The AI hardware market is challenging one of the oldest assumptions in enterprise IT:
Older hardware should always become less valuable over time.
That assumption still works for many traditional servers and components.
But AI infrastructure is different.
In 2026, demand for GPU compute remains so strong that older accelerators can continue generating meaningful economic value long after newer generations enter the market.
A recent Oracle update provides a strong example.
Oracle reported that demand for AI training and inference continues to grow faster than available supply. Since the end of the previous quarter, the company added more than 300,000 GPUs for customers and signed more than $30 billion in new AI cloud contracts. Source: Oracle Q1 FY2027 Results
More importantly, Oracle disclosed that GPU fleet utilization reached approximately 97.9%.
And when existing GPU capacity came off contract, it was not sitting idle.
According to management commentary, that capacity was either renewed or resold at roughly 20% higher pricing, even though most of those GPUs were already four years old or more.
That does not mean every four-year-old GPU is suddenly worth 20% more.
But it does tell us something important about the AI infrastructure market:
depreciation of hardware does not necessarily mean depreciation of earning capacity.