Running on-premise in an agentic world
The business case for running things on-premise has always started with control.
Host it yourself, keep the data in your environment, avoid vendor lock-in. It's a reasonable instinct, and for a long time it was a reasonable answer.
The gap between what you could run internally and what was available externally was manageable. On-premise was a defensible choice.
AI is changing that.
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, the upgrade cycles that never quite arrive on schedule, and the work required to unpick decisions made against a technology landscape that looked completely different six months ago.
None of these costs are hidden, exactly. They're just easy to ignore when the initial business case is about build cost.
You can run AI on-premise - just...
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