R0042/2026-04-01/Q001/SRC02/E01¶
Structured comparison of on-premises AI advantages and enterprise motivations
Extract¶
The guide identifies the following on-premises AI advantages:
-
Security & Data Protection: "highest security; data on wholly owned, dedicated, or controlled equipment." Prevents "sensitive enterprise data from being used to train public LLMs." Cites Deloitte survey: "55% of enterprises avoid at least some AI use cases due to data security concerns."
-
Customization & Accuracy: Enables organizations to "tailor the AI solution to the specifics of the industry, enterprise, and teams." Achieves "highest accuracy as LLM and RAG can be specifically trained on business-specific data."
-
Cost Advantages at Scale: Asset capitalization and depreciation benefits unavailable with cloud pay-as-you-go models. Lower variable transactional costs for high-volume usage. Reduced costs for terabyte-scale data training compared to cloud.
-
Performance & Control: "No dependence on internet connectivity" and "lowest latency" for real-time applications.
The guide states on-premises aligns with organizations prioritizing "security, compliance, customization, and large data amounts," particularly in regulated sectors like finance, healthcare, and energy.
Relevance to Hypotheses¶
| Hypothesis | Relationship | Strength |
|---|---|---|
| H1 | N/A | Not a survey ranking; a vendor analysis |
| H2 | Supports | Documents a motivation set that overlaps with but differs from other sources |
| H3 | Contradicts | Substantial documented motivations exist |
Context¶
The 55% Deloitte statistic is one of the most specific quantitative data points found across all sources for enterprise avoidance of AI due to security concerns. This statistic bridges the security motivation to measurable enterprise behavior.
Notes¶
Vendor bias noted — Allganize sells on-premises solutions. However, the structured analysis and cited statistics are independently verifiable.