Using AI in ITSM
AI in IT Service Management is a hot topic. Artificial intelligence will enhance service quality, reduce costs and achieve better business results.
Intelligent chatbots and virtual assistants
Currently, chatbots are among the most common uses of AI in ITSM. Their quality is growing as AI gains popularity. The benefits clearly refute the old and tired idea that a chatbot is a ‘dumb’ chat platform.
Virtual support is usually part of the self-service portal and represents the first point of contact between the user and the resolving technician on the helpdesk.
Virtual support integrated in communication platforms
Communication with technical support is moving from helpdesk portals, closer to users. It is moving into communication tools like Slack, Teams or Google Chat. The same trend is being followed by Artificial Intelligence and chatbots. For instance, users in Teams make a request that gets processed by the virtual assistant.
Service-desk chatbot in Teams, from ALVAO
The chatbot ‘gets the gist’ of the request
Regardless of how users contact the chatbot, they will receive immediate help – AI will refer users to the knowledge base, offer solutions based on historical data, etc.
If the chatbot is not up to handling the request, it evaluates who is best to pass it on to – through a ticket that the chatbot itself raises.
Benefits of chatbots:
- Support available 24 hours a day, 7 days a week.
- Minimum latency for end users.
- Reduced technical support costs.
- Better user experience, personalized responses based on past interactions, etc.
Predictive analytics
With the help of AI, IT can respond to problems faster and more efficiently. AI minimizes service downtime. It can predict the behaviour of IT systems and the impact on the overall infrastructure.
Predictions based on terabytes of data
AI analyzes a huge amount of data to identify patterns and connections between individual elements of IT infrastructure. It can predict potential problems such as system outages or network congestion.
Data from network monitoring, performance statistics, and other sources are used to predict failures. The information is analyzed with the help of machine learning and other AI techniques to help identify patterns.
Based on the analyses, requests may be raised in the ticketing tool. IT will thus receive a notification of a problem that has not yet cropped up, along with preventive measures, such as the replacement of components or software updates.
AI thus reduces the potential risk of outages and failures. This increases the reliability of the IT infrastructure and minimizes the negative impact on users.
Dealing with requests and automatic resolution
AI algorithms can identify typical problems and propose automated solutions. Problems are solved faster and more efficiently. All of which saves you time and resources – technicians don’t address minor individual issues.
In addition, AI can automate routine work. It raises tickets, draws attention to existing solutions, deletes requests or moves them between departments.
“The AI we develop at ALVAO recommends possible procedures to the solver. Our AI proposes a solution based on a prior request, warns of duplicate tickets, etc. Over time, with increasing data from clients, we want our AI to create, delete and resolve the tickets directly,” says Filip Jandora, ALVAO’s developer on AI.
Efficient work with a knowledge base
One huge benefit of AI is its ability to analyze and process huge amounts of data. This does not have to be exclusively data from the helpdesk tool or asset records. It may even be information that you collect in a knowledge base. AI can optimize the data so that it is easily accessible and effectively shared among users.
Data and information from various sources, such as incident records or change requests, can be categorized with the help of AI, labelling etc. all automatically.
Is a similar incident being handled identically? AI can analyze the problem and the solution that the operator provides, from which it can create knowledge that will be offered to everyone as a solution across the board.
AI-powered content creation
Not only does AI work with data, it can also contribute its own content to the knowledge base. Explanatory materials may be generated based on user inquiries, or pre-defined terms and conditions.
Optimized Incident Management
AI algorithms can identify any incidents and automatically send notifications to technicians. Incidents are dealt with faster and more efficiently. Artificial Intelligence does not stop at sending data. It can solve incidents based on pre-defined procedures or historical data. And if the solution is not clear-cut, AI triggers a diagnosis of the problem and passes it on to the technicians.
Change Management with complete data and tips from AI
Until now, ITSM tools have helped you plan for changes. Using their data, you were able to plan the implementation of new services or the innovation of established procedures. AI will transform Change Management as we know it.
AI will help you understand how long the changes will take, what budget to request, what the risks and potential returns will be. You’ll get broader and deeper data than ever before. In addition, AI monitors everything in real time and can adapt the solution to the situation.
Automatic data categorization
AI will automatically categorize assets based on their characteristics and attributes. It will now be easier to track and manage resources. For intelligent asset categorization, AI will use machine learning and natural language processing technologies. This will help AI identify key asset characteristics and automatically categorize them.