Despite its high environmental costs, AI could also help save the planet

The rapid growth of artificial intelligence has increased significantly increased electricity and water consumptionwhich raises concerns concerning the technology Environmental footprint and CO2 emissions. But the story is more complicated.

I study New technologies and the way their development and deployment influence economic, institutional and societal outcomes, including ecological sustainability. From my research I see that even when AI uses a lots of energyit may also produce systems cleaner and smarter.

AI is already helping to avoid wasting energy and water, reduce emissions, and make businesses in agriculture, data centers, energy, constructing heating and cooling, and aviation more efficient.

agriculture

Agriculture is answerable for almost every thing 70% of worldwide freshwater consumptionAnd Competition for water is increasing.

AI helps farmers use water more efficiently. Argentine climate technology startup Kilimo, for instance, is combating water scarcity with an AI-powered irrigation platform. The software uses large amounts of knowledge, machine learning in addition to weather and satellite measurements to find out this When and the way much which field areas should be irrigatedThis ensures that only the plants that really want water receive water.

The Chilean Ministry of Agriculture has found that within the country's Biobío region, farms using Kilimo's precision irrigation systems have reduced water consumption by as much as 30% while avoiding overwatering. In addition, less water is used reduces the quantity of energy needed to pump it off the bottom and around a farm.

Kilimo is an example that shows how AI can create economic incentives for sustainability: the quantity of water farmers save through precision irrigation is verified, and credits for these savings are sold to local corporations that need to offset a few of their water use. The farmers then make a profit – often 20% to 40% above their original investment.

Data centers

U.S. data centers used about 176 terawatt-hours of electricity in 2023, corresponding to about $1.5 billion 4.4% of total US electricity consumption. That number went up 183 TWh in 2024. This growing energy footprint has made improving data center efficiency a critical priority for data center operators themselves, in addition to the businesses that depend on them – including cloud providers, technology firms and huge enterprises running AI workloads – to each reduce costs and meet sustainability and regulatory goals.

AI is Data center support turn out to be more efficient. The number of worldwide web users grew from 1.9 billion in 2010 to five.6 billion in 2025. Global web traffic rose sharply 20.2 exabytes per thirty days in 2010 To 521.9 exabytes per thirty days in 2025 – a greater than 25-fold increase.

Despite the rise in Internet traffic and users, data center power consumption has increased more moderately and increased from 1% of worldwide electricity consumption in 2010 to 2% in 2025. Much of that is because of efficiency improvements, amongst other things those enabled by AI.

AI systems analyze operational data in data centers – including workload, temperature, cooling efficiency and energy consumption – to discover energy-hungry tasks. It adapts computing resources to demand and optimizes cooling. This allows data centers to operate easily without wasting power.

At Microsoft, AI improves energy efficiency Using predictive analytics to plan computing tasks. This allows servers to enter power saving mode during times of low demand, saving power during slower times. Meta uses AI to Control cooling and airflow in its data centers. The systems remain secure while using less energy than usual.

In Frankfurt, Germany, Equinix uses AI to Manage cooling and adjust energy consumption in its data center based on real-time weather. This improved operational efficiency by 9%, The New York Times reported.

Energy and fuels

Energy corporations are using AI to extend efficiency and reduce emissions. They unfold Drones with cameras for inspecting pipelines. AI systems analyze the pictures to acknowledge them more quickly Corrosion, cracks, dents and leaksThis allows problems to be addressed before they escalate, improving overall security and reliability.

Shell has AI systems that monitor methane emissions from its facilities through evaluation Methane concentrations and wind data reminiscent of speed and direction. This helps the system Track how methane is distributed, enabling accurate emissions determination Optimize energy sources and optimize energy consumption. By quickly detecting the most important leaks, the system enables targeted maintenance and operational adjustments to further reduce emissions. The company says it desires to work with this technology Nearly eliminate methane leaks by 2030.

AI could speed up clean energy innovation through improvements Solar panels, batteries and carbon capture systems. In the long run, it could enable major breakthroughs, amongst other things advanced biofuels and even usable nuclear fusionwhile also helping with tracking and management Carbon absorbing resources reminiscent of forests, wetlands and carbon sinks.

Shell uses AI across all of its operations to scale back emissions. It is Process optimizer for LNG analyzes sensor data to search out more efficient device settings, Increasing energy efficiency and reducing emissions.

Buildings and district heating

The energy required to heat, cool and operate buildings is answerable for roughly 28% of total global emissions. AI initiatives are starting to scale back constructing emissions through intelligent management and predictive optimization.

In downtown Copenhagen, for instance, the local utility company HOFOR used 1000’s of sensors for location purposes Temperatures, humidity and constructing energy flows. The system uses details about each constructing to forecast heating needs 24 hours prematurely and mechanically adjust supply to fulfill demand.

The Copenhagen system was first tested in schools and apartment buildings, with support from the Nordic Smart City Network and Climate Innovation grants. It has since expanded to dozens of internet sites. The results were clear: in all participating buildings, energy consumption fell by 15 to 25%, peak heat demand fell by as much as 30% and carbon dioxide emissions fell decreased by around 10,000 tons per yr.

AI may also help homes and offices save energy. Smart home systems optimize heating, cooling and device usage. Researchers at Lawrence Berkeley National Laboratory found that mid-sized office buildings within the US could achieve this by adopting AI Reduce energy consumption by 21% and reduce carbon dioxide emissions by 35%.

aviation

Um 2% of all human-caused carbon dioxide emissions in 2023 got here from aviation, which emitted about 882 megatons of carbon dioxide.

Condensation trails, the skinny clouds of ice that form when aircraft exhaust freezes at cruising altitudes, contribute to this greater than a 3rd of them the final warming effect of aviation by trapping heat within the atmosphere. AI can optimize flight routes and altitudes in real time Reduce contrail formation by avoiding areas where the air is more humid and due to this fact more prone to form contrails.

Airlines have also used AI Improving fuel efficiency. In 2023 Alaska Airlines used 1.2 million gallons less fuel through using AI for evaluation Weather, wind, turbulence, airspace restrictions and traffic to recommend probably the most efficient routes and save around 5% fuel and emissions on longer flights.

In short: AI has each positive and negative impacts on the environment. It has already helped industry reduce energy consumption, reduce emissions and use water more efficiently. Scaling up these solutions could lead on to a cleaner, more sustainable planet.