Lead the Change

The evolution of artificial intelligence is among the most remarkable technological achievements of the 21st century. Scientists have developed and refined AI to facilitate advancements in fields like healthcare, transportation, and sustainability. Over the years, the technology has progressed rapidly—what began with machines playing chess or the first radio-controlled vessels has now evolved into tools like ChatGPT and self-driving cars. Yet, like any innovation, AI comes with both costs and benefits. While artificial intelligence has the potential to make positive environmental impacts with its predictive capabilities, energy efficiency, and more, it also poses environmental challenges, including high water and energy consumption; as well as e-waste. The balance of these consequences raises the necessary question: Can AI’s benefits in advancing jobs in sustainability outweigh its environmental costs?

Below, we’ll tackle this question by diving into the various positive and negative environmental impacts of AI. 

Is AI Bad for the Environment?

AI’s rapid expansion isn’t without its consequences. Its development and operation require considerable resources, with three key areas standing out:

1. AI Energy Consumption 

Training AI models and performing routine tasks demand immense computational power, which requires a staggering amount of energy. For instance, training a single large AI model can generate as much carbon emissions as five cars in their lifetime. Data centers—the physical spaces housing the servers that power AI—consume massive amounts of electricity, much of which still comes from non-renewable energy sources. According to the International Energy Agency, energy consumption by global data centers could more than double by 2026.

A large aspect of maintaining data centers is the constant cooling systems required to prevent overheating, which are notably energy-intensive. Currently, it’s estimated that global demand for data center capacity could rise at an annual rate of between 19 and 22 percent until 2030. This has made the global data center industry a significant contributor to carbon emissions, projected to emit 2.5 billion tons of CO2 through 2030. As energy demands soar, hardware designers and engineers are racing to create more energy-efficient systems to mitigate AI’s environmental impact.

2. E-Waste

The rapid development of AI technology often results in frequent hardware upgrades, contributing significantly to electronic waste (e-waste). Servers, specialized processors, and other technological components are frequently discarded as new hardware is developed to meet the increasing demands of AI systems. Many of these discarded materials contain toxic substances that are difficult to recycle, posing a threat to the environment if not properly managed. 

As AI technology continues to advance, this waste stream is expected to grow by 3% to 12% by 2030, potentially amounting to 2.5 million metric tons of additional waste yearly. This alarming projection underscores the pressing issue of sustainable hardware solutions and improved recycling systems.

 3. Water Consumption

AI’s rapid growth and the expansion of data centers are significantly impacting water resources, exacerbating concerns about sustainability. In locations like West Des Moines, Iowa, where major tech companies operate, facilities such as those run by Microsoft consume around 6% of the district's water supply. Similarly, in The Dalles, Oregon, a court case revealed that Google’s data centers used nearly a quarter of the town’s available water. This trend is not isolated, as tech giants continue to scale up AI-driven services, increasing demand for cooling systems that consume vast amounts of water. In fact, data centers equipped with AI cooling systems can use up to 9 liters of water per kWh of energy consumed, contributing to a growing water footprint that, according to Forbes, could reach 6.6 billion cubic meters annually by 2027.

Adding to the challenge, the energy used to power these data centers often comes from water-intensive thermoelectric plants, further exacerbating water consumption. For example, on average, 43.8 liters of water are withdrawn per kWh of electricity generated. Google’s environmental report noted that its carbon footprint increased by 48% due to its growing AI infrastructure, and it replenished only 18% of the water consumed, far from its goal of 120% by 2030. 

As AI’s role in our technological ecosystem deepens, the need for sustainable solutions to manage both energy and water consumption becomes more critical.

How AI Supports Sustainability Efforts

Despite its environmental challenges, artificial intelligence holds immense potential to drive sustainable solutions, especially in advancing careers that address climate challenges. AI enables climate scientists to predict extreme weather patterns, farmers to optimize resource use in agriculture, and energy engineers to sustainably operate buildings. Here are some of AI’s environmentally beneficial contributions:

Predictive Capabilities

AI excels at analyzing large datasets, making it an invaluable tool for climate scientists. For example, AI models can forecast extreme weather patterns, track carbon emissions, and identify areas most vulnerable to environmental degradation. These insights enable proactive measures, reducing the overall impact of climate events. AI has also significantly improved the accuracy of flood predictions by processing vast amounts of climate and weather data. Machine learning algorithms can identify patterns and predict flood risks and other major weather events more quickly, providing earlier warnings and helping mitigate the impacts of natural disasters.

Smart Farming Biotechnology

AI-powered precision farming is transforming agriculture. By optimizing irrigation, reducing pesticide use, and monitoring crop health, AI helps farmers increase yields while minimizing environmental harm. For example, in California, a winery implemented a cloud-based tool that ingests data from weather forecasts, satellite imagery, and sensors to measure vine stress. The analysis of this data provides tailored watering recommendations for each vine, resulting in a 26% increase in yields while reducing water usage by 16%. This technology not only supports food security but also reduces resource wastage, making farming more efficient and sustainable.

Resource Management

From water conservation to mineral tracking, AI enhances resource management by providing real-time insights. Industries can use AI to monitor consumption, detect inefficiencies, and implement strategies to maximize resource utilization while minimizing waste. For example, modern technology now allows farmers to use apps that indicate soil conditions and weather forecasts, helping farmers better use their water supply. This is particularly an advantage for areas affected by droughts that need to use their water efficiently following regional regulations. 

Energy Efficiency

AI plays a pivotal role in optimizing energy grids, predicting peak usage times, and integrating renewable energy sources like solar and wind. Smart building systems equipped with AI can adjust heating, cooling, and lighting in real time, significantly reducing energy consumption. A recent study estimated that AI integration in HVAC systems reduced energy usage and carbon emissions by at least 8%. When put to the test, one AI HVAC system was able to reduce energy consumption by 15.8% over almost 1 year.

With predictive and proactive solutions of this nature, AI has the ability to change the future of resource allocation in a manner that could produce remarkable results.

The Bottom Line on the Impacts of AI

Artificial intelligence represents both a challenge and an opportunity for our planet. Its environmental costs—from high energy/water consumption to e-waste—are undeniable. Yet, its potential to drive sustainability efforts through predictive models, smart agriculture, resource management, and energy efficiency cannot be overlooked. By adopting ethical and sustainable practices, AI can play a vital role in combating climate change while creating impactful jobs in sustainability.

Therefore, the question we should pose isn’t whether AI should be used but rather how it can be developed and deployed responsibly. Ethical AI practices are crucial for minimizing environmental harm while maximizing its benefits for sustainability. 

These practices could look like:

• Transitioning data centers to renewable energy sources.
• Investing in recycling programs to reduce e-waste.
• Designing energy-efficient AI algorithms.
• Extending hardware lifespans through modular designs and upgrades.
• Using water-efficient cooling technologies, like closed-loop systems.

Are you passionate about addressing today’s environmental challenges? Advance your career and equip yourself with the knowledge and tools of modern technology to meet the ever-evolving needs of our planet. Explore Bard University’s Sustainability Programs for Climate Champions. 

These programs blend environmental science, economics, and international development to prepare you for a career with purpose. 

Take the first step toward making a lasting impact and request more information!