mlsanityData to 7 Oct 2026

Generative AI in the Construction Industry: Opportunities & Challenges

arXiv 2310.04427 ↗First posted 19 Sep 2023cs.AI cs.LGcited by 8

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Abstract (arXiv)

In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags in adoption. Recently, the emergence and rapid adoption of advanced large language models (LLM) like OpenAI's GPT, Google's PaLM, and Meta's Llama have shown great potential and sparked considerable global interest. However, the current surge lacks a study investigating the opportunities and challenges of implementing Generative AI (GenAI) in the construction sector, creating a critical knowledge gap for researchers and practitioners. This underlines the necessity to explore the prospects and complexities of GenAI integration. Bridging this gap is fundamental to optimizing GenAI's early-stage adoption within the construction sector. Given GenAI's unprecedented capabilities to generate human-like content based on learning from existing content, we reflect on two guiding questions: What will the future bring for GenAI in the construction industry? What are the potential opportunities and challenges in implementing GenAI in the construction industry? This study delves into reflected perception in literature, analyzes the industry perception using programming-based word cloud and frequency analysis, and integrates authors' opinions to answer these questions. This paper recommends a conceptual GenAI implementation framework, provides practical recommendations, summarizes future research questions, and builds foundational literature to foster subsequent research expansion in GenAI within the construction and its allied architecture & engineering domains.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 37 of its 165 references that are in the map. First posted on arXiv 19 Sep 2023.

Builds on

37 of 165 references.

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Citing papers per year: 2024: 2; 2025: 6.

8 papers.

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  4. 2024Blockchain Meets LLMs: A Living Survey on Bidirectional Integrationcited by 2
  5. 2025Can AI Master Construction Management (CM)? Benchmarking State-of-the-Art Large Language Models on CM Certification Examscited by 1
  6. 2025Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generationcited by 1
  7. 2025Evaluating AI-Driven Automated Map Digitization in QGIScited by 0
  8. 2025AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniquescited by 0