Artificial Intelligence (AI) is increasingly being recognized as a significant consumer of electricity, prompting concerns about its environmental implications. According to a report from The New Yorker, OpenAI's renowned generative AI model, ChatGPT, is estimated to consume over half a million kilowatt-hours daily to handle approximately 200 million user requests per day. This astonishing figure exceeds the average daily energy consumption of a typical US household by more than 17 thousand times.
The potential escalation of energy consumption becomes even more alarming as generative AI becomes more prevalent. Data scientist Alex de Vries' calculations suggest that if Google were to integrate generative AI into every search, it could result in an annual energy consumption of approximately 29 billion kilowatt-hours, surpassing the yearly electricity usage of entire countries like Kenya, Guatemala, and Croatia.
De Vries underscores the energy-intensive nature of AI by highlighting that each AI server could already consume as much power as over a dozen UK households combined. However, accurately estimating the overall electricity consumption of the AI industry poses challenges due to variations in model operations and a lack of transparency from the major tech companies driving the AI surge.
Based on data from Nvidia, a leading chipmaker in the AI sector, De Vries' paper projects that by 2027, the entire AI industry could consume between 85 to 134 terawatt-hours annually. This would constitute a significant portion of global electricity consumption, potentially reaching half a percent by 2027.
In comparison, some of the world's most electricity-intensive businesses fall short of the projected AI consumption. For example, Samsung consumes nearly 23 terawatt-hours, while tech giants like Google and Microsoft utilize around 12 and 10 terawatt-hours, respectively, to power their data centers, networks, and user devices.
As AI continues its expansion across diverse industries, addressing its energy consumption emerges as a crucial priority to mitigate environmental impacts. Efforts to develop more energy-efficient AI algorithms and hardware are essential to strike a balance between technological advancement and sustainability objectives.
