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Journals / Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji / 2026 / Cilt: 14 Sayı: 2

Comprehensive Review of Artificial Intelligence Applications in Project Management

Proje Yönetiminde Yapay Zekâ Uygulamalarının Kapsamlı İncelemesi

Elif Ece Elmas(MİLLİ SAVUNMA ÜNİVERSİTESİ ALPASLAN SAVUNMA BİLİMLERİ ENSTİTÜSÜ)0000-0001-9804-0112
Pages
865–892
Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This synthesis provides practitioners and researchers with an integrated understanding of how AI is reshaping project management practices while highlighting untapped opportunities and potential limitations that warrant further investigation.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Artificial Intelligence (AI) is reshaping project management, fundamentally changing how we plan, execute, and complete projects.
📊
Key Findings & Data:This comprehensive review systematically examines the current state and future trajectories of AI applications across all project management performance domains.
💡
Conclusion & Impact:This synthesis provides practitioners and researchers with an integrated understanding of how AI is reshaping project management practices while highlighting untapped opportunities and potential limitations that warrant further investigation.
🔬Design:Review & Systematic Survey
📍Scope:2020-2025 Verileri
⚙️Variables:Yapay zekâ · proje yönetimi · makine öğrenimi

Abstract

Artificial Intelligence (AI) is reshaping project management, fundamentally changing how we plan, execute, and complete projects. This comprehensive review systematically examines the current state and future trajectories of AI applications across all project management performance domains. Drawing exclusively from recent literature (2020-2025), we analyze the evolution of AI in project management and categorize implementations across machine learning, natural language processing, fuzzy logic systems, expert systems, hybrid approaches, and emerging generative AI technologies. The review reveals that AI is progressively enhancing decision-making processes, automating routine tasks, optimizing resource allocation, improving risk assessment, facilitating team formation, and enabling data-driven stakeholder engagement. Furthermore, we identify and discuss implementation challenges, ethical considerations, and future research directions. This synthesis provides practitioners and researchers with an integrated understanding of how AI is reshaping project management practices while highlighting untapped opportunities and potential limitations that warrant further investigation.

Özet

Yapay Zekâ (YZ), proje yönetimini yeniden şekillendirmekte; projeleri planlama, yürütme ve tamamlama biçimimizi temelden değiştirmektedir. Bu kapsamlı inceleme, tüm proje yönetimi performans alanlarında YZ uygulamalarının mevcut durumunu ve gelecekteki yönelimlerini sistematik olarak ele almaktadır. Yalnızca güncel literatürden (2020-2025) yararlanılarak, YZ'nin proje yönetimindeki evrimi analiz edilmekte ve uygulamalar; makine öğrenimi, doğal dil işleme, bulanık mantık sistemleri, uzman sistemler, hibrit yaklaşımlar ve gelişmekte olan üretken YZ teknolojileri bağlamında sınıflandırılmaktadır. İnceleme; YZ'nin karar verme süreçlerini giderek iyileştirdiğini, rutin görevleri otomatikleştirdiğini, kaynak tahsisini optimize ettiğini, risk değerlendirmesini geliştirdiğini, takım oluşturmayı kolaylaştırdığını ve veri odaklı paydaş katılımına olanak tanıdığını ortaya koymaktadır. Ayrıca, uygulama zorlukları, etik hususlar ve gelecekteki araştırma yönelimleri belirlenmekte ve tartışılmaktadır. Bu çalışma, uygulayıcılara ve araştırmacılara YZ'nin proje yönetimi uygulamalarını nasıl yeniden şekillendirdiğine dair bütünleşik bir anlayış sunarken, daha fazla araştırma gerektiren henüz değerlendirilmemiş fırsatları ve potansiyel sınırlamaları da vurgulamaktadır.

