Perception and Adoption of AI-Generated Designs Among Registered Architects in Lagos, Nigeria

The rapid emergence of artificial intelligence (AI) is transforming architectural design processes, yet empirical evidence on Architects’ perception and adoption of AI-generated designs in developing-country contexts remains limited. This study investigates registered Architects’ perceptions of AI-generated designs and examines the factors influencing the adoption and application of AI tools in architectural practice in Lagos, Nigeria. A mixed-method research design was employed, combining a cross-sectional questionnaire survey with semi-structured interviews. Data were obtained from 117 of the 277 registered Architects practising in Lagos State and analysed using descriptive statistics, content analysis and thematic analysis, with triangulation used to integrate quantitative and qualitative findings. The findings reveal high awareness and understanding of AI technologies (M=3.19, SD=1.28), but relatively limited practical competence and experience. Architects predominantly perceive AI-generated designs as conceptual and creative aids (M=3.23, SD=1.24), rather than finished professional outputs. Consequently, AI adoption is concentrated in early design activities, particularly rapid client visualisation and the generation of design alternatives (M=3.15 each). Integration into detailed design and documentation remains constrained by interoperability challenges with CAD and BIM platforms (M=2.97, SD=1.08). Ethical concerns surrounding authorship, accountability, professional responsibility and contextual relevance further moderate adoption, while perceived usefulness, workflow efficiency, innovation and creative support encourage it. Conversely, concerns about reliability, practice is shaped by interacting technological, professional and contextual factors. It highlights the need for targeted professional training, appropriate regulatory frameworks and context-sensitive strategies for responsible AI integration into architectural education and practice.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-29
DOI
https://doi.org/10.5281/zenodo.23062598
Primary Topic
BIM and Construction Integration
Type
article
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article

Perception and Adoption of AI-Generated Designs Among Registered Architects in Lagos, Nigeria

Ifeoluwa Akande, AnjolaJesu Joy Oso, Sagesse Ekenedilichukwu Godwin, Anthonia Ilamosi Akieneme et al.
Zenodo (CERN European Organization for Nuclear Research)
BIM and Construction Integration
article

Perception and Adoption of AI-Generated Designs Among Registered Architects in Lagos, Nigeria

Ifeoluwa Akande, AnjolaJesu Joy Oso, Sagesse Ekenedilichukwu Godwin, Anthonia Ilamosi Akieneme, Inioluwa Joseph Akinteye
article en

Abstract

The rapid emergence of artificial intelligence (AI) is transforming architectural design processes, yet empirical evidence on Architects’ perception and adoption of AI-generated designs in developing-country contexts remains limited. This study investigates registered Architects’ perceptions of AI-generated designs and examines the factors influencing the adoption and application of AI tools in architectural practice in Lagos, Nigeria. A mixed-method research design was employed, combining a cross-sectional questionnaire survey with semi-structured interviews. Data were obtained from 117 of the 277 registered Architects practising in Lagos State and analysed using descriptive statistics, content analysis and thematic analysis, with triangulation used to integrate quantitative and qualitative findings. The findings reveal high awareness and understanding of AI technologies (M=3.19, SD=1.28), but relatively limited practical competence and experience. Architects predominantly perceive AI-generated designs as conceptual and creative aids (M=3.23, SD=1.24), rather than finished professional outputs. Consequently, AI adoption is concentrated in early design activities, particularly rapid client visualisation and the generation of design alternatives (M=3.15 each). Integration into detailed design and documentation remains constrained by interoperability challenges with CAD and BIM platforms (M=2.97, SD=1.08). Ethical concerns surrounding authorship, accountability, professional responsibility and contextual relevance further moderate adoption, while perceived usefulness, workflow efficiency, innovation and creative support encourage it. Conversely, concerns about reliability, practice is shaped by interacting technological, professional and contextual factors. It highlights the need for targeted professional training, appropriate regulatory frameworks and context-sensitive strategies for responsible AI integration into architectural education and practice.

Zenodo (CERN European Organization for Nuclear Research)
Bells University of Technology (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
BIM and Construction Integration
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