- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
3 weeks ago
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
3 weeks ago
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.
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
3 weeks ago
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.
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
3 weeks 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