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Cite This Article

Elmas, E. E. (2026). Comprehensive Review of Artificial Intelligence Applications in Project Management. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, Cilt: 14 Sayı: 2, 865–892. https://doi.org/10.29109/gujsc.1923665

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References (53)

  1. Ç. Elmas, J. Babayev, “Can Artificial Intelligence Replace Project Manager?”, Project Management in the Development of Society: Conference theme: Project Management in the conditions of transition to the behavior economics, Kyiv National University of Construction and Architecture, 95-97, 2020.
  2. S. Bushuyev, D. Bushuiev, V. Bushuieva, N. Bushuyeva, J. Tykchonovych, “Strategic Project Management Development Under Influence of Artificial Intelligence”, Bulletin of NTU "KhPI". Series: Strategic Management, Portfolio, Program and Project Management, 2(2), 53-58, 2024.
  3. Pala, İ., & Koçer, A. (2025). Uydu Verileri ile Güneş Işınımı Tahmininde Farklı Makine Öğrenmesi̇ Yöntemlerinin Kullanımı. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 13(4), 1728-1739. https://doi.org/10.29109/gujsc.1710003.
  4. Ç. Elmas, “The applications of generative artificial intelligence in project management”, Integrated strategic management, portfolio, program, and project management: Proceedings of the XVIII International Scientific-Practical Conference, National Technical University "Kharkiv Polytechnic Institute", 28-34, 2025.
  5. M. Pourmojahed, P. Rahat, “Adopting and Implementing AI in Organizations: A Review from a Project Management Perspective”, Journal of Project Management, 9(1), 23-42, 2024.
  6. Page M J, McKenzie J E, Bossuyt P M, Boutron I, Hoffmann T C, Mulrow C D et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews BMJ 2021; 372: n71 doi:10.1136/bmj. n71.
  7. PMI (Project Management Institute), A Guide to the Project Management Body of Knowledge (PMBOK® Guide), Project Management Institute, Seventh Edition, 2021.
  8. M. W. Hsu, N. Dacre, P. K. Senyo, “Identifying inter-project relationships with recurrent neural networks: Towards an AI framework of project success prediction”, Proceedings of the British Academy of Management Conference 2021 (BAM2021), 1-9, 2021.
  9. I. Lishner, A. Shtub, “Using an artificial neural network for improving the prediction of project duration”, Mathematics, 10(22), 4182, 2022.
  10. E. Matel, F. Vahdatikhaki, vd., “An artificial neural network approach for cost estimation of engineering services”, International Journal of Construction Management, 22(10), 1934-1943, 2022.
  11. Z. H. Ali, A. M. Burhan, “Hybrid machine learning approach for construction cost estimation: An evaluation of extreme gradient boosting model”, Asian Journal of Civil Engineering, 24(7), 2267-2280, 2023.
  12. J.-Y. Yeh, C.-H. Chen, “A machine learning approach to predict the success of crowdfunding fintech project”, Journal of Enterprise Information Management, 35(6), 1678-1696, 2022.
  13. A. Natarajan, “Reference class forecasting and machine learning for improved offshore oil and gas megaproject planning: Methods and application”, Project Management Journal, 53(3), 270-293, 2022.
  14. Paleyes, R.-G. Urma, N. D. Lawrence, “Challenges in deploying machine learning: a survey of case studies”, ACM Computing Surveys, 55(6), 114, 2022.
  15. M. Blomster, T. Koivumäki, “Exploring the resources, competencies, and capabilities needed for successful machine learning projects in digital marketing”, Information Systems and e-Business Management, 20(1), 1-26, 2022.
  16. M. Balasubramani, M. R. Palav, K. T. V. Rao, R. Maranan, A. R. Salve, “Construction Project Management Using Natural Language Processing Technology”, 2023 6th International Conference on Contemporary Computing and Informatics (IC3I), IEEE, 1731-1736, 2023.
