INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO INFORMATION SYSTEMS OF DIGITAL ECOSYSTEMS IN THE HOSPITALITY AND RESTAURANT BUSINESS

Abstract

Introduction. The article is devoted to a comprehensive research on the transformation of information systems in hospitality and restaurant enterprises within the framework of the agent-based digital ecosystem concept. In current conditions, the industry's digital transformation requires a fundamental transition from fragmented software usage to the construction of holistic, interconnected ecosystems, where intelligent technologies serve as a key driver of synergy between business processes. There is an urgent need to address the integration of autonomous AI agents with traditional management systems, as this approach is a prerequisite for ensuring sustainable competitiveness amidst high market turbulence and dynamic shifts in consumer expectations.

Purpose. The purpose of the article is to develop a conceptual model of a digital ecosystem for hospitality enterprises integrated with autonomous AI agents and to define the methodological toolkit for assessing the feasibility and efficiency of implementing such solutions in the business activities of hospitality and restaurant enterprises.

Materials and methods. The study is based on contemporary scientific publications in the field of digitalization, analytical reports on innovation implementation, and established architectural principles of decision support systems. The research utilized a comprehensive methodological approach: system analysis (to structure the digital ecosystem components and identify their interrelationships); comparative analysis (to distinguish between the capabilities of traditional automation and innovative agent-based solutions); logical modeling methods (to create the multi-level conceptual architecture); and the method of abstraction and generalization (to formulate strategic conclusions regarding business resilience in the digital transformation era).

Results. A multi-level conceptual digital ecosystem model has been developed, based on three interconnected segments: the level of primary data accumulation and consolidation ("data lake"), the level of intelligent processing driven by autonomous AI agents, and the level of analytical support for management decision-making. An integral efficiency indicator for implementing the model has been substantiated, accounting for revenue growth from service personalization, operational cost optimization, and investment expenditures. Key integration factors identified include ensuring high data compatibility via application programming interfaces, algorithmic transparency, and reducing the cognitive load on personnel. It is proven that the implementation of the proposed architecture facilitates the transition of enterprises from passive accounting to proactive dynamic business management.

Discussion. Future research should focus on cybersecurity mechanisms within agent-based ecosystems, the development of standards for ethical AI usage, and the improvement of interaction algorithms between various types of AI agents to enhance their autonomy and self-correction capabilities in crisis management scenarios.