BloombergNEF (BNEF) reports that the rapid expansion of artificial intelligence is expected to hinder global efforts to reduce emissions over the next decade. AI's energy-intensive computational demands are predicted to drive increased electricity consumption, much of which will initially be met by fossil fuels. This surge in demand could slow the transition to cleaner energy sources and delay the achievement of critical emissions targets.
The report highlights that data centres, crucial for AI operations, are significant energy consumers. As AI models become more complex and widespread, their energy footprint will expand accordingly. While renewable energy capacity is growing, its deployment may not keep pace with the escalating energy needs of AI, leading to a continued reliance on fossil fuels to bridge the gap. The analysis suggests that without significant advancements in energy efficiency and a faster shift to renewables, AI could inadvertently prop up the fossil fuel industry and impede climate goals.
BNEF's findings underscore the importance of integrating sustainable energy solutions into the development and deployment of AI technologies. Efforts to mitigate the environmental impact of AI should focus on improving data centre efficiency, promoting the use of renewable energy, and developing AI algorithms that are less energy-intensive. Addressing these challenges will be crucial to ensuring that AI contributes to, rather than detracts from, global decarbonisation efforts.