The thesis investigates the feasibility of automated decision-making (ADM) in project management from two perspectives - technical feasibility, analysed through a comprehensive literature review, and organisational acceptance, evaluated through empirical evidence. To address technical feasibility, the literature study is used, and it underscores the significance of data-driven decision-making and the impact of advancements in machine learning. Organisational acceptance is investigated with thematic analysis, and the complementary method employed is semi-structured interviews, allowing for in-depth insights from experienced project managers. The analysis reveals that project integration, cost, and risk management exhibit considerable potential for ADM integration, whereas schedule, resource, and procurement management demonstrate varying levels of applicability. In contrast, scope, quality, communication, and stakeholder management are deemed less feasible due to their complex nature and the critical involvement of skilful project managers. As a result, the study advocates a balanced approach to ADM implementation, combining automated capabilities with human expertise. Its contributions lie in the formalisation and categorisation of ADM applications, addressing the challenges, and providing valuable insights for practical ADM adoption in project management.