Sustainable AI: How AI Can Help with Sustainability

Key takeaways

Sustainable AI is the practice of using artificial intelligence to encourage energy efficiency and minimize negative impact on the environment. Here are some important facts to know:

• According to Morgan Stanley’s Sustainable Signals: Corporates 2025 report, 88 percent of companies view sustainability as an opportunity to create value long-term [1].

• Training AI models requires a substantial amount of energy. Some companies are working to address this to help protect the environment without sacrificing innovation.

• You can pursue a wide range of careers in artificial intelligence, where you will have the opportunity to implement sustainable strategies.

Discover how you can continue pushing artificial intelligence forward while simultaneously looking out for the environment. If you’re ready to start preparing for a career in AI, the AI Foundations for Everyone Specialization from IBM is designed to help you develop valuable skills, such as prompt engineering and how to build a chatbot.

What is sustainable AI?

Sustainable AI refers to developing AI systems in an energy-efficient manner to mitigate the environmental impact of these often energy-intensive systems. AI models consume a substantial amount of electricity, often derived from fossil fuels, resulting in carbon emissions, as well as high water usage for cooling systems in AI data centers. However, you can implement strategies that lessen the impact, allowing AI to operate as a much more sustainable field. These strategies include recycling hardware materials, using renewable energy sources, and developing more specialized AI models to limit the computational demand compared to general models.

Does AI have a big carbon footprint?

AI has a significant carbon footprint, primarily due to the energy requirements of data centers. AI models depend on vast amounts of training data, which is stored in data centers. Data centers contain infrastructure, such as network equipment and servers, that consume a significant amount of power. Data centers account for between 1 and 1.5 percent of global greenhouse gas emissions [2]. Performing a query on a generative AI model also requires significantly more energy than your standard web search, so it’s not just data centers contributing to AI’s carbon footprint.

How does AI contribute to environmental sustainability?

Despite some of the consequences AI has in terms of emissions, you can use AI for environmental sustainability, with opportunities to conserve natural resources and reduce waste to help fight climate change. Examples of how AI can contribute to a more sustainable environment include:

• Waste management: AI can improve recycling processes in several ways, such as identifying recyclable materials to separate them from waste through sorting systems, and optimizing the logistics of recycling facilities to improve efficiency and lower energy usage.

• Farming: Implementing AI in farming and agriculture helps with managing water and pesticide usage. Using AI can also lead to improved crop yields without excessive resource usage by identifying factors such as optimal soil conditions.

• Transportation: Route optimization and autonomous vehicles are two ways AI can lower fuel usage, ultimately reducing carbon emissions.

• Environmental monitoring: AI can help protect natural resources for a more sustainable environment by analyzing climate patterns, monitoring ocean health and deforestation activity, as well as tracking wildlife.

• Supply chain management: The supply chain management industry can use AI to improve its environmental sustainability and lower emissions through machine learning models that help identify ways to better manage inventory levels and optimize shipping routes.

AI tools for sustainability monitoring and integration with ERP systems

Enterprise resource planning (ERP) systems, with the help of AI, can autonomously promote environmentally friendly business operations by improving operational efficiency and reducing waste. AI in ERP systems can perform data analysis to give you insights into managing production based on market demand, reduce hardware reliance by utilizing the cloud, and improve energy efficiency in warehousing with inventory control and environmental detection systems, each of which can help lower your carbon footprint. Some examples of AI-powered ERP systems you can integrate with your business operations are:

• SAP Cloud ERP

• Microsoft Dynamics 365

• Oracle Fusion Cloud ERP

• Epicor Kinetic

Benefits and challenges of sustainable AI

Sustainable AI can be beneficial for the environment, as it helps resources be used more efficiently and identifies areas of risk. However, within the conversation of AI sustainability, it’s important to also acknowledge the challenges presented by AI models' energy usage and the high carbon dioxide emission levels as a result of training and using AI. 

AI can work with existing data and tools to optimize the usage of valuable resources such as water and energy, track concerns such as glacier melt and deforestation, reduce waste, and improve the energy efficiency of urban developments. Furthermore, AI-powered tools make sustainability more easily measurable, so you can have a clear picture of your organization's environmental impact and ensure you’re working toward environmental, social, and governance (ESG) goals.

What is Green AI?

Green AI is an environmentally conscious approach to AI, with the goal of offsetting artificial intelligence's carbon footprint. For example, you can move data centers to areas with access to more climate-friendly energy to lower their carbon footprint and increase the usage of energy-efficient hardware. Additionally, you can use models that perform less extensive training, avoiding unnecessary, excessive training that ultimately doesn’t further improve the model's accuracy.

Getting started with sustainable AI initiatives

You can support sustainable AI initiatives by opting to use AI models and platforms that have shown a commitment to sustainability. Google, for example, is aiming to use AI in products designed to lower emissions in the transportation and energy sectors [3]. When organizations start implementing more sustainable AI initiatives, it’s a good idea to measure their emissions to know where they currently stand, and track their efforts over time to ensure they’re moving in the right direction. Implementing sustainable AI initiatives is a worthwhile effort, with 88 percent of companies viewing sustainability as an opportunity to create long-term value [1]. 

Explore our free artificial intelligence resources

Looking to learn more about artificial intelligence? Explore some of our free resources, like our LinkedIn newsletter, Career Chat, and the following:

• Watch on YouTube: How AI is Transforming Business (And Your Morning Coffee) 

• Hear from an expert: AI Problem-Solving Tactics: Expert Insights from Vanderbilt's Dr. Jules White

• Take the quiz: AI Career Quiz: Is It Right for You? Find Your Role

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