Increasingly, organizations are seeking to take advantage of artificial intelligence (AI) and machine learning (ML) in their ITSM initiatives, in an approach dubbed “AI Service Management” (AISM).

But what is AISM? What are its benefits? And how can organizations take advantage of AISM?

Table of contents:

AISM Explained

What is AI Service Management (AISM)?

AI Service Management (AISM) is an approach to IT Service Management (ITSM) that utilizes AI and ML to improve the outcomes of ITSM and IT Service delivery.

How Does AISM Work?

In AISM, AI and ML utilizes available data to iteratively “learn” by identifying patterns, enabling it to make predictions and/or provide contextually appropriate insight or information.

What ITSM Solutions Are Capable of AISM?

Many of the leading ITSM providers including ServiceNow are introducing AI capabilities into their platforms. This means many organizations that have invested in ITSM can already take advantage of some AISM capabilities.

However, to get maximum value from an AISM initiative, organizations should consider integrating their ITSM platform with purpose-built AI and AISM solutions, and other AI-ready solutions and repositories such as Snowflake to name just one example.

What is the Value of AISM?

In AISM, AI and ML have immense potential in utilizing historical data to make forward predictions and optimize systems and processes related to ITSM.

This is partly due to ITSM solutions being an excellent source of valuable enterprise and customer data, meaning AI solutions have a useful pool of data to learn from.

ITSM plays a critical role in modern organizations, encompassing the various processes that support the IT service delivery that many organizations rely on.

Due to the importance of ITSM, introducing new ways to leverage ITSM data and increase the efficiency and quality of IT service delivery can drastically impact an organization’s operations and profit. 

As such, the potential value of AISM for organizations equipped to take advantage of it is huge.

AI Service Management (AISM) Use Cases

AI and ML algorithms, natural language processing (NLP), and virtual assistants are reshaping and redefining ITSM by automating workflows, promoting data-driven decision-making, and improving user interactions. 

We can categorize the application of AISM into two primary areas:

  • AI Experiences, created by AI-powered solutions that operate independently with zero human intervention.
  • Contextual AI analyzes data to provide contextual insights for enhancing user experience, streamlining processes, and eliminating performance bottlenecks.

Real world examples of AISM use cases include: 

AI & IT Agent

IT agents usually handle an overwhelming number of routine tasks, including software upgrades and maintenance, ticket assignments, troubleshooting, etc.

AI experiences can supplement the output of IT agents by automating routine/simple issues via AI-enabled workflows. This helps free IT agents’ time, allowing them to focus on more complex issues that require human input. 

Contextual AI can support IT agents with information relating to the open issue such as similar, past issues and their resolution notes. 

AI & End User

AI experiences can support end-users without human intervention, meaning that cases can be resolved without impacting IT agent’s workloads. 

One such example of an AI experience that can benefit the end-user is an automated chatbot. 

For straightforward queries and issues, there may be enough historical, contextual information for AI-generated insight to suggest a solution the end-user can apply.

This could also apply to auto-approvals, whereby routine requests for service items can be handled by AI to reduce the administrative burden on IT agents and speed up resolution times. 

Contextual AI can also be used to support the end-user. For example, contextual AI could offer insight into a user’s platform usage and recommend best practices that would avoid causing new issues, such as recommending creating a backup after a significant system or database change.

AI & Management

ITSM involves managing various IT aspects, including asset management, incident management, service level management, request fulfillment, and problem management, to name a few.

Needless to say, it is challenging to manage and streamline all these aspects while ensuring minimal technical glitches. 

AI in ITSM can improve workflows and processes to help IT managers and decision-makers.

Workflow optimization and automation make everyday operations more efficient and agile, whereas AI-powered root cause analysis can help identify and resolve underlying issues quickly.

Business leaders can leverage AI-driven insights for strategic decision-making.

Benefits of AISM

There are many benefits of AI and ML in ITSM, including:

Data management

AI algorithms can sift through large datasets to identify errors, redundancies, and inconsistencies. This improves data reliability and accuracy, saving valuable time for IT teams and streamlining data management.

Data security

AI and ML tools continuously analyze vast data volumes to glean insights and identify anomalies and suspicious activities (such as unusual login attempts, malware infections, etc.) that human agents might overlook.

Further, they can automate threat detection and response, allowing IT teams to proactively address vulnerabilities and protect business-critical data.

IT support 

IT professionals cannot operate 24/7. They can only focus on one or two tasks at any given point. In contrast, AI-powered bots can assist multiple customers simultaneously, at any time and from anywhere, thus, improving IT support output. 

These tools can handle routine support requests while also escalating complex problems to human agents. Essentially, the support team can accomplish more work in less time and focus more on value-added activities. 

Customer experience 

As AI in IT Service Management delivers quicker resolution times and a more consistent user experience, it improves end-user satisfaction. 

Additionally, AI/ML tools allow IT teams to take a proactive stance in identifying potential incidents, mitigating minor issues affecting customer satisfaction, and improving IT processes and performance. 

Return on investment 

AI in ITSM equips IT agents with the right tools, boosting their productivity and reducing their efforts on routine tasks. 

Faster resolution times, proactive issue prediction that minimizes downtime, and shortened development cycles improve overall performance and boost the organization’s ROI. 

Replicating and Integrating ITSM Data to Enable AISM

To take full advantage of AISM, organizations need an integration solution to consistently transfer large volumes of ITSM data into their AI solutions. But not just any integration solution will do. 

Throughput, data quality and security capabilities – among others – should all be considered when evaluating an ITSM-to-AI integration solution.


The faster an integration solution can transfer large amounts of data into the desired AI/ML solution, the quicker AI can learn from the data. It is also important that the regularity, rate and/or volume of data transfer does not impede the performance of the ITSM platform.

Data Quality

Data being fed into the AI/ML solution must be of high quality to ensure the solution is learning from reliable and accurate datasets. 


ITSM data – particularly customer data – is often sensitive and subject to strict regulations. As such, the integration tool must facilitate the secure transfer of data.

How Perspectium Enables AISM for ServiceNow Users

Perspectium is a ServiceNow-native data replication and integration-as-a-service (IaaS) solution, specializing in high-throughput data replication and transfer. 

Designed by ServiceNow’s founding developer, David Loo, Perspectium was purpose-built to overcome the common challenges associated with extracting data from ServiceNow, including performance bottlenecks and data extraction limits.

Perspectium’s DataSync application is ideal for ServiceNow users keen to take advantage of AISM. The application does not require performance degrading external API calls to initiate data transfers, and instead, it is installed directly within the ServiceNow platform. 

This allows DataSync to use efficient push technology to transfer data for secure, high throughput data transfers, enabling users to extract and replicate over 20 million ServiceNow records daily, without impacting the Platform’s performance. 

As well as AI and ML in ITSM, DataSync’s high-throughput capabilities make the solution ideal for various use cases including reporting, analytics, business intelligence and more.

Do you want to learn more about implementing AI in ITSM for your organization? Talk to us!

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