The explosive growth of generative artificial intelligence, which creates content like text, images, audio and synthetic data, is expected to add millions of metric tonnes of electronic waste annually by the end of the decade, a study in Nature Computational Science has said.

This rise in e-waste is due to the rapid expansion of AI applications and data centres, which demand frequent upgrades of high-performance computing hardware. Short life cycles for advanced processors and storage equipment mean devices are replaced often to meet rising demand, resulting in a surge of discarded electronics.

Generative AI models, such as large language models, are highly resource-intensive, requiring powerful servers, processors and storage solutions to operate effectively. As big-tech companies race to develop more sophisticated models and hardware, e-waste from discarded equipment is piling up. At the current adoption rate, e-waste from generative AI could reach between 1.2 and 5 million metric tonnes annually by 2030 – a thousand-fold increase over today’s levels.

Reducing e-waste generated by artificial intelligence is not without its challenges. Data security is a major barrier, as companies often destroy used devices to protect sensitive information. Secure data erasure technology could allow for safe reuse without compromising privacy. Recycling also remains expensive due to the cost of safely handling hazardous materials, even though recycled metals hold significant economic value.

The Global E-Waste Monitor estimates that only 22 percent of electronic trash is formally recycled, with much of it ending up in informal recycling systems in lower-income countries, where safe processing methods are usually unavailable.