The premier brownfield redevelopment conference in Virginia is hosted by the Virginia Department of Environmental Quality (DEQ) and the City of Staunton.
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Redeveloping brownfield sites is often a slow and costly undertaking—one that requires numerous steps and the coordinated expertise of many professionals. This presentation explores how artificial intelligence (AI) is transforming that process by improving and accelerating environmental studies and remedial actions. AI-driven tools—including machine‑learning models, geospatial analytics, and natural language processing—are enabling environmental scientists and engineers to evaluate data more efficiently, reduce uncertainty, and streamline decision‑making. These technologies are now embedded in a wide range of technical tasks, such as data collection and review, change detection, predictive modeling, report automation, and QA/QC activities. As a result, AI‑enhanced workflows are increasing efficiency, optimizing limited budgetary and staffing resources, and ultimately shortening project timelines for brownfield redevelopment.
