AI and Sustainability

The Challenge and Opportunity of AI and Sustainability

The explosive rise of artificial intelligence (AI) technology has led to tantalizing potential for sustainability solutions as well as enormous challenges for environmental, social, and economic governance. Intentional, responsible, safe, and sustainable AI use is profoundly important, and it also aligns with UC values and policy. The UC Responsible AI Principles includes “shared benefit and prosperity,” meaning that “AI-enabled tools should be inclusive and promote equitable benefits (e.g., social, economic, environmental) for all." The UC Policy on Sustainable Practices also mandates that procurement, energy consumption, and campus data center operations align with the university's strict net-zero carbon, clean energy, and ethical supply chain standards. This webpage provides tips and resources to help readers navigate these overlapping issues. 

If you’ve discovered a way to use AI more efficiently or have feedback on these tips and resources, please share your thoughts in our survey.

Tips for Greener AI Use

Artificial intelligence and the data centers that support it require significant energy, water, and critical minerals. The following checklist offers ways to minimize our collective environmental footprint in accordance with UC Berkeley values. 

  1. Be Intentional: is AI necessary for your task? Consider disabling AI services that are unneeded or offer minimal value.
  2. Consolidate Prompts: One well-structured prompt is more energy-efficient than a long "chat" session. This reduces the number of energy-intensive server calls.
  3. Opt for Text: Avoid AI image/video generation unless essential. One AI image can consume as much energy as a full smartphone charge. 
  4. Batch High-Impact Tasks: If you must generate images or large data analyses, do them in one session rather than intermittently throughout the day to allow server resources to spin down.
  5. Minimize "Idle" AI: Turn off automated AI meeting bots or summary tools when they are unnecessary for accessibility or record-keeping. Each automated summary adds to the campus carbon footprint.
  6. Apply Data Minimization: Only input the data needed for the task. Processing excess data increases the "compute load" and associated carbon footprint. 
  7. Leverage Models Wisely: Test "small" or "efficient" models to determine whether they meet your needs for  routine or simple text tasks before using more advanced models. Efficient models are often labeled with names like “Flash,” “Light,” “Fast”, and “Micro” while advanced models are labeled with names like “Ultra,” “Thinking,” or “Pro”.
  8. Use Berkeley-Licensed AI Tools: In addition to meeting security requirements, licensed tools are procured with consideration of "Green Spend" targets required by policy.
  9. Prevent E-Waste: Do not upgrade hardware (laptops/servers) solely for "AI-ready" features unless the existing equipment is at the end of its functional life, supporting UC's Zero Waste goals. When possible, update hardware elements rather than discarding the entire device.

AI + Environment Research at UC Berkeley

The following is a limited selection of the academic entities on campus doing research on AI and the environment. 

Resources and Policies

Resource Author Description
Berkeley AI Hub UC Berkeley Tools, Training, and Resources for UC Berkeley.
CERC-AIR UC Berkeley Committee of subject matter experts that provides risk assessment and risk mitigation guidance to units seeking to deploy AI at UC Berkeley.
UC Responsible AI Principles UC AI Council UC systemwide ethical guide.
UC Berkeley Guidance on Appropriate Use of AI Office of Ethics, Risk, and Compliance Services Interpretation of existing policy as it applies governing use of AI.
UC Berkeley Licensed AI Tools Berkeley IT AI tools licensed in a process including requirements set forth by the UC Policy on Sustainable Practices
UC Artificial Intelligence Risk Assessment Guide (2025) UC Office of the President Designed to help UC community members evaluate both the risks associated with using artificial intelligence in administrative settings and whether their intended use aligns with their location’s risk tolerance.
UC Policy on Sustainable Practices UC Office of the President Goals in 13 areas of sustainable practices, including Clean Energy, Sustainable Procurement, and Sustainable Water Systems.
UC Berkeley Climate Action Plan (published draft in public comment period) Office of Sustainability Most recent plan; will replace 2020 Plan.
Clean Energy Campus Utility Improvement Project Office of Sustainability Description of the plan to modernize UC Berkeley’s energy infrastructure by replacing its aged steam system with efficient, all-electric heating and cooling systems.

Selected Reading/Watching/Listening (last updated April 2026)

  1. What Your Digital Life Uses (2026)
  2. Doing Data Centers the Not-Dumb Way (2026)
  3. Stanford 2026 AI Index Report
  4. Energy and AI (2025)
  5. Artificial Intelligence Meets Natural Stupidity: Managing the Risks (2025)
  6. RARE/EARTH: The Geopolitics of Critical Minerals and the AI Supply Chain (2025)
  7. What we know about energy use at U.S. data centers amid the AI boom (2025)
  8. From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debate (2025)
  9. The PR Machine Powering Big Tech’s AI Energy Story (2025)
  10. ICEF Roadmap 2023: AI for Climate Change Mitigation