Artificial intelligence and machine learning capabilities are not only improving but also transforming ITSM activities. Execution of automated techniques helps IT practitioners understanding the existing infrastructure better.
In this article at TechTarget, George Lawton explains how natural language processing (NLP) acts as a virtual agent. It gives the end-users a familiar interface to communicate with IT service agents.
By employing machine learning to ITSM processes, organizations can generate a volume of ITSM data with unlimited information of when, why, and by whom. The data hints at the existing IT assets, their owners, and utilization to deliver valuable insights.
Machine learning also help organizations resolve existing ITSM issues. It can help you take preventative measures to improve or boost employee productivity. Here are the ways in which AI and machine learning are transforming ITSM delivery:
Automated Classification of Incidents
The integration of chatbots into ITSM infrastructure helps in addressing customer queries. The chatbot interface also streamlines and prioritizes user’s service requests.
Smart Integration of Service Requests
AI in ITSM can automatically transfer the service request to specific support groups. It is an ideal approach to reduce human intervention and maintain consistency in the process.
Addressing Basic Needs Through Task Allocation
With the help of NLP, the chatbots can handle multiple user requests and incidents. It can help your ITSM team maintain a repository of past events to refer to in the future.
Formation of a Warehouse
Using DevOps bots, the ITSM teams can generate a unified repository of strategies for developers and operations teams. They can track critical changes in the IT infrastructure with the help of these repositories to resolve uncertain issues.
Incident Declaration Guide
An ITSM repository can generate an AI guide for a similar incident to configure ideas and address issues with a more fitting solution.
Optimized Learning Process Flow
By automating employee onboarding or other tedious tasks, organizations can reduce unnecessary efforts of their staff. They can use the workforce to resolve other complex issues that require brainstorming.
Proactive Data Analytics
Big data and analytics are effective in improving ITSM capabilities. AI enables proactive resolution of issues introduced through rapid changes in the system.
Detection of Unusual Incidents
Automated tools can detect malicious incidents across multiple IT systems. They can alert the staff to address them beforehand.
Predictive Analytics to Disrupt SLAs
Predictive analytics can inspect performance data to identify potential problems. It can guide your ITSM team to find alternative ways to fulfill service requests.
Monitor Security Flaws
Security researchers can frequently identify loopholes in the IT infrastructure. The AI tools can prioritize ways to address the existing vulnerabilities before the hackers breach.
Click on the following link to read the original article: https://searchcio.techtarget.com/tip/10-ways-to-use-machine-learning-and-AI-in-ITSM-to-improve-processes