The growing complexity of construction projects combined with the digital transformation of the industry makes it necessary to modernise personnel management systems, which is a key factor in ensuring the competitiveness of construction enterprises. The purpose of the study was to develop a comprehensive digital human resources (HR) management system designed to increase the efficiency of HR processes in the context of dynamic technological changes. The methodological foundation of the paper was based on the analysis of corporate documentation of 8 international construction companies for the period 2020-2023, which served as a basis for evaluating and implementing innovative HR strategies. Among the critical achievements, the integration of artificial intelligence into recruitment processes is notable, which reduced the recruitment time by 32% and substantially improved the quality of candidate selection (an increase of 45%). The use of virtual reality (VR) simulations in training programmes reduced the error rate when performing complex production operations by 45%. In addition, the developed competence monitoring system, based on 15 parameters of construction processes, contributes to the formation of reference profiles of specialists. The transformation of the workspace based on the activity-based working principle had a positive impact on the level of professional burnout, reducing this indicator by 18%, and increasing labour productivity by 16%. The implemented well-being support programmes recorded a 22% reduction in the number of sick days, and the development of cross-functional teams accelerated the introduction of innovations by 35%. The combination of these results creates a practical basis for the modernisation of HR processes in the construction industry. The study materials can be used to develop professional development programmes, adapt innovative HR management methods, and form digital transformation strategies in the context of the specifics of the construction industry
digital transformation; professional competencies; cross-functional teams; predictive analytics; well-being programmes