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Artificial intelligence already uses as much energy as a small country and its energy consumption is only getting larger. By 2028, its computing power demand may increase more than a million times.
But AI also has tremendous potential to improve energy efficiency and optimize emission-reduction technologies. Its net impact on climate change is uncertain, yet some experts predict it could reduce 5 to 10 percent of global greenhouse gas emissions.
In a recently published edition of the Angeleno Group Reader — “Artificial Intelligence and Climate Solutions,” — Angeleno Group reviews literature on AI’s applications in clean energy and climate solutions, ranging from smart grid management to advanced material science for energy storage solutions. Founded in 2001, Angeleno Group fosters environmental impact alongside financial returns through investments in high growth, sustainability-focused companies.
The report summarizes how AI is revolutionizing various sectors within the energy and industrial realm. One particularly noteworthy application is optimizing electricity distribution networks by modeling real-time emissions, managing electricity scheduling algorithms, and improving supply and demand matching by reducing uncertainty in forecasts. To Illustrate, The State Grid Corporation of China (the largest utility company in the world) uses AI technology to monitor vulnerabilities in transmission lines and perform maintenance before prevent power outages occur.
Mitigating climate change also greatly depends on reducing greenhouse gases from buildings, which produce 39% of the world’s emissions — 28% related to operations and 11% from materials and construction. AI can be deployed to more effectively manage energy use through utilizing smart appliances and adaptive control systems for heating and cooling, adjusting lighting and temperature to occupancy patterns, and performing energy-intensive operations during periods when renewable energy is highly available. Additionally, it can accelerate materials science for energy storage, as well as suggest designs for optimal energy capture via solar panels and wind turbines.
Additionally, the Angeleno Group reader presents case studies from portfolio companies harnessing AI: REsurety provides a Locational Marginal Emissions Tool that helps data centers align energy consumption with clean energy production, Span.io employs advanced analytics in smart panels to enable homeowners to optimize their energy use, and Fictiv provides AI-processed information to assist customers in making manufacturing decisions on component parts.
However, the reader cautions that the expansion of AI must proceed with prudence and transparency, guided by robust frameworks that ensure the responsible rollout of these technologies. A deeper analysis of AI’s growing energy demand is necessary, as the media has historically failed to predict the future energy consumption of new technology. For instance, global data center energy use only rose 6% between 2010 and 2019, while workloads increased by 550%, largely due to efficiency improvements in storage, networking, servers, and infrastructure
Currently, AI uses only a fraction of the 2-3 percent of total global energy use associated with data centers. Yet as generative AI expands, so does its energy demand; the computing power necessary to support AI’s growth doubles every 100 days. Most data centers are currently run on fossil fuels, yet all major cloud providers plan to transition to net-zero carbon by 2030.
Advances in hardware and processing power are predicted to improve the efficiency of AI and data centers. Selective use of AI and policies; such as European Union Parliament’s bill requiring high-risk AI systems to log energy consumption, resource use, and environmental impact; could also reduce AI’s carbon footprint. Yet, the net impact of AI on grid stability and climate change remains to be seen.
The possibilities of AI are boundless, from suggesting low-emission transportation routes, to refining climate predictions, to assessing suitability for carbon capture. Furthermore, AI can bolster data analytics, improve decision-making at both municipal and national levels, and enable cities to more effectively plan for climate resilience.
Angeleno Group’s latest report outlines AI’s applications in the environmental sector and provides a framework for its thoughtful integration into efforts to address climate change. While AI holds significant potential for supporting sustainability, its development should be approached carefully to manage potential risks alongside its benefits.
