Why on-premise AI infrastructure is becoming unsustainable
By
Rob Gates
Summary
The article argues that the traditional business case for on-premise infrastructure — centered on control, data security, and avoiding vendor lock-in — is becoming untenable in the age of AI. It contends that the costs of keeping on-premise AI systems updated (people, licenses, compute) quickly outweigh the benefits, and that the gap between internal capabilities and external AI services is widening. The piece ultimately makes the case that running AI on-premise is increasingly costly, slow, and prone to rapid obsolescence.
Source
bskyWhy on-premise AI infrastructure is becoming unsustainabletechradar.comKey quotes
· 3 pulledThe business case for running things on-premise has always started with control.
The build-it-yourself case ignores almost everything that comes after: the people required to keep things running as AI models evolve, the license fees and compute costs that compound as the landscape shifts.
On-prem AI is costly, slow, and quickly outdated.
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