Project Start: June 2026
As with other rapidly changing technologies and fields, the evolving development and advancement of AI and ML tools and applications make it difficult for environmental practitioners to stay current with the critical information about this field. Understanding opportunities and risks for applying AI and ML in the environmental field will continue to improve as more scientific studies, use cases, and guidelines are completed and published.
What are the barriers to overcome?
While AI/ML offers great potential, its adoption in the environmental field is not without challenges. A number of barriers prevent government and private organizations from effectively implementing these technologies including:
- Lack of Knowledge
- Regulatory and Policy Uncertainty
- Cost and Access
- Data Quality and Trust
How will we overcome the barriers?
ITRC will work with the AI/ML Team members to develop a product for publication at the end of 2027 to serve as a “snapshot in time” to improve education and understanding around the opportunities for AI and ML to efficiently and responsibility manage and analyze environmental data. This will likely include a summary of tasks where AI/ML application may increase efficiencies but balance quality control. Any references, links, or data cited likely will become outdated over time.
ITRC acknowledges the challenges of environmental impacts of infrastructure to support the growth of AI. This issue falls outside the scope of this product.
Note: The project team proposal outlines the initial scope and intended deliverables. As the team begins its work and collaboration, the final project scope, deliverables, and content may be adjusted to best meet the needs of ITRC members and the environmental community.
Team Leaders
Thomas Wallace
TWallace@mdeq.ms.gov
James Jennings
James.M.Jennings@illinois.gov
Program Advisor
Sarah Bennett
sbennett@skeo.com