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AI-Enabled Building Design Collaboration: Insights from Australian Adoption and Implementation

Year: 2026

Type: article

Abstract: The integration of Artificial Intelligence (AI) into Architecture, Engineering, and Construction (AEC) practice is reshaping building design processes and collaborative workflows. However, AI’s role as a design collaborator remains poorly understood across educational and professional contexts. To address this gap, this study conducts an empirical survey of built environment students, academics, and professionals. Collectively, the study develops a comprehensive view of AI’s role in building design collaboration. The survey findings (n = 155) show widespread use of Large Language Models (LLMs) and image-generation tools across design education and practice, especially for creative and documentation-related tasks. While AI is valued for enhancing productivity and streamlining workflows, respondents also express concerns around technology dependency, data privacy, bias, and trust. This study contributes dual-perspective insights—encompassing both theoretical foundations and contemporary perceptions—into AI’s evolution towards transparent and multimodal design collaboration. The findings support a more structured and context-aware integration of AI tools into building design practice.

Source: Buildings

DOI: 10.3390/buildings16061126

Authors: Ju Hyun Lee, Michael J. Ostwald

Institution: UNSW Sydney

Language: English

Topic: Architecture and Computational Design

Subfield: Architecture

Field: Engineering

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $3,137