International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Artificial Intelligence (AI) is rapidly transforming Learning and Development (L&D) by enabling personalized learning experiences, accelerating content creation, improving multilingual delivery, and supporting data-driven decision-making. While current adoption predominantly focuses on content production efficiency, the strategic use of AI for workforce development and skills management remains underdeveloped. This paper examines the role of AI-based training solutions in corporate learning ecosystems, drawing on recent industry research and insights from qualitative interviews with three learning and development experts. The study discusses opportunities, implementation challenges, ethical considerations, and the emerging shift toward AI-native learning platforms. Recommendations for future implementation and research are provided.

In this paper are presented some conclusions on the selection of the LMS to be used. The results of this study give readers information to make their own decisions when choosing an LMS platform based on the needs of their institution. The process of LMS selection is a multi-criteria decision-making problem and an Analytical Hierarchy Process (AHP) was used to assist in building the model and draw decisions. The paper presents an environment ”Network technologies for e-learning”(NTEL) using the offered Model for describing, structuring, and organizing the ontological representation of learning objects through providing a semantic infrastructure. Strategies and methodologies in ontology development and implementation are also discussed.