It has been nine years since Digiconomist was first launched with the objective of “exposing the unintended consequences of digital trends.” For a big part of these nine years, the sustainability of digital assets such as Bitcoin has been a key focus of the research by Digiconomist. However, in 2022 and 2023 a new digital trend has emerged that has an equal potential to rapidly grow in terms of electricity consumption: artificial intelligence (AI). If not managed properly, AI could be responsible for as much electricity consumption as Bitcoin is today in just a few years’ time. This is the conclusion of a new research by Digiconomist titled “The Growing Energy Footprint of Artificial Intelligence” that was published in the journal Joule today (October 10, 2023). AI-servers are power-hungry devices. A single NVIDIA DGX A100 server can consume as much electricity as a handful of US households combined. Because of this, the electricity consumption of hundreds of thousands of these devices will start to add up quickly. While the supply chain of AI-servers is facing some bottlenecks in the immediate future that will hold back AI-related electricity consumption, it may not take long before these bottlenecks are resolved. By 2027 worldwide AI-related electricity consumption could increase by 85.4–134.0 TWh of annual electricity consumption from newly manufactured servers. This figure is comparable to the annual electricity consumption of countries such as the Netherlands, Argentina and Sweden. While this would represent half a percent of worldwide electricity consumption, it would also represent a potential significant increase in worldwide data center electricity consumption. The latter has been estimated to represent one percent of worldwide electricity consumption. Given the potential growth of AI-related electricity consumption, the new research contains a call to action to be mindful about the use of AI. Emerging technologies such as AI and previously blockchain are accompanied by a lot of hype and fear of missing out. This often leads to the creation of applications that yield little to no benefit to the end-users. However, with AI being an energy-intensive technology, this can also result in a significant amount of wasted resources. A big part of this waste can be mitigated by taking a step back and attempting to build solutions that provide the best fit with the needs of the end-users (and avoid forcing the use of a specific technology). AI will not be a miracle cure for everything as it ultimately has various limitations. These limitations include factors such as hallucinations, discriminatory effects and privacy concerns. Environmental sustainability now represents another addition to this list of concerns. Link to full article (DOI): doi.org/10.1016/j.joule.2023… For the first 50 days after the publication of the article it can be accessed for free using the following link: authors.elsevier.com/a/1huvY…

Let’s start the year by reflecting on the colossal growth in the resource consumption of AI and what it means for 2026. At the start of 2025, the global power demand of AI systems was approximately 9.4 GW. By the end of the year, this demand had likely increased to around 23 GW.

It appears the media have moved on to AI where they are, in fact, still using my research. Of course, amid the AI frenzy, it is worth remembering that Bitcoin remains responsible wasting as much resources as AI systems require in total at the moment.

I moved on to AI about three years ago, but glad to see my name still out there. Pro tip: a current measurement of direct water consumption in New York ≠ the total GLOBAL average water consumption (direct + INDIRECT) in 2021. Try saying something smarter in another 3 years.

Google released some new data on the environmental impact Gemini AI prompts, but omitted so many details you can hardly consider it useful. Instead, it does paint an overly rosy picture of the impact concerned. theverge.com/report/763080/g…