As artificial intelligence (AI) becomes increasingly pervasive in business and governance, its considerable environmental impact – from significantly increased energy and water consumption to increased carbon emissions – cannot be ignored. By 2030, AI’s energy demand is expected to increase by 160%. However, adopting more sustainable practices, such as using baseline models, optimizing data processing sites, investing in energy-efficient processors, and leveraging open-source collaborations, can help mitigate these impacts. These strategies not only reduce AI’s environmental footprint, but also improve operational efficiency and cost-effectiveness, balancing innovation and sustainability.
How businesses can mitigate AI’s growing environmental footprint
