The diploma thesis examines the possibilities of using artificial intelligence to manage the time and costs of a construction project. Due to their technical, organisational, time-related and financial complexity, construction projects are often exposed to delays, cost overruns, changes in scope and other risks. The thesis first presents the theoretical foundations of project management, the characteristics of construction projects, and the importance of managing time, costs and risks. It then discusses the limitations of traditional project management, particularly manual preparation of schedules and reports, delayed detection of deviations, disconnected project data and dependence on individual experience. The central part of the thesis focuses on the use of artificial intelligence in delay prediction, cost overrun prediction, progress monitoring, project documentation analysis, automated reporting, risk analysis and decision support. The thesis finds that artificial intelligence does not replace the project manager, but can serve as a support tool for faster data processing, earlier detection of deviations and the preparation of a better information basis for decision-making. Based on the literature review, a conceptual model of AI-supported project management is proposed. The model connects project documentation, the project schedule, cost data, site data and external factors. The proposed approach is also illustrated using a simplified construction project example, including early detection of deviations, prediction of time and cost impacts, and comparison of alternative corrective-action scenarios.
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