The management of sustainability focused on digital and artificial intelligence (AI) is an emerging trend that sees the implementation for, for example, to integrate climate risk analysis into incident management data for better management of extreme weather events.
More and more regulators are obliging the disclosure of data on real -time emissions, pushing companies to adopt automated surveillance solutions. Industrial companies use digital twins for energy efficiency and modeling climate risk scenarios. Overall, the AI and advanced analyzes are integrated into the durability, monitoring of the carbon footprint and the optimization of the supply chain.
But there is a disadvantage of the use of AI and digital solutions, which are the energy data centers to store cloud data and artificial power intelligence. Data centers with hundreds of thousands of computers must be kept cool with electricity and sometimes refrigerated water, putting pressure on energy and water resources.1 The AI uses so much electricity that Google has reported that its greenhouse gas emissions have jumped 50% since 2019.2 Each chatgpt query is transported to a data center and supplied with an AI system, using as much electricity as this could supply a bulb for 20 minutes.
Google, Microsoft and Meta technological companies have undertaken to reach at least net carbon emissions by 2030, and Amazon has committed to reaching net zero emissions by 2040. The four companies have committed to being positive in water by 2030, which means that they would reconstruct the environment with more water than for operations.3 Microsoft made an additional commitment to be negative in carbon by 2030, but in their sustainability report published in May 2024, they revealed that emissions increased by 29% compared to 2020 due to the construction of the data center to support the workloads of the AI.4
In a session in small groups on the sustainability of recent Wolters Kluwer Amablon Sustainable performance forum (SPF) 2025 event in Chicago, Stuart Neumann, vice-president of advisory services at Verdantixsaid that these technological companies have ambitious carbon reduction objectives, the arrival of AI has increased their emission trajectories. Neumann added that there is no immediate solution to this problem, and the next two to three years will likely see growing emissions for these companies. He stressed the difficulty of supporting AI data centers with renewable energies and said that nuclear energy may be necessary to reach the required scale.
The use of nuclear energy to generate enough energy to supply the data centers and the workloads of the AI presents another charge of natural resources, as nuclear power plants (NPP), such as data centers, are generally based on water for cooling purposes. A typical NPP consumes 20% to 80% more water than energy installations with carbon with similar capacity, which leads to daily consumption of water between 35 and 65 million liters.5 In response to global water shortages, NPPs are looking for more sustainable and less intense resources to cool installations while maintaining (and even improving) operational efficiency.
No matter how you cut it, AI eats and drinks a lot of energy and water, and producing more energy to supply AI also requires many natural resources.
Most of us may not have planned how much the omnipresent AI would quickly become and how easy it would be to use chatbots to get aid for research, homework, coding or to create videos and images. To follow the request, Apple recently announced its intention to spend $ 500 billion in the next four years to build new data centers. Google plans to spend $ 75 billion in AI infrastructure in only 2025.6
Currently, 4.4% of all energy in the United States goes to data centers. And given the current trajectory of the development and accessibility of AI, our use of AI is the lowest that it will ever be. The projections of Lawrence Berkeley National Laboratory in December 2024 predict that in 2028, more than half of the electricity would go to data centers will fuel AI, which means that AI could consume as much electricity per year as 22% of American households.7
The imminent question is how to establish a balance in using AI and cloud -based solutions to help all types of businesses (not just technological companies) achieve their durability objectives, while using AI to help individuals in their daily lives?