  17. A. A. Vasiliev, A. V. Goryachev, “Application of text mining technology to solve project management problems”, 2022 XXV International Conference on Soft Computing and Measurements (SCM), IEEE, 78-81, 2022.
  18. H. Zhou, B. Gao, S. Tang, B. Li, S. Wang, “Intelligent detection on construction project contract missing clauses based on deep learning and NLP”, Engineering, Construction and Architectural Management, 32(1), 387-407, 2025.
  19. L. Zhang, H. Yao, Y. Fu, Y. Chen, “Comparing subjective and objective measurements of contract complexity in influencing construction project performance: Survey versus machine learning”, Journal of Management in Engineering, 39(4), 04023022, 2023.
  20. N. S. Manoj, Analyzing Stakeholder Feedback Using AI, Yüksek Lisans Tezi, Harrisburg University of Science and Technology, 2024.
  21. Hess, S. Kunz, “Could ChatGPT be Your New Project Management Assistant? Using AI Chatbots to Support Project Management Tasks”, Advances on Digital Transformation (DIGITAL 2023), Porto, Portugal, 10-17, 2023.
  22. N. Rane, “Potential role and challenges of ChatGPT and similar generative artificial intelligence in architectural engineering”, International Journal of Artificial Intelligence and Applications, 2023.
  23. J. C. Weng, “Putting intellectual robots to work: Implementing generative AI tools in project management”, Harvard Business Review Digital Articles, 2023(June), 1-8, 2023.
  24. E. Plebankiewicz, K. Zima, vd., “Modelling of time, cost and risk of construction with using fuzzy logic”, Journal of Civil Engineering and Management, 27(6), 412-426, 2021.
  25. E. Senić, M. Dobrodolac, Z. Stojadinović, “Predicting Extension of Time and Increasing Contract Price in Road Infrastructure Projects Using a Sugeno Fuzzy Logic Model”, Mathematics, 12(16), 1-22, 2024.
  26. J. E. Ricardo, A. J. R. Fernández, vd., “Compensatory Fuzzy Logic with Single Valued Neutrosophic Numbers in the Analysis of University Strategic Management”, International Journal of Neutrosophic Science, 19(1), 48-56, 2022.
  27. O. Dudnyk, Z. Sokolovska, “Application of fuzzy expert systems in IT project management”, Project Management- New Trends and Challenges, IntechOpen, 2022.
  28. N. B. Kultin, “Expert systems in innovation project management: architecture and application”, International Conference System Analysis in Engineering and Control, Springer, 249-258, 2021.
  29. A. Shehadeh, O. Alshboul, K. F. Al-Shboul, vd., “An expert system for highway construction: Multi-objective optimization using enhanced particle swarm for optimal equipment management”, Expert Systems with Applications, 238, 122311, 2024.
  30. C. H. Go, F. Agusalim, W. Wan Hussin, E. J. T. Chang, vd., “Moving Towards Automation and Artificial Intelligence in Managing HSE Risks and Incidents”, Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 2023.
  31. H. Abbasianjahromi, M. Aghakarimi, “Safety performance prediction and modification strategies for construction projects via machine learning techniques”, Engineering, Construction and Architectural Management, 30(10), 4427-4447, 2023.
  32. S. W. Choi, E. B. Lee, J. H. Kim, “The Engineering Machine-Learning Automation Platform (EMAP): A Big-Data-Driven AI Tool for Contractors' Sustainable Management Solutions for Plant Projects”, Sustainability, 13(18), 10384, 2021.
  33. S. Monshizada, H. Sarbazhosseini, M. Mohammadi, “Development of Artificial Intelligence Systems in terms of People-Process-Data-Technology (2PDT)”, Pacific Asia Journal of the Association for Information Systems, 15(1), 23-47, 2023.
  34. S. Goyal, H. Jha, A. Gupta, “Automation in Project Management 4.0 with Artificial Intelligence”, Proceedings of 3rd International Conference on Machine Learning, IoT, Smart Cities and Applications (ICMISC 2022), Springer, Singapore, 723-731, 2023.
