# Investigating the use of ChatGPT for the scheduling of construction projects

arXiv: https://arxiv.org/abs/2302.02805 · HTML: https://mlsanity.com/paper/2302.02805/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 38 references that are in the map.
- First posted on arXiv 27 Jan 2023.

## Builds on (most cited first, 4 of 4)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models](https://mlsanity.com/paper/2010.15036/) (2020)

## Built on by (most cited first, 17 of 17)

- [Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models](https://mlsanity.com/paper/2304.01852/) (2023)
- [One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era](https://mlsanity.com/paper/2304.06488/) (2023)
- [GPT Models in Construction Industry: Opportunities, Limitations, and a Use Case Validation](https://mlsanity.com/paper/2305.18997/) (2023)
- [Robot-Enabled Construction Assembly with Automated Sequence Planning based on ChatGPT: RoboGPT](https://mlsanity.com/paper/2304.11018/) (2023)
- [MyCrunchGPT: A chatGPT assisted framework for scientific machine learning](https://mlsanity.com/paper/2306.15551/) (2023)
- [Generative AI in the Construction Industry: Opportunities & Challenges](https://mlsanity.com/paper/2310.04427/) (2023)
- [CEQuest: Benchmarking Large Language Models for Construction Estimation](https://mlsanity.com/paper/2508.16081/) (2025)
- [AECBench: A Hierarchical Benchmark for Knowledge Evaluation of Large Language Models in the AEC Field](https://mlsanity.com/paper/2509.18776/) (2025)
- [Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competition](https://mlsanity.com/paper/2305.06934/) (2023)
- [Foundation Models for Autonomous Robots in Unstructured Environments](https://mlsanity.com/paper/2407.14296/) (2024)
- [Leveraging Large Language Models for Enhancing Public Transit Services](https://mlsanity.com/paper/2410.14147/) (2024)
- [Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model](https://mlsanity.com/paper/2410.19262/) (2024)
- [Prompt to Protection: A Comparative Study of Multimodal LLMs in Construction Hazard Recognition](https://mlsanity.com/paper/2506.07436/) (2025)
- [Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry](https://mlsanity.com/paper/2310.05414/) (2023)
- [Evaluating the Inclusiveness of Artificial Intelligence Software in Enhancing Project Management Efficiency -- A Review](https://mlsanity.com/paper/2311.11159/) (2023)
- [Generative AI and the History of Architecture](https://mlsanity.com/paper/2312.15106/) (2023)
- [A Large Language Model for Disaster Structural Reconnaissance Summarization](https://mlsanity.com/paper/2602.11588/) (2026)

## Abstract (arXiv)

Large language models such as ChatGPT have the potential to revolutionize the construction industry by automating repetitive and time-consuming tasks. This paper presents a study in which ChatGPT was used to generate a construction schedule for a simple construction project. The output from ChatGPT was evaluated by a pool of participants that provided feedback regarding their overall interaction experience and the quality of the output. The results show that ChatGPT can generate a coherent schedule that follows a logical approach to fulfill the requirements of the scope indicated. The participants had an overall positive interaction experience and indicated the great potential of such a tool to automate many preliminary and time-consuming tasks. However, the technology still has limitations, and further development is needed before it can be widely adopted in the industry. Overall, this study highlights the potential of using large language models in the construction industry and the need for further research.