Resources · AI Infrastructure Lifecycle
Disposition timing against the depreciation curve
Written for the finance function rather than the recycler. This page separates what has actually been disclosed or observed from what is being forecast — because a great deal of what circulates about AI hardware depreciation is the second sort presented as the first.
Why this page exists
The accounting question and the physical question have come apart
For most of the history of enterprise infrastructure, a depreciation schedule was a workable proxy for when equipment would leave a rack. For accelerated computing, that relationship has broken — and it has broken in both directions at once.
Operators are revising useful lives in opposite directions on comparable hardware, and separately, running equipment well past the point the schedule implies because it still earns.
That leaves the timing decision genuinely open, which is uncomfortable but also useful: it means the decision is yours to make on operating grounds rather than one the accounting makes for you.
Observed · disclosed in filings
What major operators have actually changed, and when
| Operator | Change | Effective | Disclosed impact |
|---|---|---|---|
| Amazon | Servers and networking extended 4→5 years | 1 Jan 2022 | $3.6B reduction in depreciation expense |
| Amazon | Servers extended 5→6 years | 1 Jan 2024 | $3.2B reduction in depreciation expense |
| Amazon | A subset of servers and networking shortened 6→5 years, citing the increased pace of technology development in AI and machine learning | 1 Jan 2025 | $1.4B increase in depreciation expense |
| Meta | Useful life extended to 5.5 years | Disclosed 29 Jan 2025 | Lower 2025 depreciation |
| Microsoft | Extended 4→6 years | 2022 | — |
| Oracle | Extended 4→5 years | 2023 | — |
Source: company disclosures. The 2025 revision is the one worth reading twice — it is the first shortening in the set, and the stated reason names AI directly.
Signal and noise
Four things that are observed, and two that are being forecast at you
Operators disagree, in both directions, on identical hardware
Published useful-life assumptions currently span four to six years across major operators, and the direction of travel is not one-way — Amazon shortened its assumption in the same period Meta lengthened its. That is not a market converging on an answer. It is a market that does not have one.
Prior-generation accelerators are still contracted forward
Named operators have stated on the record that prior-generation accelerators remain fully utilised and are under contract years into the future. The only confirmed public retirement of a large accelerator fleet is a generation further back than the one the market talks about.
A power and cooling constraint is holding hardware in place
Legacy halls were built around roughly 20 kW per rack. Current-generation accelerated racks draw about 120 kW by the manufacturer's own figure. Facilities cannot host the newest hardware without a power and cooling rebuild, so the previous generation stays in service.
The published residual figures disagree by roughly a factor of two
Because they use different denominators. One index measures against today's new price, which has itself fallen sharply; another measures against original list price set during a shortage. Both can be internally consistent. Neither is comparable to the other.
A large retirement wave arriving imminently
Widely asserted, including by parties selling disposition services. We could not find transaction volumes, filings or operator statements supporting it. Treat as a forecast.
An 18–24 month accelerated refresh cycle
Circulated in vendor commentary and sponsored content. Every instance traced back to a party with a commercial interest, and none was accompanied by volumes actually being processed. Treat as a vendor assertion.
The decision
Four states, and what each one actually calls for
- Still earning
- Operating economics almost always outweigh a declining residual. The disposition question is premature, and the right action is to revisit it on a schedule rather than a hunch.
- Out of service, decision unowned
- The expensive case, and the most common one. Equipment that stopped earning months ago and is still in a staging area is losing value on a clock nobody is watching. This is where the largest avoidable losses in the category occur.
- Out of service, decision owned
- Move on a defined timetable. The relevant window is short — the observed period before material decline is measured in weeks, not quarters — and sequencing is a financial decision, not a logistical one.
- Retiring against a lease or site deadline
- Timing is fixed for you, so the variable is preparation. The projects that lose money here are the ones where discovery started too late for the inventory to be built before the trucks were booked.
The second row is where the money goes. It is also the only one of the four that nobody has put on an agenda, precisely because no single function owns it.
FAQ
What finance and infrastructure teams ask
Can we plan a disposition pipeline from our depreciation schedule?
What is a fair residual expectation?
How much does waiting cost?
Is refurbished worth the extra handling?
Should we sell outright or share the proceeds?
What is the single most expensive timing mistake?
Sizing the cost of waiting on a specific estate?
We would rather model your actual configuration and timeline than quote you a market-wide percentage that may not describe your equipment at all.