The Role of Digital Learning Innovations in Strengthening Human Capital: A Mixed Educational and Corporate Perspective
Abstract
The current era is influenced by digital transformation together with Industry 4.0 and 5.0, which also significantly affects the area of human capital management and development in the form of education. The article analyzes the strategic use of information technologies, including artificial intelligence (AI) and machine learning (ML), in the process of increasing the efficiency of education and in the adaptation process of employees. The theory is devoted to human capital, potential and innovations used in the educational process with an emphasis on modern digital technologies, pedagogical models and adaptive learning. The research analyzed the results of a quantitative survey among Slovak university students (n=78). The results showed that students are very satisfied with current forms of teaching in the online space (video lectures, problem-solving tasks). However, universities should consider technical limitations or mandatory interaction of participants, because these two factors are perceived by students as barriers. To support the research, a case study of the Slovak branch of HPE was also analyzed, where it was confirmed that personalized education using modern technologies (cloud, educational tools based on AI and ML) makes the employee development process more efficient and improves the quality. The results of the article emphasize the necessity of cooperation between the human factor (human resources specialists) and technologies in the employee education process. This makes it possible to ensure a resilient and qualified workforce that will be able to deal with the situation and challenges of the digital economy.
Fields of Study & Subjects
Impact of AI and Big Data on Business and Society
Digital Transformation in Industry
AI and HR Technologies
Publication details
- Journal / source
- Advances in Artificial Intelligence and Machine Learning
- Publisher
- Advances in Artificial Intelligence and Machine Learning
- Volume
- 06
- Issue
- 01
- Pages
- 5096–5096
- Publication date
- 1 January 2026