Artificial Intelligence (AI) offers many exciting opportunities for business, but how will it affect IT service management. Marcel Shaw, federal sales engineer for Ivanti explains.

Artificial Intelligence (AI) will dramatically improve technology in our homes and in the workplace. As AI infiltrates our corporate and government networks, IT Service Management (ITSM) organisations will be burdened with the responsibility to keep these systems up and running, but it will also allow the enterprise to give end users a higher level of customer service at every level of the interaction with the service desk.

We should expect AI technology to impact ITSM offerings in three key areas:

  • Point of Entry (incident/request creation)
  • Automated backend processes
  • Knowledge management

I’ll spend the rest of this article going into more detail about the evolution of these processes:

Point of Entry (incident/request creation)
Automated ITSM processes are designed to work when information provided is accurate. I remember working with an organisation that provided a self-service portal for requests and incidents. The online form that the end-users were required to fill out asked if they were making a request or asking for help, which then determined the backend process. Unfortunately, many requests turned out to be incidents, and vice versa. As a result, the end-user experience was negatively affected as requests and incidents were delayed or lost. 

Until these types of challenges are resolved, ITSM will continue to rely on human frontline analysts. This is because they fear they might spend more time and money correcting errors caused by miscommunication from an inefficient system than they would spend on supporting the end user directly.

Adding AI technology to chatbots will enable automated ITSM solutions with the capability to interpret incidents and requests accurately. As the technology matures, we will see it improve and personalise the end-user experience in addition to improving the efficiency of the service management solution.

Automated backend processes
ITSM consists of backend processes that are designed to manage any request or issue entered into the system traditionally by an analyst, or an end-user through a self-service portal. However, ITSM solutions that are integrated with other systems on the network will be able to detect and automatically open a request or incident without any human intervention. For example, imagine an ITSM solution is integrated with a facilities management solution that manages IoT devices, such as smart lightbulbs. By communicating to the facilities management solution, the ITSM solution would be able to detect that a lightbulb is not working, then automatically open a service ticket, or open an asset request to replace the lightbulb without any human intervention.

The power of AI in ITSM will manifest itself through integration with other technologies on the network. For example, integrating an ITSM solution with a solution that provides IT Operations Analytics (ITOA) would enable your ITSM solution to be notified of potential network issues.

Based on patterns, an ITSM solution powered by AI will learn as it updates its knowledge database, ultimately improving how it reacts to any issue. In other words, AI will learn from past experiences.

If ITSM is integrated with every system installed on the network, then it will have the ability to see much larger patterns, making it more efficient. For example, imagine the ITSM system that is integrated with an ITOA solution, is also integrated with security. If the ITOA solution detected an increased amount of browser crashes throughout the day, it would report back to the ITSM department that there was a potential problem.

The ITSM solution would be able to investigate that issue and cross-reference the data with the IT security solution to find any patterns that might explain the anomaly. When ITSM logs the “problem” it would provide insight about how the problem will progress and recommendations on how to fix it. 

As we move further into the future, the ITSM solution will be able to automatically correct the issues by working with the other solutions it integrates with on the network. No human intervention will be required.  

Knowledge management
ITSM solutions powered by AI could then look to knowledge databases for answers. If they are not there, they would go to trusted knowledge sites in the cloud. ITSM powered by AI would solve problems based on infinite amounts of data, and document these findings into those knowledge databases, which could be used to support humans as well, both end-users and analysts.

AI-enabled knowledge solutions will also change the way that end-users ask for help. They will give accurate answers to almost any question very quickly. We live in a world where “instant gratification” has become the norm. We expect the right answer right now. ITSM knowledge solutions in the future will not only provide answers to our IT questions, these solutions will be able to provide training and tips and tricks for end-users and analysts.

Eventually, much of the knowledge provided by an ITSM solution will be knowledge that was learnt by the ITSM knowledge solution, versus documents that were created by human analysts, which are often outdated or not relevant to the current issue. However, until AI is perfected over the next few decades, human input will be vital for ITSM knowledge solutions.

Although ITSM solutions are rapidly evolving, service management will never go away as long as IT exists. However, by implementing AI technology, IT service management will experience a disruption that will change the way humans are involved with the service management process.

Author Bio:
James West

James West

Editor, SITS Insight

If you have service desk news to share or would like to become a SITS Insight blogger, please get in touch with James

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One Response to How AI will impact IT service management

  1. Jim Higham December 12, 2017 at 08:55 #

    This is mainly hype in my opinion. I think there is a place for AI in KM and ITSM however the examples given here are weak and are being done already with simple rule based systems mainly or google search (does Google search count as AI? probably!).

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