ARCHITECTURE OF MANAGEMENT SYSTEMS BASED ON HYBRID INTELLIGENCE: INNOVATIVE APPROACHES TO PROCESS OPTIMIZATION

2024

Full text Open access: Hybrid Metadata (CSL-JSON)
DOI 10.52167/1609-1817-2024-135-6-223-231
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This paper presents a study on the architecture of management systems powered by hybrid intelligence, which combines the capabilities of artificial intelligence (AI) with human expertise to enhance the efficiency and adaptability of business processes. The relevance of this work is driven by the increasing demands for intelligent management solutions in the context of digital transformation. The paper outlines the key architectural elements of such systems, including machine learning techniques, predictive analytics, natural language processing, and expert systems, along with their integration into a unified management platform. Special attention is given to optimizing decision-making processes through the combination of automated data analysis with human intuition and expert evaluations. The paper discusses successful examples of the application of hybrid intelligent systems across various industries, demonstrating their effectiveness in managing uncertainty and rapidly changing markets. The author also explores the future potential of hybrid intelligence as a strategic management tool capable of significantly enhancing the productivity and competitiveness of modern enterprises.