How Does AI in ITSM Enhance Service Management?

There’s a lot of media hype around artificial intelligence (AI), especially on the back of the buzz created by generative AI tools such as ChatGPT. However, this hype shouldn’t overshadow the AI-enabled capabilities already added to IT service management (ITSM) tools, including the use of generative AI. Especially the capabilities that improve ITSM process efficiency and effectiveness in line with the automation mantra of  “better, faster, cheaper” operations and outcomes. 

This blog looks at some specific ways that AI-enabled capabilities have been introduced to ITSM tools, taking a process-based perspective. But first, here’s some benefits-focused scene setting.

This @SysAid blog looks at some specific ways that AI-enabled capabilities have been introduced to ITSM tools, taking a process-based perspective. #AI #ITSM #ArtificialIntelligence Share on X

The Benefits of AI in ITSM

The potential benefits of AI for ITSM include:

• Improved service experiences including personalization, with AI able to provide personalized engagements to end-users based on their profile, including past interactions and preferences.
• Improved operational efficiency and speed, with AI automating routine ITSM tasks. This includes improved Level 0 support capabilities via AI-powered chatbots and virtual assistants that can handle basic inquiries and support requests.
• Cost reduction, which includes labor savings and a reduction in the costs related to service downtime.
• Enhanced decision-making because AI technologies such as machine learning can analyze large data sets to identify patterns and trends that inform better decisions. This includes better planning, with AI predicting future demand for IT resources and allocating resources optimally.
• Proactivity, including with problem-solving capabilities, because AI can predict potential issues before they occur by analyzing system performance data.
• Enhanced IT security by identifying and responding to security threats more quickly and efficiently than humans can.

Examples of ITSM processes that are helped by AI

Given that ITSM processes all involve workflows, some form of analysis, and a focus on improvement, it could be argued that all are open to AI-based enhancement. However, some of the most commonly adopted ITSM processes, where ITSM tool vendors have added AI-enabled capabilities, are:

This @SysAid blog shares examples of #ITSM processes that are helped by Artificial Intelligence. #AI #ArtificialIntelligence Share on X

• Incident management – where AI can automatically categorize and route incidents to the most appropriate team. If possible, an automated resolution can be applied to the incoming ticket without human involvement. Machine learning models can also analyze historical data to predict and prevent incidents before they occur.
• Service request management – AI-powered chatbots, or bots in collaborative tools like Slack and Microsoft Teams, can interact with end-users to understand their needs. Either resolving them or escalating them to human agents when needed. Simple service requests such as password resets can be actioned automatically. 
• Problem management – AI can help identify the underlying root causes of recurring incidents by analyzing historical data. It can also analyze trends and logs to detect underlying problems that might not be immediately obvious to human eyes.
• Change management (change enablement in ITIL 4) – AI can evaluate the potential impact and risk of proposed changes. AI-driven automation tools can perform pre- and post-implementation testing to help ensure safe and effective changes.
• Knowledge management – AI can help keep the knowledge base updated by suggesting new articles based on recent incidents and problems or “knowledge gaps” when new service desk tickets are compared to existing knowledge articles. AI can also personalize the knowledge content that ITSM tools show to end-users based on their past queries and preferences.
• Service configuration management – AI can automate the discovery of IT assets and their configurations to keep the configuration management database (CMDB) up-to-date. It can also detect configuration anomalies related to security risks or operational inefficiencies.
• Capacity and performance management – AI can forecast future resource requirements based on historical trends and usage patterns. It can also suggest the optimal deployment of resources to maximize efficiency and cost savings.
• Asset management – AI can predict when IT assets might fail or require maintenance. It can also analyze historical usage patterns to optimize the allocation and utilization of assets.
• Security management – AI can monitor networks for unusual activity, quickly identifying and responding to potential security threats. It can also continuously scan the IT infrastructure for vulnerabilities, prioritizing their remediation based on potential impact.

Extending AI-enabled ITSM capabilities to other business functions

In the same way that enterprise service management (ESM) approaches extend ITSM processes and ITSM tool capabilities to other business functions – such as human resources (HR), facilities, finance, and legal – the same is true for AI capabilities. This includes the capabilities where AI is used to improve ITSM processes.

'If AI improves IT operations and outcomes, it can do the same for other business functions.' Find out more in this blog. #AI #ArtificialIntelligence #ITSM Share on X

In fact, the speed with which new technologies and capabilities are brought into ITSM tools can be considered a key differentiator for both ITSM and ESM needs. If AI improves IT operations and outcomes, it can do the same for other business functions. For example, automated ticket triage capabilities (that categorize and route incoming tickets based on historical data patterns) can be used in almost every other service-provider business function to improve process execution. Because, for example, the AI can know what an HR request means and how to respond, it can also provide the best resolution without human intervention.

There are also many other possible ESM use cases of AI-enabled ITSM tool capabilities that can benefit other business functions. For example: 

• Providing automated recommendations to service-provider staff “in workflow” 
• Automatically escalating tickets (or whatever the business function name is) when a service-level breach is likely
• AI chatbot capabilities that converse with employees to understand their needs and to offer the best solution (including transfer to a human when needed).

If you want to learn more about how AI improves ITSM and ESM processes, take a look here.