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AI in ITSM reshapes operations practices and tasks

AI capabilities are merging within ITSM practices to augment IT's performance and enhance the user experience. Read on to learn more about AI uses for ITSM, and how to approach them.

IT organizations are under pressure to provide real-time, on-demand support for the growing digital economy, with remote, global access becoming the norm. They face the task with both limited budgets and IT staff.

The use of AI-enabled IT service management (ITSM) tools has great potential to address these problems and more. AI functionality is poised to be a game-changer in the ITSM world. But before exploring the possibilities for AI in ITSM, it's important to first understand what AI is -- and what it is not.

Artificial intelligence is technology that emulates human performance or augments human resources. While automation is a major capability of AI, the technology must go beyond that.

AI requires the application of analytics and logic to interpret input and make decisions about it. People already interact with AI on a daily basis, whether it's through a voice-activated interface or browser advertisements tailored for them. 

But what can AI do for an organization? Here are just three examples:

  • Augment human resources. AI technologies can take over tedious or repetitive activities, freeing up time for people to do more value-added work.
  • Make large data sets understandable and meaningful. Organizations have access to large sets of data from multiple, disparate sources, located both on and off premises. With AI technologies, companies can better collect and consolidate -- and take actions based upon -- this data.
  • Enhance and personalize the user experience. The user experience is one of the key differentiating factors of modern organizations. By learning user preferences and behaviors, AI can help deliver that differentiated experience that customers have come to expect.

AI comes to ITSM

An effective ITSM implementation helps organizations achieve their business goals and realize value from their investment in and use of IT. But as the realities of the digital economy take root, it is becoming more challenging to sustain and make the best of these ITSM implementations.

The successful introduction of AI in ITSM depends on first establishing a solid foundation.

IT systems generate huge amounts of data and information, which typical ITSM implementations and staff are ill-equipped to handle. ITSM admins struggle with how to use that information for continual improvement. They usually make decisions based only on a limited view of a small subset of information that their tools and systems can capture.

Another challenge of traditional ITSM is ensuring that practitioners and consumers always have current, accurate and relevant information. Knowledge articles can become stale or irrelevant; new services emerge while other services retire; and the rate of change that organizations, and the IT departments that support those organizations, face continues to increase.

Understanding any relationships or potential patterns between seemingly disparate sources of data is also a significant obstacle. IT systems are becoming more complex, with critical components of those systems in multiple locations. However, admins must be able to manage each of those components in a consistent fashion, regardless of location, and having the access and ability to interpret system information is more critical now than ever.

What AI is not

AI cannot replace the human expertise and involvement required, for example, to develop a strategy, define plans or manage a budget. AI technologies are not able to make moral judgments and are inadvertently vulnerable to any biases of those who develop and create them. And it will only do what admins program it to do.

Companies should not look at AI in ITSM or other fields as a replacement for human resources. While AI-enabled tools can replace some human-performed tasks, the aim of AI adoption should be to augment and enable people, not eliminate their jobs. 

AI encompasses many technologies

These technologies can be found in AI-enabled ITSM tools:

  • Chatbots are computer programs designed to simulate conversation with human users over the internet. Chatbots are rules-based, and their interactions occur through some type of chat interface, like a messaging app. Sometimes AI is built into the program, which allows the chatbot to learn from previous interactions.
  • Virtual agents are computer-generated, animated, AI-enabled virtual characters that typically serve as online service desk agents.
  • Automation performs a procedure through the use of technology with minimal human involvement. It may be as simple as a script that executes at some regular interval or in response to the detection of some condition. AI technologies can find situations where automation would be valuable.
  • Robotic process automation (RPA) technology uses software robots to mimic a human worker. Business rules or logic and structured inputs govern automation routines. RPA may utilize AI to help the bot improve automation and adapt to exceptions and new situations.
  • Machine learning algorithms receive input data and use statistical analysis techniques to predict an output, while updating output predictions as new data becomes available. Machine learning enables computers to act without explicitly being programmed to do so.
  • Natural language processing (NLP) enables computers to learn, process and communicate through the interpretation of human speech.
  • Cognitive computing uses models to simulate the human thought process to resolve complex situations that often include ambiguous and uncertain variables. Cognitive computing features self-learning technologies, pattern recognition algorithms and NLP.

Uses of AI in ITSM practices

Emerging uses of AI in ITSM platforms focus on augmenting human work and tasks. Here are just a few ways ITSM tools use AI technologies:

  • respond to and remediate defined issues;
  • categorize and route incidents;
  • identify and correlate patterns from large data sets gathered from IT systems for event management and IT performance optimization;
  • intelligent alerting and reporting based on data filtering and correlation capabilities;
  • predictive analytics to resolve IT problems before they affect users; and
  • on-demand self-help to serve up relevant knowledge base content to resolve user issues and questions.

Introducing AI-enabled ITSM to your organization

The successful introduction of AI in ITSM depends on first establishing a solid foundation.

Ensure that there are solid, repeatable and consistent processes in IT operations, including appropriate measures to deal with issues, and error-path procedures. Without these defined processes in place, efforts to introduce AI-enabled ITSM tools will struggle at best.

Identify areas where AI can intervene, such as tedious or repetitious work. Addressing these most noticeable issues first provides for some quick return on investment and also frees up people's time to work on other areas that may benefit from the introduction of AI-enabled ITSM tools.

Take an adaptive approach to implementation; conduct small experiments regarding the use of AI in ITSM functionality. This will help the organization identify where there are higher probabilities of success and teach the organization what to expect from AI, and thus how to approach further opportunities.

To fully exploit the possibilities of AI-enabled ITSM tools, provide adequate training to appropriate team members. 

Editor's note: With extensive research into the ITSM tool market, TechTarget editors have focused this series of articles on vendors with considerable market presence and that offer ITSM tools with AI functionalities that can be classified as responsive, proactive, predictive and autonomous. Our research included Gartner, Forrester Research and TechTarget surveys.

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