---
sourceDocument: Xanadu IT Service Management
sourceDocumentLink: https://www.servicenow.com/docs/r/xanadu/it-service-management

 Release :

    - xanadu

ft:locale :

    - en-US

ft:publication_title :

    - Xanadu IT Service Management

ft:clusterId :

    - itsm

bundleId :

    - itsm

workflow :

    - Technology


---

# ITSM Predictive Intelligence Workbench implementation

# ITSM Predictive Intelligence Workbench implementation {#ariaid-title1}

* Release version: Xanadu
* 
* Updated August 1, 2024
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read

Use machine learning to optimize your business processes. You can train and implement
ITSM Predictive Intelligence Workbench use case models to augment your existing
application workflows.  
Important:  
Starting with the Xanadu release, ITSM Predictive Intelligence Workbench is being prepared for future deprecation. It will be completed deprecated and will no longer be supported from the Yokohama release. To get the
latest experience for this functionality, you must install the Task Intelligence for ITSM application (com.snc.itsm_ml_task) plugin. For more information, see [Task Intelligence for ITSM](https://www.servicenow.com/docs/II8kAMUdIE1Wa3OLDkDftw "ServiceNow Task Intelligence for ITSM uses machine learning to set up, deploy, and track solution-based models to achieve important business outcomes.")

For details, see the [Deprecation Process \[KB0867184\]](https://support.servicenow.com/kb?id=kb_article_view&sysparm_article=KB0867184) article in the Now Support
Knowledge Base.

## Explore use case templates {#itsm-piwb-implementation-guidance__section_i2r_wcv_mlb}

Users with the piwb_admin or piwb_manager role can explore the prebuilt use case templates and
create predictive machine learning models. To create a machine learning model, you first select
a prebuilt use case template. Some of the prebuilt templates are guided and display the
Guided Setup flag. These templates include a comprehensive setup process
to help ease you through implementation. Non-guided templates display the Classic Setup flag.  
Figure 1. ITSM Predictive Intelligence Workbench guided use case template  
Figure 2. ITSM Predictive Intelligence Workbench classic setup use case template

Templates with available pretrained models accelerate your setup process, by providing a
pre-generated model based on your data. When a template indicates
Pretrained, this means you can go directly to the evaluation phase of
the use case setup. If the pretrained model is acceptable, you can directly integrate it with
your business processes. Otherwise, you can tune this model or create another model. You may
change the name and description of the use case later. Pretrained models display the estimated
percentage of your correctly predicted incidents.

Templates with available pretrained models also display the estimated percentage of the
correctly predicted incidents. If the pretrained model is acceptable, you can directly integrate
it with your business processes. Otherwise, you can tune this model or create another model. You
may change the name and description of the use case later. Pretrained models display the
estimated percentage of your correctly predicted incidents.  
Figure 3. ITSM Predictive Intelligence Workbench pretrained model use case template

Non-guided, Classic Setup templates provide links to relevant Predictive Intelligence Workbench product documentation or link to the ServiceNow platform Predictive Intelligence application with the
Take me therebutton.  
Figure 4. ITSM Predictive Intelligence Workbench links to product documentation and Predictive Intelligence product documentation

## Use case creation phases {#itsm-piwb-implementation-guidance__section_elz_xdv_mlb}

Creating a predictive machine learning model involves several phases. After you create and train your model you need to evaluate and tune it, test its prediction results, and then integrate it with your business process. Use case model creation phases include:

* Create and train models: Define parameters to create a model that you will train based on your unique data. It is common to create multiple models in this phase. You will tune and refine your models by defining the right combination of coverage and precision to use.
* Test your models: Get prediction results from your models to decide which one is best to integrate with your business process. To see if a model returns a correct result, you can use either the single or batch testing process.
* Integrate the best model: Deploy the best model into your business process. After you determine which model returns the best, correct result, integrate it into production.  
  Note:  
  For details regarding trained use case integration implementation, refer to [Predictive Intelligence Workbench integration and customization](https://www.servicenow.com/docs/ouimcQ4YcdMwsTSE8gfU8g "Predictive Intelligence Workbench uses scripted extension points to integrate a trained use case model for prediction.").
{#itsm-piwb-implementation-guidance__ul_pfz_vhv_mlb}