Sustainable AI: Using Innovation Responsibly

As AI increasingly becomes part of our day-to-day, from brainstorming outlines to powering personalized learning, it is easy to focus on the benefits: speed, scale, and deeper insights. As we accelerate adoption, we also want to address: how do we align AI use with our personal and organizational values, including sustainability?

There can be a way to use AI that is both effective and environmentally responsible, and it starts with awareness.

AI’s Environmental Footprint

It’s no secret that AI systems, particularly generative models, rely on large data centers that consume significant amounts of electricity and water. These centers use cooling towers and outside air systems to prevent overheating, both of which require water. In fact, the projected water consumption from large-scale generative AI adoption could match the annual fluid intake of over 328 million adults (Accenture, Nature, 2024).

Electricity use is another common concern. AI queries, such as asking ChatGPT to summarize an email, consume roughly five times more electricitythan a standard web search (MIT News, 2025). Data centers already account for about 2% of all U.S. electricity use,and that number is expected to grow as AI adoption grows (Gartner).

AI As Part of the Solution

Despite its footprint, AI has enormous potential to support sustainability. The AI for Good movement is exploring how AI can help reduce greenhouse gas emissions and support climate resilience. Applications include AI-driven weather prediction, water management, waste monitoring, disease detection, biodiversity tracking, and precision agriculture (EY).

What You Can Do: Individual Best Practices

Using AI responsibly doesn’t mean using it less, it means using it smarter. Here are a few practical ways you can reduce your personal AI footprint:

• Be Purposeful with Prompts: When using an AI tool, thoughtfully structuring prompts, cutting unnecessary words, and reducing the amount of times you need to clarify or follow up can reduce energy consumption (Zhao, 2025).

• Use AI Where it Adds Value: Not every task needs AI. If a simpler tool or manual method works just as well, consider using it, especially for low-complexity tasks.

• Support Transparency and Governance. When choosing tools and technologies, consider how your colleagues or partners prioritize sustainability and responsible practices. Look for providers that share progress through transparent reporting and commit to goals like transitioning to renewable energy and reducing environmental impact. Staying informed helps you make decisions that align with your values and contribute to a more sustainable future.

For personal use outside of work, here are additional ways to reduce your AI footprint:

• Choose the Right Model for the Task: Selecting the most efficient model for the required task can help lower carbon production. Smaller models (e.g., the AI behind email spam filters or basic customer service chatbots) are great for straightforward tasks like answering yes/no questions or pulling basic facts. Larger models (e.g., ChatGPT, Copilot, Gemini) are better suited for complex reasoning or generating detailed responses, but they use significantly more energy -nearly three times the carbon output- than simple queries (Zhao, 2025).

• Run Tasks During Off-Peak Hours: Zhao (2025) compares AI usage to AC systems where the higher the temperature is outside the more energy is needed to cool off the inside. Best practice encourages limiting personal AI usage to later in the evening to decrease the amount of processing power used.

• Support Sustainable Platforms: When choosing which AI platform to use, take time to review what different companies are doing to address climate impact from AI. Choosing to support platforms with strong sustainability commitments in your personal and professional tech use is one way to contribute to a lower-carbon footprint.

As we continue to innovate, let’s also lead by example. By making informed choices, both individually and collectively, we can ensure that our use of AI supports not just productivity, but sustainability.

Julie Jasewicz  joined FMP in May 2023 as a Human Capital Intern and works on a variety of projects ranging from training and development to strategic communications. She graduated from George Mason University’s IO psychology master’s program and is originally from the Adirondack mountain region in New York. Julie is passionate about cooking, travel and is a loving cat mom to her kitten Winter.  

References

Accenture. (n.d.). Powering sustainable AI. https://www.accenture.com/us-en/insights/sustainability/powering-sustainable-ai 

Beatman, A. (2023, July 25). 15 tips to become a better prompt engineer for generative AI. Microsoft Tech Community. https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/15-tips-to-become-a-better-prompt-engineer-for-generative-ai/3882935

Deloitte. (n.d.). Powering AI: How to achieve Green AI. https://www.deloitte.com/global/en/issues/climate/powering-ai.html

EcoEngineering Hub. (n.d.). Best practices for responsible AI use. https://www.ecoengineeringhub.com/responsible-ai-use/

EY. (n.d.). AI and sustainability: Opportunities, challenges and impact. https://www.ey.com/en_nl/insights/climate-change-sustainability-services/ai-and-sustainability-opportunities-challenges-and-impact

Gartner. (n.d.). Keep AI from doing more climate harm than good. https://www.gartner.com/en/articles/keep-ai-from-doing-more-climate-harm-than-good

Marr, B. (2024, September 25). How to write amazing generative AI prompts. Forbes. https://www.forbes.com/sites/bernardmarr/2024/09/25/how-to-write-amazing-generative-ai-prompts/

Microsoft. (n.d.). Sustainability. Microsoft Corporate Social Responsibility. https://www.microsoft.com/en-us/corporate-responsibility/sustainability[1](https://www.microsoft.com/en-us/corporate-responsibility/sustainability)

MIT News. (2025, January 17). Explained: Generative AI’s environmental impact. https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117

Nature. (2024). How transparent is your AI?. https://www.nature.com/articles/d44151-024-00024-8 Zhao, C. (2025, July 2). How much energy does your AI prompt use? It depends. Science News. https://www.sciencenews.org/article/ai-energy-carbon-emissions-chatgpt