According to an article of Latham & Watkins LLP, the intersection of artificial intelligence (AI) and Environmental, Social, and Governance (ESG) concerns is becoming increasingly significant for companies in the United States. The rapid advancement of AI technologies has led to a surge in electricity demand, prompting regulatory scrutiny regarding the natural resources these technologies consume. This dual challenge of managing environmental targets while advancing AI capabilities can offer a competitive edge for companies.

The article explains that scaling AI infrastructure requires substantial resources such as energy and water. Research predicts that data centers, driven partly by AI, may consume 3-4% of global power by 2030, potentially doubling their carbon dioxide emissions. Companies are adopting various strategies to mitigate environmental impacts, including enhancing their carbon-free energy portfolios, entering power purchase agreements for clean energy, strategically locating data centers in low-carbon areas, and improving data center efficiency.

From a governance standpoint, companies are leveraging the AI Risk Management Framework by the National Institute of Standards and Technology (NIST). This framework offers guidelines for assessing and documenting the environmental impact and sustainability of AI activities. The article also highlights recent legislative developments, such as the introduction of the Artificial Intelligence Environmental Impacts Act of 2024 by Congressional Democrats, which mandates a study on AI's environmental impacts and proposes a voluntary reporting system for these impacts.

Additionally, federal initiatives are underway to modernize the electric grid and support a clean energy economy using AI. NIST has also published draft guidance for generative AI, identifying environmental risks and suggesting over 400 actions to address these risks effectively. As the regulatory landscape evolves, companies must continuously evaluate and adjust their targets, keeping abreast of federal and state rulemaking on the energy and environmental implications of AI, as well as global regulations driving energy transitions.