Cloud AI vs On‑Prem AI (evaluation visual)
Cloud AI (public cloud)
- Data may egress / cross-border processing
- Governance/audit often needs extra work
- Best for: public data, low-audit tasks
On‑Prem / Private AI
- Data stays in your intranet (offline-capable)
- Reuse SSO/RBAC with audit trails
- Best for: sensitive, compliance/audit use cases
The core difference is not “which model is stronger”, but data boundary, governance accountability, and auditability:
- Data boundary (data residency): Cloud AI often implies data egress and cross-border processing; on‑prem/private deployment keeps data inside your intranet (offline-capable), reducing leakage and compliance risk.
- Access control and audits: Cloud AI is often centered on personal accounts and one-off chats; on‑prem AI can reuse SSO/RBAC and keep audit trails (who asked what, when, and based on which sources).
- Verifiability and operability: Cloud tools optimize for “usefulness”; enterprise deployment requires “governable, regression-testable, continuously improvable”.
- Contractable responsibilities: On‑prem delivery makes it easier to define data retention, audit responsibilities, operations, and boundaries in NDA/DPA and Enterprise Agreements (agreement governs).