Abstract
Artificial intelligence (AI) technologies have great potential to improve decision-making and automation processes in various sectors, including project management. AI technologies could significantly contribute to overcoming the complexity of project management through process automation, cognitive insight, and engagement. However, the adoption of AI technologies still faces many challenges due to technical, human resource-related, organizational, and legal issues. Our research identified the potential factors that lead to the willingness of people and organizations to adopt AI technologies in project management. This paper proposes a causal model describing multivariate causal relationships between the driving factors and the willingness to adopt AI. The causal model is a set of hypotheses evaluated through a survey and causal analysis using the structural equation modeling (SEM) technique. The analysis focused on six factors influencing the willingness to adopt AI in project management, i.e., performance effectiveness, price, previous experience, feedback, complexity, and complementary technologies. Our research found that the perception of the high effectiveness of AI technologies leading to higher profits and overall the state of the project is the main factor influencing the willingness to adopt AI technologies in project management.
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Sarafanov, E., Valilai, O.F., Wicaksono, H. (2024). Causal Analysis of Artificial Intelligence Adoption in Project Management. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2023. Lecture Notes in Networks and Systems, vol 822. Springer, Cham. https://doi.org/10.1007/978-3-031-47721-8_17
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