Using ServiceNow Backups to Train AI

Using ServiceNow backups to train AI models is one of many inventive approaches organizations are employing to provide AI solutions with large amounts of quality data.

This blog post explores why ServiceNow backups in particular are useful for training AI models and the challenges organizations face when adopting the approach. 

Table of contents:

1. Why Use Backups to Train AI Models?
2. Why ServiceNow Backups In Particular?
3. Challenges to Using ServiceNow Backups to Train AI
4. How to Create ServiceNow Backups That Can Be Used to Train AI

Why Use Backups to Train AI Models?

AI solutions are only as good as the data used to train those models.

They require extensive, good quality historical datasets to accurately identify and predict trends. This means the data must be clean, error-free, and reliable.

However, collecting, processing and storing the large volumes of historical data required to train AI models is no easy feat. It takes time to generate data, resources to process and clean it up, and money to store. 

Fortunately, organizations are typically creating and storing backup data as a byproduct of their operations. And as long as they have access and control over backup data, it can be leveraged to train AI. 

In supporting and training AI solutions, backup data provides:

Rich pool of data and usable insights

ServiceNow backups are a goldmine of operational data, capturing every process, user interaction, and system update. As such, ServiceNow backups are a detailed snapshot of business data with backup versions reflecting changes over time. 

When organizations leverage these data-rich backups for AI/ML model training, they have a rich source of historical data that can be used to produce meaningful patterns and deliver accurate predictions that address real-world challenges.

Consistent, up-to-date data

Organizations that create regular backups will consistently have access to up-to-date data that effectively captures the recent changes on the platform. This ensures that AI solutions are ingesting up-to-date, relevant data. 

Backups ensure data availability 

Using backups for AI/ML model training ensures the exercise can continue even if ServiceNow experiences downtime. Training with backup data creates a stable, uninterrupted pipeline for model development and improvement, circumventing any disruptions caused by potential ServiceNow outages. 

Why ServiceNow Backups In Particular?

While ServiceNow backup data isn’t the only source of backup data available for training AI, the ITSM platform is arguably one of the more impactful sources. 

As a leader in ITSM, ServiceNow is used globally to support organizations internal and external IT services and requirements. This means for many organizations, the solution is constantly generated useful data and insight relating to service delivery, technological issues, customer and employee experience and more.

And then there’s the value of optimizing ITSM using AI Service Management (AISM). Since ITSM supports so many functions around the enterprise, it stands to reason that ITSM optimization can have a significant positive affect on the whole organization.

AISM allows organizations to pursue various use cases including:

• Enabling automated chatbots.
• Enabling auto-approvals for routine requests.
• Creating AI-driven insights for strategic decision-making.
• Supporting IT agents with information relating to open issues.
• Automating the handling and resolution of routine/simple cases without impacting IT agent’s workloads.
• Offering insight into platform usage and recommending best practices to avoid causing issues.

Challenges to Using ServiceNow Backups to Train AI

While the benefits of using ServiceNow backup data to train AI should now be plain to see, taking advantage of the idea is not so simple—at least for organizations reliant on ServiceNow’s in-built backup capabilities. 

Such organizations have very little control over the backup process and no direct access to retrieve backup data. ServiceNow exercises complete control over when ServiceNow-made backups occur, what data is backed up and how long backups are retained.

The only way to retrieve a backup is by contacting ServiceNow via their support portal and asking them to initiate an instance restore.

This rules ServiceNow’s OOTB backup capabilities out of supporting AI refinement.

How to Create ServiceNow Backups That Can Be Used to Train AI

The problem with ServiceNow backups is that the user has no control over their creation or use. This isn’t just a problem for organizations exploring the use of backups to train AI, either. In fact, lacking the ability to access and retrieve backups has other implications. 

The reliance on ServiceNow support limits recovery time. Lacking the ability to increase backup frequency or the backup retention period increases the risk of permanent data loss.

No control over the backup schedule means backup creation can occur at a time when system resources are needed elsewhere, or even conclude just before significant updates.

Fortunately, the solution to the aforementioned limitations of ServiceNow’s built-in capabilities and leveraging ServiceNow backup data to train AI, is to backup ServiceNow data externally. 

With the right, purpose-built backup solution for ServiceNow, organizations can take control of backup creation and storage, allowing them to easily access backup data on the organization’s terms.

Take Advantage of Backup-trained AI with Snapshot

And what is the right purpose-built backup solution for ServiceNow? Enter, Snapshot. 

Developed by ServiceNow’s founding developer – David Loo – Snapshot is a robust backup and restore solution that functions like a time machine for ServiceNow.

It gives users the flexibility that ServiceNow does not, allowing organizations to use backup data to support whichever initiatives they believe it can impact positively—including training AI.

With Snapshot, users can:

• Create and control their ServiceNow backup schedule.
• Create unlimited ServiceNow backups and retain them indefinitely. 
• Choose what data will be backed up (backup and restore at the object level) instead of ServiceNow’s “all or nothing” approach. 
• Backup and recover complete objects, including metadata, attachments, related records, forms, properties, lists, and schemas.
• Maintain routine ServiceNow operations during backup and restore activities with zero downtime.
• Preserves parent-child and recursive relationships when creating backups to maintain referential integrity.
• Feed backup data into third-party solutions including but not limited to AI.

Are you curious to learn more about our backup and restore solution? Talk to us!