  35. N. G. Castellanos, “Generative AI for Dynamic Risk Scenario Simulation in Project Management”, Journal of Advanced Computing Systems, 3(5), 13-20, 2023.
  36. A. Barcaui, A. Monat, “Who is better in project planning? Generative artificial intelligence or project managers?”, Project Leadership and Society, 4, 100104, 2023.
  37. M. Felicetti, D. Rao, S. Ammirato, “Generative AI Supporting Project Management: A Vertical Integration Using OpenAI MyGPT”, Big Data Empowered Project Management, Springer, 2025.
  38. M. A. Hamada, A. Abdallah, M. Kasem, M. Abokhalil, “Neural network estimation model to optimize timing and schedule of software projects”, 2021 IEEE International Conference on Smart Information Systems and Technologies (SIST), IEEE, 1-5, 2021.
  39. F. ul Hassan, T. Nguyen, T. Le, C. Le, “Automated prioritization of construction project requirements using machine learning and fuzzy Failure Mode and Effects Analysis (FMEA)”, Automation in Construction, 148, 104754, 2023.
  40. O. T. Akinyokun, M. K. Onifade, vd., “An Artificial Intelligence Framework for Project Planning and Control using Decision Tree Analysis and Artificial Neural Network”, 2024 International Conference on Science, Engineering and Business for Sustainable Development Goals (SEB4SDG), IEEE, 1-6, 2024.
  41. A. Mohammed, N. Al Busaeedi, A. A. Mohamed, H. Al Marzouqi, M. Al Marzooqi, “Smart project management system (SPMS)-an integrated and predictive solution for proactively managing oil & gas client projects”, Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, 2022.
  42. N. Gordon, K. W. Moore, “The effects of artificial intelligence (AI) enabled personality assessments during team formation on team cohesion”, NeuroIS Retreat, 311-318, 2022.
  43. N. Khan, D. A. Siddiqui, “Issues in Implementation of Artificial Intelligence in Project Management in Pakistan”, SSRN Electronic Journal, 2024.
  44. N. İ. Yurttakal, “Man-Hour Estimation Model Development in BIM-Based Projects with Machine Learning-Regression Algorithms”, Orclever Proceedings of Research and Creative Studies, 2(1), 15-26, 2023.
  45. H. Hegazy, J. Zhang, “Artificial intelligence for enhanced decision-making in construction”, Digital Transformation in the Construction Industry, Editör: Hamledari, H., García de Soto, B., Elsevier, 441-462, 2025.
  46. J. I. Santos, M. Pereda, V. Ahedo, J. M. Galán, “Explainable machine learning for project management control”, Computers & Industrial Engineering, 180, 109261, 2023.
  47. I. Taboada, A. Daneshpajouh, N. Toledo, T. De Vass, “Artificial intelligence enabled project management: a systematic literature review”, Applied Sciences, 13(8), 5014, 2023.
  48. S. Uddin, S. Yan, H. Lu, “Machine learning and deep learning in project analytics: methods, applications and research trends”, Production Planning & Control, 36(1), 1-25, 2025.
  49. A. Waqar, “Intelligent decision support systems in construction engineering: An artificial intelligence and machine learning approaches”, Expert Systems with Applications, 249, 123503, 2024.
  50. J. E. C. Rasmuss, E. Tømte, “Artificial Intelligence as a Tool for Project Decision-Making Support”, Project Management Journal, 53(5), 467-482, 2022.
  51. G. J. Miller, “Artificial Intelligence Project Success Factors—Beyond the Ethical Principles”, Information Technology for Management: Business and Social Issues. FedCSIS-AIST ISM 2021, Editör: Ziemba, E., Chmielarz, W., Springer, 65-96, 2022.
  52. R. Hoda, H. Dam, C. Tantithamthavorn, P. Thongtanunam, M. A. Storey, “Augmented agile: Human-centered ai-assisted software management”, IEEE Software, 40(4), 106-109, 2023.
  53. K. Bainey, AI-Driven Project Management: Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success, Wiley-IEEE Press, 2024.