Open Access
American Research Journal of Computer Science and Information Technology
ISSN (Online): 2572-2921
DOI: 10.46568/arjcsit
The Use of Trained AI to Automate Decision-Making in Industrial Systems
Abstract
The article discusses issues related to the specifics of using trained artificial intelligence (AI) to automate decision-making
(with an emphasis on the industrial sector). The importance of addressing the topic is predetermined by the growing
demands on the efficiency and reliability of industrial systems (especially against the background of rapid digitalization,
which permeates all areas of activity without exception). In the current environment, trained AI is becoming a key tool to
help establish and optimize production processes, as well as reduce operating costs. At the same time, its application in
the field under consideration is accompanied by several contradictions, including the implied lack of unified approaches
to its integration, limited methods for assessing the quality of those decisions that are made, and insufficient attention to
issues of ethical responsibility. The purpose of the study is to analyze existing developments regarding the integration of
trained AI into industrial systems, systematization (based on familiarization with scientific publications) of advantages,
and related limitations. The article summarizes modern achievements in the field of predictive analytics, security
management methods, and the protection of AI systems from adversarial attacks. The conclusions point to the need to
unify methodological approaches, increase the resilience of AI to external threats, and develop standards governing its use.
The presented materials will be useful to scientists dealing with the problems of artificial intelligence, and automation,
specialists in industrial safety, and heads of enterprises interested in the digitalization of production.
