USE OF ARTIFICIAL INTELLIGENCE IN AUTOMATED SYSTEMS - ANTONENKO, АRTEM; PAKHOMOV, MYKHAILO; KALYTA, TETIANA; HALETA, VOLODYMYR (Herald of Khmelnytskyi National University. Technical sciences, 2023)
The rapid development of artificial intelligence and its integration with production automation have initiated changes in the commercial activities of enterprises. Companies and commercial enterprises are focusing on the application of artificial intelligence along with advancing production automation to achieve new heights of mastery and perfection. This article provides a characterization of the application of artificial intelligence and automation to demonstrate how artificial intelligence and automation are interrelated and how they can be more efficient when they work as a whole, and what competitive advantages they can offer. The combination of artificial intelligence and automation has transformed the way enterprises operate. With the integration of these technologies, companies can optimize their operations, enhance their products and services, and improve their overall efficiency. One of the main advantages of using artificial intelligence and automation is that it allows businesses to process and analyze large amounts of data quickly and accurately. This is particularly important in sectors such as finance, where decisions must be made quickly based on real-time data. Another advantage of using artificial intelligence and automation is that it enables companies to reduce their labor costs while increasing productivity. Automation can take care of repetitive and mundane tasks, freeing up employees to focus on more important tasks that require a human touch. Artificial intelligence can also assist in decision-making by analyzing data and providing insights that humans may miss. Overall, the combination of artificial intelligence and automation presents significant opportunities for businesses to enhance their operations and gain a competitive advantage. However, it is important for companies to carefully consider the potential risks and challenges associated with these technologies and to develop strategies to mitigate them.
Keywords: machine learning; automation industry; artificial neural network; autonomous computing; algorithms