Aside from using AI in software testing and development, we’ve touched upon, the technology can also be used together with IT in the following ways.
AI in Service Management:
AI technology and machine intelligence are also widely used when it comes to service management. When leveraging AI for service management, companies can use their resources more effectively, providing faster deliveries at a cheaper price. Thanks to its machine learning capabilities, AI will offer IT companies a type of self-resolving service desk which will allow them to analyze all of their input data and provide users with proper suggestions and possible solutions.
By applying AI, they will be able to track user behavior, make suggestions, and provide self-help options to make the service management process more effective, overall. In other words, AI will provide users with a better experience through self-service.
In addition, AI can be used to develop Computer Vision (CV) technology that can be used to automate the visual understanding from a sequence of images, PDFs, videos, and text images with the help of M.L. algorithms. What happens is that CV replicates certain functions of human vision, but at a much faster and other, more accurate rate.
Machine learning and deep learning capabilities of AI will allow systems to analyse a request submitted to a service desk. The AI will find all concurrent requests, compare the newly submitted ones with those that have been previously resolved, and get an instant understanding based on past experience. The end result will be a solution to the request.
All in all, AI being such a powerful business tool, it can assist IT professionals in their operational processes, by providing them with a more strategic approach. By being able to track and analyse user behaviour, the AI system will provide suggestions for process optimization and even help with developing a comprehensive business strategy.
AI for IT Operations (AIOps)
AI for IT operations refers to the use of Artificial Intelligence to manage Information Technology based on a multi-based platform. The main technologies used in AIOps are Machine Learning and Big Data. These automate data processing and decision making, using both historical and online data.
The expected result of using AIOps is a continuous analysis that will provide answers and allow for the continuous implementation of corrections and improvements in terms of IT infrastructure. The AIOps platform used will connect performance management, service management, and automation to achieve its intended purpose and can be looked at as a continuous improvement of information systems.
There are several reasons why AIOps is growing in popularity over the past several years. Among these, we can include the ever-increasing volume from data collection systems, the increase in the total number of information sources, and the rising number of changes in controlled systems. As such, it’s also become increasingly hard for specialists and professionals to keep track of all of these systems, let alone respond to any issues effectively.
AI In Fraud Detection
Modern technology has made it much easier for companies to detect fraud. At the same time, however, it has also multiplied the ways in which cybercriminals are committing fraud. Most businesses will need to use a multi-layered approach in detecting fraud, which usually will involve statistical data analysis and AI There are several Artificial Intelligence tools used in fraud detection. Among these, machine learning can process large amounts of data at a much faster rate than people can.
It can also be designed to become faster and more accurate over time Machine learning tools will be able to identify patterns of fraudulent behavior by looking at historical data that involved similar circumstances. The IT department will then use the synthesized data to take the appropriate action against these cyber criminals as well as build more effective preventive measures for the future.