Several large tech firms that are active in AI have set goals to hit net zero by 2030, but a new forecast of the energy and water required to run large data centres shows they're unlikely to meet those targets As the AI industry rapidly expands, questions about the environmental impact of data centres are coming to the forefront - and a new forecast warns the industry is unlikely to meet net zero targets by 2030. Fengqi You at Cornell University in New York and his colleagues modelled how much energy, water and carbon today's leading AI servers could use by 2030, taking into account different growth scenarios and possible data centre locations within the United States. They combined projected chip supply, server power usage and cooling efficiency with state-by-state electrical grid data to conduct their analysis. While not every AI company has set a net zero target, some larger tech firms that are active in AI, such as Google, Microsoft and Meta have set goals with a deadline of 2030. "The rapid growth of AI computing is basically reshaping everything," says You. "We're trying to understand how, as a sector grows, what's going to be the impact?"

Three years ago, Google set an ambitious plan to address climate change by going "net zero", meaning it would release no more climate-changing gases into the air than it removes, by 2030. But a report from the company on Tuesday showed it is nowhere near meeting that goal. Rather than declining, its emissions grew 13 percent in 2023 over the year before. Compared with its baseline year of 2019, emissions have soared 48 percent. Google cited artificial intelligence and the demand it puts on data centres, which require massive amounts of electricity, for last year's growth.

In this article we drill into why Monitoring & Targeting often doesn't deliver on its true savings potential and how Machine Learning can overcome this. Net Zero has never been a bigger topic. Amongst the sea of Science Based Targets and long term reduction strategies, it's clear that there is no single answer to reaching net zero and for most organisations it's a marathon not a sprint. However many businesses are looking again at what they can do in the short term to make an immediate impact. Reducing demand is the first step of any energy hierarchy and utilising data in a commercially-viable way is critical to this.

COVID-19, a low oil price and an industry facing increased environmental scrutiny has resulted in a turbulent 2020 for the oil and gas sector. As many North Sea fields reach maturity, stakeholders will be carefully considering their options including decommissioning and diversifying the energy mix. The National Decommissioning Centre (NDC) (a partnership between the University of Aberdeen, the Oil & Gas Technology Centre (OGTC), and industry) has said that efficient late-life management and decommissioning of assets is a "societal and economic necessity". Emerging tech and artificial intelligence (AI) can help achieve this. However, the contribution AI and new technology could have on decommissioning cannot be considered in isolation.