“AI is not just another technological wave. It is an economic force that reshapes how value is created and how quickly it fades.” - Andrew Ng, Entrepreneur and researcher
Market anxiety around AI depreciation
A sharp downturn in major AI related stocks in November 2025 revived worries about whether the sector was heading toward a correction. Companies involved in chips, cloud infrastructure and hyperscale computing have seen double digit drops, triggering comparisons to previous periods of overinvestment.
Spark behind the debate
Attention turned to the argument that many tech giants are understating depreciation on high end chips and servers. Extending asset life from two to three years (wrongly) creates an inflated picture of profitability and masks the true cost of rapid hardware obsolescence.
Fast aging chips
Nvidia’s move to design new AI chips every year highlights how quickly older units lose utility. Hyperscalers must constantly refresh their fleets to stay competitive. When devices become outdated sooner, companies may need to tighten their depreciation schedules, affecting reported earnings.
Corporate responses to depreciation concerns
Some firms adjusted. Amazon increased server life to boost 2024 earnings, then reversed those assumptions and accelerated depreciation on certain assets in early 2025. Such shifts signal how sensitive financials are to useful life estimates for AI infrastructure. Depreciation is non cash, but it matters because it reveals how fast companies burn value through upgrades. If hardware cycles shorten further, investors may need to reassess expectations for long term returns from aggressive AI expansion.
Summary
AI infrastructure becomes obsolete quickly, and depreciation policies significantly influence earnings. As chip cycles shorten, tech companies may face pressure to revise asset life estimates, prompting fresh scrutiny of the AI investment boom.
Food for thought
If AI hardware keeps aging faster, can the current pace of investment remain sustainable?
AI concept to learn: Depreciation in AI infrastructure
This refers to how quickly AI hardware like GPUs and servers lose value due to rapid technological upgrades. Companies must estimate useful life carefully because it shapes profitability. Beginners should understand it to see how AI economics truly works.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
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