AI for ITSM | 5 Use Cases and Examples

Jul 16, 2025 by Ronan McQuillan

For IT teams, there’s a particular urgency about adopting AI solutions. Indeed, ITSM is one of the use cases where some of the most effective solutions for implementing AI have come to market.

Today, we’re exploring the role of AI in ITSM in 2025, including checking out some practical use cases and examples that we can implement today.

Specifically, we’ll be covering:

What is AI for ITSM?

Implementing AI for ITSM largely means designing LLM-powered systems that can replicate and augment tasks that would otherwise rely entirely on human service agents.

These tasks range from very simple, deterministic workflows, like password resets, to more complex, context-dependent tasks, like investigating incidents.

Therefore, AI is often used as part of our efforts to automate ITSM workflows, with the overarching goals of providing better outcomes more efficiently.

Types of AI solutions

Some of the most common types of AI solutions for ITSM teams include:

  • Monitoring, detection, and predictive analytics - including detecting events or anomalies that can trigger ITSM workflows.
  • Intelligent routing - determining which agent, queue, or workflow a request should be routed to.
  • Ticket triage - identifying the related CIs and relative priority of a ticket based on established business rules.
  • AI actions within traditional workflow automations - using LLM-based tools to carry out specific actions within a workflow.
  • Chatbots - interactive tools that can direct users to relevant tools to self-serve.
  • Content and response generation - leveraging LLMs to generate responses to end-user queries.

Benefits and challenges

A high level of almost all AI ITSM solutions seek to achieve the following benefits:

  • Increased productivity - enabling human service agents to focus on more productive tasks.
  • Faster resolution times - resolving routine issues automatically.
  • Improved knowledge management - making knowledge articles more relevant and accurate.
  • Lower costs - reducing the labor hours required to deliver services.

However, implementing AI solutions can be a large undertaking, which is often fraught with potential challenges, including:

  • Upfront costs - needing to account for the upfront costs of developing and deploying AI ITSM solutions.
  • Technical skills and resources - many teams might require additional technical skills and resources to develop solutions.
  • Resistance to change - facing resistance from internal stakeholders when adopting AI.

5 AI ITSM use cases

Now that we have a strong grasp of AI for ITSM, we can start to think about how we’d go about implementing some of the most common use cases.

The specific examples and use cases we’re going to discuss are:

  1. Ticket triage
  2. Incident categorization
  3. Translation
  4. Change request summarization
  5. Response generation

1. Ticket triage

Ticket triage is the process of using defined business rules to determine the category and priority level of incoming submissions.

For this, we’ll use Budibase’s AI Column, starting with a lightweight tickets table in our database that contains Title, Description, and Status.

Next,

You are an IT ticket triage assistant.

{{ Title }} and {{ Description }} are the details of a new ticket.

Use this information to determine a Category for the ticket.

Possible Categories are Hardware, Software, Network, Security, Other

Then, provide a Priority for the ticket.

Options are Low, Medium, High, Emergency.

The priority should be based on the number of users affected and the likely impact of the issue described.

Return this information as a JSON object in the following format:

{
"Category": "Hardware",
"Priority": "Low"
}

2. Incident categorization

For this use case, we have a database table with Title, Description, and Status. We’ll add an AI Column, this time calling it Category and choosing Categorise Text as our operation.

We’ll add the following categories as comma-separated values - Hardware, Software, Network, Security, Data Breach, Account, Configuration Error, and Other.

3. Translation

In this case, we want to provide coverage for users across the organization in multilingual service requests.

We’ll configure this so that tickets can be submitted in any language, and they’ll be automatically translated into English.

4. Change request summarization

We can save huge amounts of time by furnishing IT colleagues with key facts in assessing and interpreting requests.

5. Response generation

One of the most exciting AI use cases for ITSM is response generation. By automating this process, we can significantly reduce the workload involved.

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