AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects

Jiajuan Li; Xia Wang; Chengzhong Liu; Yaxin Chen; Le Fang; Yingqing Xu; Lie Zhang; Kun Pyo Lee; Stephen Jia Wang

doi:10.1145/3772318.3791643

AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects

Jiajuan Li
, Xia Wang
, Chengzhong Liu
, Yaxin Chen
, Le Fang
, Yingqing Xu
, Lie Zhang
, Kun Pyo Lee
, Stephen Jia Wang (Corresponding Author)

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

Senior architects are pivotal in shaping architectural projects, yet integrating Generative AI (GenAI) into their workflows presents notable challenges. A formative study (N=11) identified key pain points in their early concept design process. To address these, we developed EarlyArchi, a GenAI-driven system supporting automated concept generation and evaluation. In a within-subject study (N=13), participants used EarlyArchi for early-stage design tasks. Results showed enhanced perceived creativity, improved design competency, and more efficient ideation. However, concerns emerged regarding controllability and domain-specific accuracy, highlighting the need for features that preserve professional autonomy and trust. Further analysis revealed three GenAI involvement modes—fully AI-driven, GenAI-led, and human-led—emphasizing the importance of adaptive role allocation in balancing creative exploration with expert leadership. These findings offer insights into supporting senior architects through GenAI while identifying key considerations for designing future human–AI co-creation systems.

Original language	English
Title of host publication	CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Editors	Nuria Oliver, David A. Shamma, Heloisa Candello, Pablo Cesar, Pedro Lopes, Alessandro Bozzon, Thomas Kosch, Vera Liao, Xiaojuan Ma, Valentino Artizzu, Fiona Draxler, Gustavo Lopez, Anke V. Reinschluessel, Xin Tong, Phoebe O. Toups Dugas
Publisher	Association for Computing Machinery (ACM)
Pages	1-22
Number of pages	22
ISBN (Electronic)	9798400722783
DOIs	https://doi.org/10.1145/3772318.3791643
Publication status	Published - 13 Apr 2026

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Keywords

Creativity Support
Early Design Stages
Generative AI
Human-AI Collaboration
Senior Architects

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

More information

10.1145/3772318.3791643

Cite this

Li, J., Wang, X., Liu, C., Chen, Y., Fang, L., Xu, Y., Zhang, L., Lee, K. P., & Wang, S. J. (2026). AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects. In N. Oliver, D. A. Shamma, H. Candello, P. Cesar, P. Lopes, A. Bozzon, T. Kosch, V. Liao, X. Ma, V. Artizzu, F. Draxler, G. Lopez, A. V. Reinschluessel, X. Tong, & P. O. Toups Dugas (Eds.), CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-22). Article 85 (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery (ACM). https://doi.org/10.1145/3772318.3791643

Li, Jiajuan ; Wang, Xia ; Liu, Chengzhong et al. / AI for Creativity : A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects. CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. editor / Nuria Oliver ; David A. Shamma ; Heloisa Candello ; Pablo Cesar ; Pedro Lopes ; Alessandro Bozzon ; Thomas Kosch ; Vera Liao ; Xiaojuan Ma ; Valentino Artizzu ; Fiona Draxler ; Gustavo Lopez ; Anke V. Reinschluessel ; Xin Tong ; Phoebe O. Toups Dugas. Association for Computing Machinery (ACM), 2026. pp. 1-22 (Conference on Human Factors in Computing Systems - Proceedings).

@inproceedings{3da6b8e937174b3488591be7e254bd85,

title = "AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects",

abstract = "Senior architects are pivotal in shaping architectural projects, yet integrating Generative AI (GenAI) into their workflows presents notable challenges. A formative study (N=11) identified key pain points in their early concept design process. To address these, we developed EarlyArchi, a GenAI-driven system supporting automated concept generation and evaluation. In a within-subject study (N=13), participants used EarlyArchi for early-stage design tasks. Results showed enhanced perceived creativity, improved design competency, and more efficient ideation. However, concerns emerged regarding controllability and domain-specific accuracy, highlighting the need for features that preserve professional autonomy and trust. Further analysis revealed three GenAI involvement modes{\textemdash}fully AI-driven, GenAI-led, and human-led{\textemdash}emphasizing the importance of adaptive role allocation in balancing creative exploration with expert leadership. These findings offer insights into supporting senior architects through GenAI while identifying key considerations for designing future human{\textendash}AI co-creation systems.",

keywords = "Creativity Support, Early Design Stages, Generative AI, Human-AI Collaboration, Senior Architects",

author = "Jiajuan Li and Xia Wang and Chengzhong Liu and Yaxin Chen and Le Fang and Yingqing Xu and Lie Zhang and Lee, \{Kun Pyo\} and Wang, \{Stephen Jia\}",

