Enhancing ITSM, ESM, and Employee Experience through AI Capabilities

Posted by Marbenz Antonio on October 26, 2023

Understanding how artificial intelligence (AI) can positively impact your organization’s IT service management (ITSM) operations and outcomes is crucial. It’s important to discern not just what seems beneficial but what truly aligns with your organization’s needs. This blog aims to explore the ways AI can enhance ITSM and enterprise service management (ESM) operations and outcomes, beginning with an examination of the associated benefits.

The High-Level Benefits of AI Adoption in ITSM and ESM

When evaluating the advantages of AI, it’s crucial to recognize its role in both generating insights and executing actions. Consequently, the conventional benefits associated with standard automation are extended to what can be termed “intelligent automation.” AI enhances the benefits of conventional automation, encompassing the trifecta of “better, faster, cheaper,” by providing superior data-driven insights and enhanced experiences within various ITSM and ESM use cases.

Some benefits within the realms of ITSM and ESM include:

  • Operational Efficiency Gains – in instances where the technology lessens the workloads of IT personnel, it allows individuals to dedicate their time to more valuable tasks. The heightened speed additionally has a positive effect on employee experiences and mitigates lost productivity.
  • Improved Employee Experiences – accelerated operations and AI-powered capabilities, like chatbots and virtual assistants, enhance employee experiences across various service providers.
  • Reduced Operational Disruption – quicker issue resolution, preventive problem management and maintenance, self-healing capabilities (for IT), and decreased human error all contribute to this benefit, further enhancing employee experiences and reducing lost productivity.
  • Cost Reduction – Automation, more efficient resource utilization, proactive problem management, and improvement initiatives all contribute to cost savings.
  • Data-informed decision-making – This includes strategic decision-making, capacity planning, demand forecasting, and improvement identification. Better decisions can positively impact all of the above benefits, including the employee experience.
  • The ease of scalability – AI-enabled capabilities help organizations to grow, cope with skill shortages, and better adapt to internally and externally driven change.
  • Improved perceptions of the service provider’s operations and outcomes – based on the cumulative effect of the aforementioned benefits.

The Common ITSM and ESM AI Use Cases

AI is already being used in ITSM tools to improve service provider operations and outcomes, speeding up activities and removing the reliance on manual effort (and its limitations). Examples of ITSM and ESM AI use cases include:

  • Process Automation – which speeds up operations, improves experiences, and frees up personnel to focus on other tasks and issues. For instance, incident ticket categorization and routing, accurately classifying (or categorizing) incidents and routing them. This IT example also applies to other corporate service providers such as Human Resources (HR), Facilities, or any other business function that handles employee or third-party requests for help, information, service, or change. This AI-enabled process automation can also include automated provisioning or issue resolution.
  • Virtual Assistants and Chatbots – which help both service provider staff and the people they serve. For example, providing knowledge in context, answering common questions, guiding people through troubleshooting steps, or automating routine tasks. This accelerates operations, enhances experiences, and liberates service provider personnel.
  • Knowledge Management Improvements – which include analyzing past incidents and solutions to create new knowledge articles, suggesting new articles to fill knowledge gaps, and delivering knowledge to individuals when necessary. This AI enablement enhances the service provider’s knowledge management capabilities, operations, and associated employee experiences.
  • Experience Personalization – For example, AI can personalize the content and layout of self-service portals based on employee preferences and behavioral data, thereby enhancing the employee experience.
  • Advanced Analytics Capabilities – that improve service delivery and the associated outcomes and experiences, such as:
  • Predictive Analytics – where serious IT issues are predicted using historical data and patterns, and addressed before adversely impacting business operations.
  • Root Cause Analysis – where data sources such as performance metrics, configuration data, and log files are used to identify the root causes of problems.
  • Demand Forecasting – where historical patterns and trends are used to predict IT demand.
  • Continual Improvement – where analyzing patterns, trends, and correlations in ITSM data can highlight issues and opportunities.
  • Risk Analysis – For example, with change enablement, AI can analyze historical change data to predict the risks associated with a proposed change (and the expected impact of a change).
  • Asset Optimization – analyzing asset usage patterns to recommend revised IT asset allocation and cost reductions.
  • Sentiment Analysis – to gauge customer satisfaction and improve services in the right places.

The Impact of Generative AI Technologies on ITSM and ESM

The above list covers many of the AI-enabled capabilities already seen in ITSM tools. But there is a new entrant in the AI arena with the sudden surge in interest in ChatGPT and other generative AI tools. The potential of generative AI for ITSM and ESM will be discussed in upcoming SysAid blog posts, including the advantages and disadvantages of its utilization.

If you have any queries about the currently accessible AI-enabled ITSM and ESM capabilities or the ChatGPT phenomenon that the IT industry is currently witnessing, please feel free to share in the comments section below.


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