- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
yesterday
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
yesterday
Hi,
The major differences between on-premise and cloud instances in ServiceNow regarding AI capabilities are:
1. Deployment & Updates
Cloud: AI features (like Now Assist, Predictive Intelligence, AI Search) are automatically enabled and updated by ServiceNow. You get the latest AI innovations without manual upgrades.
On-Premise: You must manually install and update AI plugins. This often involves longer delays for new features and requires internal maintenance.
2. Infrastructure & Scalability
Cloud: ServiceNow manages all AI infrastructure, including GPU resources for model training/inference. It scales automatically with usage.
On-Premise: Your organization must provision and maintain high-performance hardware (e.g., GPUs) and ensure scalability, which can be complex and costly.
3. Data Governance & Compliance
Cloud: Data is processed in ServiceNow’s secure data centers. Some organizations may have compliance requirements that restrict cloud data processing.
On-Premise: Full control over data residency and governance, which is crucial for highly regulated industries (e.g., government, defense).
4. Feature Parity
Cloud: Access to the full suite of AI services (e.g., Now Assist for ITSM, CSM, HR).
On-Premise: Not all AI features are available on-premise due to dependencies on cloud-native infrastructure or third-party integrations.
5. Integration with External AI
Cloud: Easier integration with cloud-based AI services (e.g., OpenAI, Microsoft Azure AI).
On-Premise: Integrations may require custom configurations and are often limited to on-premise-compatible APIs.
6. Total Cost of Ownership
Cloud: Subscription-based pricing with no upfront hardware costs.
On-Premise: Higher initial investment in hardware, software licenses, and dedicated AI expertise.
Recommendation:
For most organizations, the cloud offering is preferable due to its ease of use, automatic updates, and lower operational overhead. However, on-premise is viable only if data must reside locally due to strict compliance needs.
Hope this helps!
Thanks & Regards,
Muhammad Iftikhar
If my response helped, please mark it as the accepted solution so others can benefit as well.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
yesterday
Hi,
The major differences between on-premise and cloud instances in ServiceNow regarding AI capabilities are:
1. Deployment & Updates
Cloud: AI features (like Now Assist, Predictive Intelligence, AI Search) are automatically enabled and updated by ServiceNow. You get the latest AI innovations without manual upgrades.
On-Premise: You must manually install and update AI plugins. This often involves longer delays for new features and requires internal maintenance.
2. Infrastructure & Scalability
Cloud: ServiceNow manages all AI infrastructure, including GPU resources for model training/inference. It scales automatically with usage.
On-Premise: Your organization must provision and maintain high-performance hardware (e.g., GPUs) and ensure scalability, which can be complex and costly.
3. Data Governance & Compliance
Cloud: Data is processed in ServiceNow’s secure data centers. Some organizations may have compliance requirements that restrict cloud data processing.
On-Premise: Full control over data residency and governance, which is crucial for highly regulated industries (e.g., government, defense).
4. Feature Parity
Cloud: Access to the full suite of AI services (e.g., Now Assist for ITSM, CSM, HR).
On-Premise: Not all AI features are available on-premise due to dependencies on cloud-native infrastructure or third-party integrations.
5. Integration with External AI
Cloud: Easier integration with cloud-based AI services (e.g., OpenAI, Microsoft Azure AI).
On-Premise: Integrations may require custom configurations and are often limited to on-premise-compatible APIs.
6. Total Cost of Ownership
Cloud: Subscription-based pricing with no upfront hardware costs.
On-Premise: Higher initial investment in hardware, software licenses, and dedicated AI expertise.
Recommendation:
For most organizations, the cloud offering is preferable due to its ease of use, automatic updates, and lower operational overhead. However, on-premise is viable only if data must reside locally due to strict compliance needs.
Hope this helps!
Thanks & Regards,
Muhammad Iftikhar
If my response helped, please mark it as the accepted solution so others can benefit as well.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
12 hours ago
Hi and thanks for the rapid respons 🙂
Do you also now status on AI Control Tower, Now Assist and AI Agent Fabric is availible on-premise?
Thanks
Kent
