Westh Duggan's Kennel

With all the advances in the field of Artificial Intelligence (AI) and its broad application across different disciplines, this latest technology is coming into IT Service Management (ITSM). ITSM has witnessed multiple kinds of technological advances that promise to revolutionize the way things work. But many of them failed to make an impact and have passed on as mere fashions. The most obvious question everyone is asking is "Aid in ITSM": Is AI going help assist in making ITSM more effective and less complicated? This is the issue we'll address in the two-part series "The AI Advantage In ITSM". Part one, "AI at Work" in ITSM, sets the stage for our AI discussion. Part 2 "Features and Utilization Cases," will focus on specific AI-related features as well in use cases that can change the way IT service desks function. Check out here to find out additional resources on IT helpdesk automation. Industry experts make some solid predictions about this. Gartner's Predicts for 2018 Artificial Intelligence report[i"> states that by 2022, 40 percent of employees who interact with citizens and government employees will utilize an AI virtual support agent to assist them in making decisions or handling their requests. Gartner says that AI capabilities will empower virtual support agents to act as a resource which will enable human support personnel to respond quicker and more effectively to citizen or customer inquiries or requests. AI will have a significant impact on IT service desks once it is capable of doing tasks humans are unable to perform and also take actions that humans wouldn't mind doing. These actions fall under one of three categories: strategic insight and smart automations. They are also known as predictive analytics. The manual process of routing tickets to the right person takes a lot of time that an IT technician can be using to perform other duties. Help desks may use rules to automate ticket routing. The rules classify requests according to predefined conditions and parameters. But, these rules are not permanent, which means they won't alter or evolve over time. Service desks can use AI technologies like Machine Learning (ML) to create a categorisation model based upon previous IT service desk information. Best of all, these ML models will become more precise with time by taking live data into consideration. The models that are based on ML are much more efficient than manual categorization and rule-based automations. Vendors have the ability to develop AI-based models that produce insights and detect irregularities within IT service desks. This is a huge advancement over what would take for humans to do. Real-life scenarios include suggesting the best window for patch updates, helping with change management and implementation, flagging breaches of an SLA, and anticipating IT problems. What is the process by which AI is used How AI functions in ITSM. AI algorithms and programs are designed based on available documented knowledge and historic data. This means that AI is as effective as the information base and data it is based on. ITSM requires that an AI-based model be created for any specific situation. This is similar to ITSM. It must be well documented with solutions, workarounds, and articles, as well as historical data. To develop an AI-based categorization/prioritization model, for example, we need a historical database that contains the types of requests, their levels and impacts, as well as urgency website and other parameters. This data must be documented. In addition, AI-based models such as these don't work everywhere. Prioritization and categorization models are trained on particular data sets and are only used by the desk that the data set is retrieved. They continuously train themselves by using live data to improve their accuracy and effectiveness over time.

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