Published on: May 2026
COMPARATIVE ANALYSIS OF MANUAL VS AI-ASSISTED PROJECT SCHEDULING AND COST ESTIMATION IN CONSTRUCTION MANAGEMENT
Jyotsna N. Pawar
Prof. Mr. P. D. Aher
Article Status
Available Documents
Abstract
Construction industry is increasingly becoming digitalized but most residential projects are still being done using manual ways of project scheduling and cost estimation which is usually time consuming, inaccurate and subject to human error. This paper will provide a full comparative literature review of the hand-assisted and AI-assisted methods used in construction management and how they enhance the accuracy of the planning process, cost estimation, and resource optimization. The Python-based software application is created with the graphic user interface (GUI) to help the design of residential buildings safe and compliant with all the codes and to incorporate project scheduling and cost estimation features. The methodology is based on a hybrid that integrates traditional planning methods with AI-based models relying on machine learning and predictive analytics, both on real and simulated project data. The comparative evaluation is done using key performance indicators that include time accuracy, cost deviation, and efficiency of resource utilization. The suggested AI-based model will help to improve the accuracy of estimations, reduce delays, and optimize the use of resources in comparison with the manual approach. It is expected that the results will prove that AI-based solutions can enhance efficiency, reliability, and scalability in construction project management and facilitate informed decision-making and encourage the use of intelligent systems in the construction industry.
How to Cite this Paper
Pawar, J. N. (2026). Comparative Analysis of Manual Vs AI-Assisted Project Scheduling and Cost Estimation in Construction Management. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.174
Pawar, Jyotsna. "Comparative Analysis of Manual Vs AI-Assisted Project Scheduling and Cost Estimation in Construction Management." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.174.
Pawar, Jyotsna. "Comparative Analysis of Manual Vs AI-Assisted Project Scheduling and Cost Estimation in Construction Management." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.174.
Search & Index
References
- Keunwoo Lee et , “Structural performance of multi-storey modular buildings with bolt-free post-tensioned inter-module connections” Engineering Structures, Elsevier, Volume 342, 2025, 120511. https://doi.org/10.1016/j.engstruct.2025.120511
- Junjun Guo et , “SectionMCPy: Python programming-based moment-curvature analysis for cross-sections” SoftwareX, Elsevier, Volume 31, 2025, 102365. https://doi.org/10.1016/j.softx.2025.102365
- Hollis Williams, “LabDA: A Python GUI application for generating scaling with dimensional analysis” Software, Elsevier, Volume 31, 2025, 102322. https://doi.org/10.1016/j.softx.2025.102322
- Colin Caprani et al., “PySTRA: Python structural reliability analysis” Software, Elsevier, Volume 29, 2025, 102047.https://doi.org/10.1016/j.softx.2025.102047
- Paul Akuyenze et , “Revolutionizing starch modification: the role of genetic engineering in enhancing starch properties for sustainable industrial applications – A review” Discover, 2025. https://doi.org/10.1007/s44340-025-00033-y
- Yunpeng Hu et al., “Development and research of green building environment design and thermal energy management integrated system based on virtual reality technology” Springer, 2025. https://doi.org/10.1186/s42162-025-00544-2
- Shamim, M.M.I., Hamid, A.B.b.A., Nyamasvisva, T.E., Rafi, N.S.B., "Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models" Modelling, Volume 6, Page No. 35, 2025.https://doi.org/10.3390/modelling6020035
- Jayakannan, S.M., "Real-Time Dynamic Scheduling in Construction: An Artificial Intelligence Approach" World Journal of Advanced Research and Reviews, Volume 26, Page No. 2631-2636, 2025.https://doi.org/10.30574/wjarr.2025.26.2.1888
- Alrasheed, K., Al Ballat, M., Soliman, E., Albader, H., "Artificial Neural Network-Based Cost Estimation for Public Construction Projects in Kuwait" Journal of Engineering Research, Volume Online, Page Online, 2025.https://doi.org/10.1016/j.jer.2025.09.001
- Jafary, , Shojaei, D., Rajabifard, A., Ngo, T., "AI-Augmented Construction Cost Estimation: An Ensemble Natural Language Processing (NLP) Model to Align Quantity Take-Offs with Cost Indexes" International Journal of Construction Management, Volume Online, Page No. Online, 2025. https://doi.org/10.1080/15623599.2025.2558070
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: May 06 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.