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What are the major differences between on-premise and cloud instance when it comes to AI

kentnilsson
Kilo Contributor
 
1 ACCEPTED SOLUTION

Community Alums
Not applicable

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.

View solution in original post

2 REPLIES 2

Community Alums
Not applicable

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.

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