4me AI in ITSM

Artificial intelligence (AI) is being assigned a key role in the future of ITSM. It is beyond doubt that AI is becoming an essential element for improving efficiency and providing better customer support. In this post, we will focus on the ways in which 4me uses AI in the context of better and more efficient IT service delivery.

„Companies must embrace AI as a strategic imperative, integrating it into their business model, processes, and decision-making to drive efficiency, innovation, and competitive advantage in an increasingly AI-driven world“  – Prof. Claztion Christensen 

In the 4me platform, the AI is built on the Amazon Bedrock service. This service allows you to build your own generative AI application using various high-performing foundation models.

In this case, the answer is Retrieval Augmented Generation (RAG) AI. This means that the model is adapted to use specific data or 4me requirements. AI agents can thus perform specific tasks within 4me by using data resources directly in 4me.

Using AWS Bedrock allows you to maintain a high level of safety and ethical responsibility.

4me AI already brings directly integrated the following functionalities:

Automatic summarization of the request

Specialists, especially at the second and third level of support, often have to analyze a request that contains a lot of notes and comments from the previous solution to the request. In this case, if the request is transferred to another specialist and contains more than 5 comments, the AI enables the automatic creation of a summary of the request. In the case of requests with a lot of comments, this AI functionality can save tens of minutes of analyzing the request by specialists.

Example of summarizing a request through 4me AI:

Summarization for customer notification

If the specialist needs additional information from the applicant to solve the request, 4me allows you to send an automated notification by simply switching to the “Waiting for customer” status. In this case, 4me AI can generate a short summary of the request and specify what steps or information are required from the requester in order for the specialist to proceed.

Example of a customer notification generated by 4me AI:

customer notification message

Designing knowledge articles

After resolving a request or issue, it is a best practice to check whether a knowledge base article needs to be created on the topic. However, specialists often avoid this activity and prefer to deal with other requirements. Therefore, 4me comes with the possibility that the article will be suggested by 4me AI based on the information of the given request or problems.

Example of knowledge article content design using 4me AI:

knowledge article example

Benefits of 4me AI

As can be seen from the above examples, 4me AI can significantly save the specialist’s time or make his work more efficient. Let’s take a realistic model example of a specialist who, within a month, among other things, solves 20 more complex requests or incidents, where it is also necessary to add information from the user and creates at least 1 knowledge article. In this case, 4me AI can save approx. 5% of the monthly working time, which represents approximately 1 MD. And in the case of 4me without any increase in the price for using the service.

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