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The management of systems is often associated with great difficulties arising from the high degree of uncertainty in the elements influencing the system’s operation. One means of overcoming these difficulties is to automate processes by applying knowledge in artificial intelligence systems. The development of technologies in the field of artificial intelligence contributes to the increase of capabilities in control systems to perceive and interpret reality. The paper presents models of a conventional system with artificial intelligence, as well as a description of the properties and processes involved in the control process in both systems. The brief analysis identifies opportunities for improving management and increasing its efficiency through the use of artificial intelligence systems.
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The transition from a post-industrial economy to a digital economy is presented as a major trend in world economic development at the beginning of the 21st century. The relationship and conditioning of the term “digital economy” with related concepts is traced and it is emphasized that the digital economy creates new opportunities for growth and well-being, but is also associated with many challenges. The digital economy is emerging as a generalizing concept, which is reduced not only to new digital technologies, but also to significant changes in the traditional rules of doing business, in new manifestations of classical economic laws. The expansion of the digital economy thus has major strategic implications for productivity growth and global GDP.
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