AI, Energy, and the Environment: Use, Policy, and Tradeoffs

The rapid growth of AI is creating new economic development opportunities and driving a wave of investment in data centers, computing infrastructure, and energy systems. Across the country, state and local governments are making decisions about data center development, electricity demand, water use, transmission infrastructure, land use, and environmental impacts while balancing goals for economic growth, affordability, reliability, and sustainability.

At the same time, public agencies, utilities, and environmental organizations are beginning to use AI to improve forecasting, environmental monitoring, resilience, permitting, resource management, and infrastructure planning.

For public officials, the challenge is not simply whether to support or oppose AI-related development. It is how to balance competing priorities. How can governments capture economic benefits while protecting communities and natural resources? How should agencies respond to growing energy demand and infrastructure needs? Where can AI help improve energy and environmental outcomes, and where might it create new costs, risks, or unintended consequences?

Designed for state and local government staff, utility professionals, regulators, planners, sustainability and resilience officials, economic development staff, environmental agency staff, and public-sector leaders, the series provides practical frameworks for evaluating tradeoffs, asking better questions, and making informed decisions in a rapidly changing landscape.

By the end of this series, participants will be able to:

• Understand the energy and environmental implications of AI-related infrastructure growth.
• Identify where governments, utilities, and environmental organizations are using AI to improve planning, operations, resilience, and environmental management.
• Evaluate policy, regulatory, planning, and investment approaches for managing AI-related energy and environmental challenges.
• Assess tradeoffs among economic development, affordability, reliability, sustainability, and public accountability.
• Ask informed questions about AI-related infrastructure investments, environmental impacts, and public-sector uses of AI.