7 AI and machine learning use cases in ITSM

AI and machine learning are no longer a thing of the future. The future is now and ITSM can benefit from it to increase team efficiency, reduce operational costs, as well as raise customer satisfaction levels. It is, as they say, managers should listen to their employees and employees to the customers. 

Below, you will find out more about what AI for ITSM means, the advantages of using technology to scale, and also a few AI ITSM use cases to convince you that this can become the new normal. 

What is an AI-powered service desk?

AI service management is a team powered by a digital tool that can help with IT assistance. For example, help desk teams can use an AI-based ticket assistant to automate the process of addressing and forwarding customer queries.

>>> What are AI and machine learning?

Artificial intelligence, or AI, is the intelligence that machines proved to have. Machine learning, or ML, is an application of AI, and represents the process of feeding data to support a computer learning on its own by detecting patterns, without direct input.

ML, deep learning, and natural language processing or NPL, amongst other cognitive technologies, are at the base of useful tools, such as chatbots, virtual assistants, and predictive analytics, to name a few. AI for ITSM helps reduce costs, increase productivity, as well as forecast issues, and improve key metrics. 

>>> Is artificial intelligence the future of the IT help desk?

AI is one of the biggest tech markets globally, estimated to reach over $1000B by 2029. By leveraging an AI service management tool, albeit not cheap in the beginning, a company can lower costs long term. 

For help desks, it facilitates answering basic questions and developing personalized messages, to name a few, inside and outside a company. It can also evolve on its own based on its experience. 

Chatbots reduce the number of tickets that help desk employees receive daily. They also help by triaging tickets and gathering data about issues, so the IT team can improve products or solutions, and even their skill set. 

How can AI and machine learning be used in ITSM?

The purpose of ITSM or IT service management is to create scalable workflows that teams can count on to deliver excellent services. Due to the fast-paced evolution of digital services, ITSM needs to adapt to keep up with rising customer expectations.

Here is where ML can join by taking care of repetitive tasks, so employees get uninterrupted time to focus on other things. For example, if they receive a classic malfunction request, AI service management can offer articles that users can read and help themselves in that instant instead of waiting. But there is more AI in ITSM use cases.

  1. Routing of Service Requests, which means that it can scan the request using natural language processing (NLP), label it ‌and then send a personalized answer based on the product you are using, the language, and even the market you are working in, or assign an IT professional to fix the problem. 

  2. Incident management means AI service management and more precisely ML can solve any Level-O and Level-1 tickets. Level-O means that ML can identify the problem right away, while Level-1 means that it can take a draft solution and adapt it to suit a particular problem. For example, if a program isn’t working properly, it might suggest updating it; or if a password needs resetting, it can send an automatic link to do so.   

  3. Problem management means that ML can keep tabs on recurring issues with a specific solution and can make predictions about when it will happen next, or show where bugs keep happening and the solution needs upgrading. AI can manage the root cause analysis, like a virtual agent 

  4. Data-Driven Predictions are a key asset of using this type of technology, as they will automate offline maintenance periods based on the right data, not on standardized ones. Also, you might not need the system to be fully offline, only parts of it. 

  5. Change management is another aspect that ML can facilitate. This means that when things need to shift to accommodate the core, business goals, AI service management can help managers better understand what teams need, how long it will take, and what is the required budget. 

  6. Reporting and Alerts in Real-Time is a top advantage as AI can be set up to do everything instantly, thus lowering human delaying or error, which is an important aspect when it comes to cybersecurity.

  7. Service asset and configuration management is a mix of asset management of how you deliver IT services and configuration management, which tracks various IT components in your service. The flow requires planning, managing, identifying, auditing, and changing in a balanced loop. This takes time, and AI is a master at saving it by identifying gaps and facilitating onboarding processes. 

In the end, think of AI for ITSM like how Google already serves us the right content personalized to what we are searching for and less like Matrix’s SiFi world. AI-powered tools are here to support customer and support teams, not take over their jobs. A digital transformation is already happening; give your employees time to get acclimated and the results will be worth it.

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