What question did this study set out to answer?

The aim is to reevaluate the e-waste generation estimates from artificial intelligence servers by 2030.

February 26, 2026Resources Conservation and Recycling0 citationsOpen Access

Recalibrating global artificial intelligence e-waste estimates

Key Points

The aim is to reevaluate the e-waste generation estimates from artificial intelligence servers by 2030.
Analyzed projected e-waste from AI servers for 2030
Compared with previous estimates and e-waste production in countries like Denmark, Norway, and Austria
Emphasized the importance of supply-chain data and server lifespans
AI servers could generate between 131.0 and 224.8 kilotons of e-waste annually by 2030
AI's contribution to global e-waste may be less significant than earlier projections
Highlighting a substantial amount of AI e-waste remains, necessitating data center transparency

Abstract

• 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.

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