The relevance of this study is determined by the need to improve human capital manage- ment systems at enterprises in the context of the introduction of new technologies transforming production and business processes. For large companies with sufficient resources, one solution to this problem may be the creation of a human capital reproduction ecosystem in which the enterprise acts not only as the end consumer but also as a customer and co-producer of personnel. This paper examines the development of such an ecosystem in the context of the spread of artificial intelligence (AI) technologies. The aim of the study is to identify the characteristics of human capital reproduction in an enterprise amid the spread of AI technologies based on employee assessments of their applicability, loyalty, and satisfaction. The scientific novelty lies in the development of a methodological approach to assessing the reproduction of human capital in an industrial enterprise amid the spread of AI technologies, based on the perception of these technologies by those who hold human capital. The theoretical basis consists of the works of Russian and international authors devoted to the reproduction and management of human capital, as well as the development of an ecosystem approach in the social and labor sphere. The use of the index method allowed us to obtain assessments reflecting the attitudes of employees and students toward AI technologies. The empirical base was formed by the results of a survey among employees of the mechanical engineering company that initiated the ecosystem, and students of the university included in this ecosystem. A total of 72 employees and 47 students were surveyed. The results yielded assessments of employee and student loyalty and satisfaction with AI technologies, providing insight into the transformation of various stages of human capital reproduction in the context of the introduction of new technologies. Overall, human capital holders positively evaluate the use of AI technologies; however, the loyalty index of both employees and students revealed that absolute adherents of these technologies are in the minority. Employee satisfaction is rated low (47.92), while that of students is average (76.45). This is due to the fact that the use of AI in the educational process, which underlies the stage of human capital formation, is significantly more intensive. Based on the data obtained, key areas of transformation in the human capital reproduction ecosystem in the context of the spread of AI technologies are identified.