Dashboard / Circularity strategies

Circularity strategies

Reduce e-waste across the AI hardware lifecycle

8

strategies

Design

Design for Disassembly

AI priority

Specify screw-based fastening, labeled subassemblies and tool-light access so servers, GPUs and cooling modules can be separated cleanly at end of life.

Impact
High
Feasibility
Medium
AI relevance
High

Design

Modular and Upgradeable Architecture

AI priority

Decouple accelerators, memory and storage from the chassis so a node can be upgraded rather than replaced when a new AI hardware generation arrives.

Impact
High
Feasibility
Medium
AI relevance
High

Use

Reuse and Refurbishment

AI priority

Redeploy retired training hardware into inference, staging or edge workloads, extending useful life by two to four years before recycling.

Impact
High
Feasibility
High
AI relevance
High

Procurement

Circular Procurement

AI priority

Embed repairability, take-back guarantees, spare-part availability and recycled-content thresholds into every hardware tender.

Impact
High
Feasibility
High
AI relevance
High

End of life

Component Recovery

AI priority

Harvest DIMMs, SSDs, power supplies and interconnects from decommissioned nodes to feed spare-part pools and cut new procurement.

Impact
Medium
Feasibility
High
AI relevance
High

Operations

Cooling Retrofit over Replacement

AI priority

Convert air-cooled halls to liquid cooling with retrofit kits so rising AI rack density does not force premature demolition of infrastructure.

Impact
Medium
Feasibility
Medium
AI relevance
High

End of life

Material Recycling

Route non-reusable hardware to certified recyclers capable of recovering copper, gold, palladium and rare-earth elements at high yield.

Impact
Medium
Feasibility
High
AI relevance
Medium

Operations

Asset Traceability and Data Passports

Track every asset from install to disposition with a digital passport recording composition, repairs and final treatment route.

Impact
Medium
Feasibility
Medium
AI relevance
Medium