Low-code platform «n8n» as the basis for managing the intellectual ecosystem of an enterprise based on artificial intelligence

the aim of the study is to develop a conceptual model of an ecosystem of intelligent enterprise management systems based on the n8n platform and to substantiate its effectiveness for improving operational efficiency in the digital economy. Methods: the research employs system analysis of the n8n platform architecture, comparative analysis with competing solutions (Zapier, Microsoft Power Automate, Make.com), case study method based on implementation analysis in five companies from various industries, and business process modeling using BPMN 2.0 notation. Findings: a four-level conceptual model of the ecosystem has been developed, including infrastructure, integration, intelligent, and management levels. Empirical analysis showed operational efficiency growth from 25% to 300%, average payback period of 2.4 months, and labor cost savings of 70-200 hours monthly per process. Conclusions: the synergistic effect of integrating low-code technologies and artificial intelligence in building management ecosystems has been confirmed. The proposed model ensures a transition from monolithic information systems to an adaptive network management architecture, which is critical in conditions of IT specialist shortage and the need for rapid digital transformation of Russian enterprises.

enterprise management ecosystem, n8n platform, low-code technologies, digital transformation, intelligent management systems, business process automation, artificial intelligence