What you give up
Being clear about this is more useful than pretending the tradeoffs away.
Vendor support is limited to what you can describe. No remote session, no telemetry, no logs uploaded. Diagnostics happen over the phone or through exported bundles, and the quality of support depends on the quality of your own instrumentation.
Diagnosis is slower. In a connected deployment, an engineer can reproduce a problem against the same version. In an air-gapped one, they cannot see your environment at all.
Security patching is delayed. The gap between a vulnerability being published and a patch reaching a disconnected network is measured in weeks, and it is the strongest argument for maintaining a strict internal change process to compensate.
AI features need local infrastructure. An assistant that calls an external model endpoint will not work. Inference has to run inside the boundary, which means GPU capacity, a locally hosted model, and the operational responsibility for it. Our AI agents article covers what to configure; in this environment, the inference target is not a choice between vendors but a decision about local capacity.