Formation of a convergent industrial, scientific, and educational ecosystem using generative artificial intelligence technology

The article is devoted to the development of a concept for a new-generation industrial, scientific, and educational ecosystem integrated with generative artificial intelligence technologies and focused on sustainable management of specialist competencies.
The research objective lies in creating an effective coordination mechanism for university-industry-government collaboration under conditions of accelerated transformation of technological requirements and labour market demands.
The ecosystem is conceptualised as a three-circuit system: the research-educational circuit encompasses universities, departments, laboratories and academic staff; the production circuit incorporates partner enterprises, real industrial projects and their digital twins; the digital circuit establishes the technological foundation, including generative AI, competency databases, analytical services and VR/AR training simulators. This approach ensures resource integration and flexible adaptation of educational processes to production needs.
A mathematical model has been examined to formalize ecosystem dynamics. It reflects changes in resource potential, educational expenditure and specialist training flows, accounting for material, digital, human and intellectual resources. The model enables the
formalisation of management processes and evidence-based decision-making.
Particular attention is devoted to data processing and interpretation within the convergent environment. Generative AI serves as an analytical tool for unstructured information from professional standards, curricula, production processes and digital twins. The
feedback system ensures automatic adjustment of educational content in accordance with current industry requirements.
The practical significance of this research lies in developing a mechanism to overcome traditional barriers between education, science and production through intelligent automation of competency management. Implementation of this concept contributes to
the modernisation of high-technology sectors within the national economy and establishes a sustainable specialist training system.
The proposed framework addresses contemporary challenges in workforce development by leveraging advanced digital technologies to create seamless integration between theoretical knowledge acquisition and practical skill application. Through continuous monitoring and adaptive learning mechanisms, the ecosystem maintains alignment with evolving industrial demands whilst preserving academic rigour and research excellence.

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