differences across agencies, and extracting patterns under de...
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Welcome to the CEQA.ai Blog! We're excited to launch this platform dedicated to exploring the fascinating intersection of artificial intelligence and environmental planning. As environmental regulatio...
Read article →Mitigation Monitoring and Reporting Programs (MMRPs) often live in spreadsheets that few people see. Field inspectors juggle clipboards, project managers chase updates, and executives are left guessin...
Read article →Automation is reshaping the environmental review workforce. Rather than replacing planners, AI expands capacity and changes how expertise is applied. Agencies that intentionally design hybrid teams ga...
Read article →Geospatial context is central to every environmental review. Planners have long relied on GIS analysts to translate layers into actionable insights. Today, language models can interpret spatial data, ...
Read article →Public comment periods can generate thousands of letters, emails, and hearing transcripts. Sorting themes, drafting responses, and coordinating approvals can overwhelm even experienced teams. A commen...
Read article →Courts now expect agencies to explain how they use automation during CEQA and NEPA reviews. A single undocumented prompt or unverifiable citation can undermine years of analysis. By embedding legal gu...
Read article →Drafting a CEQA Initial Study or Environmental Impact Report is a marathon of synthesis, formatting, and citation management. Language models and document automation platforms can shorten that maratho...
Read article →Baseline data is the backbone of every CEQA analysis, yet too often the datasets that planners rely on are fragmented, stale, or undocumented. Modern language models can change that reality. By pairin...
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