Over the past year, my research has first highlighted the rapidly growing power demand of AI systems, followed by an assessment of the associated carbon and water footprints.

Today, my latest research—published in Resources, Conservation & Recycling—addresses another, often overlooked consequence of the expanding AI infrastructure: electronic waste.

While this is not the first attempt to examine AI-related e-waste, it is the first estimate grounded in supply-side data, rather than inferred from demand-side assumptions.

The main findings are as follows:

• By 2030, AI servers could generate 131.0–224.8 kilotons of e-waste per year.
• AI systems may contribute less to global e-waste than previously anticipated.
• The gap highlights the need for supply-chain data and realistic AI server lifespans.
• 2030 AI e-waste could still match Denmark, Norway, or Austria’s 2022 e-waste.
• Substantial AI e-waste persists, underscoring the need for data center transparency.

The full article is available open access and can be accessed here: https://doi.org/10.1016/j.resconrec.2026.108872