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Artificial Intelligence Influence In Project Management: A Literature Review

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  • ADAM Ioana-Gabriela

    (Alexandru Ioan Cuza University of Iasi)

Abstract

An increasing number of technological solutions demonstrate the influence of artificial intelligence in project management. Its algorithms can identify both problems and their solutions within the project management processes. These artificial intelligence-based technologies can solve complex problems, allowing project managers to focus more on creativity and innovation. This study aims to analyse, first the literature from bibliometric perspective and moving forward with the literature to identify enablers and barriers to artificial intelligence adoption in project management, offering insights into the state of research and practice into the studied domain. To conduct the literature search, two major databases were utilized, respectively Scopus and Web of Science. Out of 2123 records, 68 were retained for content analysis. The study highlights how artificial intelligence solutions proactively adapt to dynamic projects and help in optimizing resource allocation. Enablers such as natural language processes and machine learning applications are destined to stakeholders for analysis purposes. Lastly, the study also investigates the barriers that persist in widespread adoption of artificial intelligence solutions in project management. The literature emphasizes that artificial intelligence adoption in project management depends not only on technological readiness but also on developing organizational capabilities.

Suggested Citation

  • ADAM Ioana-Gabriela, 2025. "Artificial Intelligence Influence In Project Management: A Literature Review," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 77(3), pages 79-89, December.
    • Handle: RePEc:blg:reveco:v:77:y:2025:i:3:p:79-89
    DOI: 10.56043/reveco-2025-0027
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    References listed on IDEAS

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    1. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    2. Thordur Vikingur Fridgeirsson & Helgi Thor Ingason & Haukur Ingi Jonasson & Hildur Jonsdottir, 2021. "An Authoritative Study on the Near Future Effect of Artificial Intelligence on Project Management Knowledge Areas," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    3. Wauters, Mathieu & Vanhoucke, Mario, 2017. "A Nearest Neighbour extension to project duration forecasting with Artificial Intelligence," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1097-1111.
    4. Ivan Martins De Andrade & Cleonir Tumelero, 2022. "Increasing customer service efficiency through artificial intelligence chatbot," Revista de Gestão, Emerald Group Publishing Limited, vol. 29(3), pages 238-251, May.
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    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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