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AI in ITSM? Don’t miss the proverbial bus, and discover the trends that will shape the next decade

How can AI (Artificial Intelligence) improve today’s ITSM processes; where has AI been helping for quite some time; where is development heading? AI integration into the workplace will be increasingly common. Virtually any activity that works with data can be made more effective with AI. It’s no surprise that AI in IT Service Management is a hot topic. AI can already improve service quality, reduce costs and improve business results.
Jana Šilarová

3. 4. 2023

What can AI do in ITSM 

By implementing tools and best practices, AI can collect and analyze data from various IT tools for network monitoring, event management, or configuration management. Artificial intelligence can identify patterns of behavior following incidents, run automated workflows, and analyze the likely cause of an outage.  

AI can help you buy software 

The trend to buy software as a service (SaaS) is growing in market dominance. Yet, what kind of license to buy often remains an open question. AI can provide the answer.  With AI, you have software usage data to help you make decisions. Artificial intelligence automatically generates a professional report on the frequency of use of the various software apps. Without laborious manual work. Licensing is likely to shift, from quarterly billing to payment by the day or hour. How you actually use your software will become crucial knowledge. 

Virtual assistants and chatbots  

Among the most widespread implementations of AI in ITSMT are chatbots and ‘virtual’ IT assistants. Chatbots and virtual support staff are usually the first point of contact between the user and the solver – the technician on the other side of the helpdesk solution process.

The quality of chatbots is skyrocketing

Today’s chatbots are not just ‘dumb’ tools with a few phrases that will ultimately pass you over to support. Thanks to deep-learning neural networks and terabits of reference data these networks learn from, the chatbot can recognize the user’s intention and mood. The tool can provide the user with the required information or corresponding solutions from the knowledge base. 

According to IBM research, a chatbot implementation can reduce technical support costs by up to 30%.   

LEGO figures

Artificial intelligence in communication channels 

User support and service provision are gradually migrating from primary ticketing tools to direct communication/chat channels such as MS Teams. That makes for direct contact with users. Employees simply create an IT or HR request from Teams, for example, and the entire communication exchange takes place in the application. Everything is recorded and traceable.  

The same trend applies to AI, which will become part of communication channels more and more often 

Graphical user interface, application Description automatically generated               

Service desk chatbot in Teams, from ALVAO - learn more in the video ALVAO for MS Teams

Process automation with AI, according to ITIL 4  

Artificial intelligence in ITSM is not limited to chat. Less noticeable, and all the more important, is the overall automation of processes and predictive analytics. 

Service management systems such as the Service Desk (helpdesk tool) record huge amounts of data. Nevertheless, few are analyzed or used to make decisions.

AI machine learning in analytics will be used to identify correlations that no person could cost-effectively evaluate. AI can make high-accuracy predictions based on historical data.    

Incident Management 

AI will be able to identify and classify incidents, propose solutions, or assign incident resolution to the right team or person. AI can recognize patterns in datasets, allowing the Service Desk to quickly identify and resolve recurring issues.  

For example, if the same problem is occurring with a specific device, AI can identify the pattern and suggest a lasting solution. 

Change Management 

ITSM tools generally help with change management. AI takes Change Management to the next level. AI analyses the impact of change, assesses risks and costs, recommends best practices and monitors the results of changes in real time. AI can help automate approvals processes and stakeholder communication. 

Service Configuration Management (CMDB) 

AI can extend configuration management (CMDB) capabilities. AI automates the discovery, classification, and mapping of IT resources and their dependencies. AI helps maintain the accuracy and completeness of CMDB data, as well as detecting and resolving inconsistencies and errors.  

AI can provide insights and recommendations based on CMDB data analysis. For example, identifying potential risks, opportunities and optimizations for IT service management.  

Knowledge Management 

AI can create, update, and share knowledge across the organization. AI can extract information from a variety of sources — documents, databases, and conversations. Thus, it can help to find and provide relevant knowledge for problem-solving or process improvement. 

Asset Management 

AI can help optimize asset usage by tracking status, location, and ownership to analyze trends and behavioral patterns. AI can also help detect and resolve issues with assets, or plan for asset renewal or disposal.  

AI in predictive maintenance will make it possible to anticipate potential problems and alert you to solutions before a failure. This will significantly reduce system downtime and costs 

Deploying AI in ITSM 

Have you taken a shine to AI, and want to introduce it in your company? There are several ways to deploy AI in your ITSM tool. The process is demanding and complex, but we will at least outline the basic procedure. 

First of all, you need data to work with. These might be from your ITSM tool or another source. The selected data must be pre-processed – selected, normalized or converted. With the help of deep learning frameworks like TensorFlow or PyTorch, AI gets trained and learns from the data entered.  

It is also necessary to integrate the trained model with your ITSM tool using the API. You can use the ChatGPT and OpenAI interfaces or create your own. 

The next step is to integrate the model with the user interface of your ITSM tool. This might be to create a chatbot, integrate the model with an existing platform or embed AI into a tool for generating articles, etc. 

As a final step, you need to test the AI. You monitor whether the AI meets your requirements and matches the required performance and accuracy.Al

How we test artificial intelligence for ITSM tools in ALVAO 

The potential of AI is huge – especially in the field of ITSM, which is interwoven with user data. That is why we at ALVAO are testing artificial intelligence integration into our products.  

We began by looking at where AI could come into the picture. We identified areas in our Service Desk tool that could be improved or automated by artificial intelligence. Now we are preparing prototypes and testing them with customers.  At this stage, our AI is recommending potential approaches to the solver. It proposes a solution based on an existing requirement, warns of duplicate tickets, etc. Over time, AI could raise, delete and resolve tickets independently. 

“We believe in developing AI for our ITSM tools because we see artificial intelligence as the future. This is our main motivator. I think we are at the beginning of something that will grow enormously,” comments ALVAO developer Filip Jandora. 

How far will AI evolve, in the ITSM world 

AI has the ambition not only to streamline human activities but to replace them. With the advancement of AI and the pressure for efficiency, the distinction between end-user communication with a virtual assistant or a human agent is likely to blur.  The development of technology will allow the automatic resolution of some requests without the intervention of a support agent. In addition to process automation, AI will probably also be responsible for the overall analysis of processes and setting up their optimization. For example, editing articles from the knowledge base or adding new ones – all based on data about user behavior and needs. The next step could be to modify the services themselves, create new ones, delete existing ones, change the SLA, etc.

Eventually, we may get to the point where AI will make decisions that are entirely strategic. 


AIOps and AISM – new disciplines in ITSM  

With the migration of AI into ITSM processes, new fields have also emerged – AIOsp (Artificial Intelligence Operations) and AISM (Artificial Intelligence Service Management). Regions use AI to automate and optimize IT operations. Traditional practices will find it increasingly difficult to keep up with the competition these days. Therefore, the implementation of AIOps and AISM will be critical for most organizations.