note = "Publisher Copyright: {\textcopyright} 2026 Copyright held by the owner/author(s).",

year = "2026",

month = apr,

day = "13",

doi = "10.1145/3772318.3791643",

language = "English",

series = "Conference on Human Factors in Computing Systems - Proceedings",

publisher = "Association for Computing Machinery (ACM)",

pages = "1--22",

editor = "Nuria Oliver and Shamma, \{David A.\} and Heloisa Candello and Pablo Cesar and Pedro Lopes and Alessandro Bozzon and Thomas Kosch and Vera Liao and Xiaojuan Ma and Valentino Artizzu and Fiona Draxler and Gustavo Lopez and Reinschluessel, \{Anke V.\} and Xin Tong and \{Toups Dugas\}, \{Phoebe O.\}",

booktitle = "CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems",

address = "United States",

}

Li, J, Wang, X, Liu, C, Chen, Y, Fang, L, Xu, Y, Zhang, L, Lee, KP & Wang, SJ 2026, AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects. in N Oliver, DA Shamma, H Candello, P Cesar, P Lopes, A Bozzon, T Kosch, V Liao, X Ma, V Artizzu, F Draxler, G Lopez, AV Reinschluessel, X Tong & PO Toups Dugas (eds), CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems., 85, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery (ACM), pp. 1-22. https://doi.org/10.1145/3772318.3791643

AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects. / Li, Jiajuan; Wang, Xia; Liu, Chengzhong et al.
CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. ed. / Nuria Oliver; David A. Shamma; Heloisa Candello; Pablo Cesar; Pedro Lopes; Alessandro Bozzon; Thomas Kosch; Vera Liao; Xiaojuan Ma; Valentino Artizzu; Fiona Draxler; Gustavo Lopez; Anke V. Reinschluessel; Xin Tong; Phoebe O. Toups Dugas. Association for Computing Machinery (ACM), 2026. p. 1-22 85 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - AI for Creativity

T2 - A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects

AU - Li, Jiajuan

AU - Wang, Xia

AU - Liu, Chengzhong

AU - Chen, Yaxin

AU - Fang, Le

AU - Xu, Yingqing

AU - Zhang, Lie

AU - Lee, Kun Pyo

AU - Wang, Stephen Jia

PY - 2026/4/13

Y1 - 2026/4/13

N2 - Senior architects are pivotal in shaping architectural projects, yet integrating Generative AI (GenAI) into their workflows presents notable challenges. A formative study (N=11) identified key pain points in their early concept design process. To address these, we developed EarlyArchi, a GenAI-driven system supporting automated concept generation and evaluation. In a within-subject study (N=13), participants used EarlyArchi for early-stage design tasks. Results showed enhanced perceived creativity, improved design competency, and more efficient ideation. However, concerns emerged regarding controllability and domain-specific accuracy, highlighting the need for features that preserve professional autonomy and trust. Further analysis revealed three GenAI involvement modes—fully AI-driven, GenAI-led, and human-led—emphasizing the importance of adaptive role allocation in balancing creative exploration with expert leadership. These findings offer insights into supporting senior architects through GenAI while identifying key considerations for designing future human–AI co-creation systems.

AB - Senior architects are pivotal in shaping architectural projects, yet integrating Generative AI (GenAI) into their workflows presents notable challenges. A formative study (N=11) identified key pain points in their early concept design process. To address these, we developed EarlyArchi, a GenAI-driven system supporting automated concept generation and evaluation. In a within-subject study (N=13), participants used EarlyArchi for early-stage design tasks. Results showed enhanced perceived creativity, improved design competency, and more efficient ideation. However, concerns emerged regarding controllability and domain-specific accuracy, highlighting the need for features that preserve professional autonomy and trust. Further analysis revealed three GenAI involvement modes—fully AI-driven, GenAI-led, and human-led—emphasizing the importance of adaptive role allocation in balancing creative exploration with expert leadership. These findings offer insights into supporting senior architects through GenAI while identifying key considerations for designing future human–AI co-creation systems.

KW - Creativity Support

KW - Early Design Stages

KW - Generative AI

KW - Human-AI Collaboration

KW - Senior Architects

UR - https://www.scopus.com/pages/publications/105038650025

U2 - 10.1145/3772318.3791643

DO - 10.1145/3772318.3791643

M3 - Conference article published in proceeding or book

T3 - Conference on Human Factors in Computing Systems - Proceedings

SP - 1

EP - 22

BT - CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

A2 - Oliver, Nuria

A2 - Shamma, David A.

A2 - Candello, Heloisa

A2 - Cesar, Pablo

A2 - Lopes, Pedro

A2 - Bozzon, Alessandro

A2 - Kosch, Thomas

A2 - Liao, Vera

A2 - Ma, Xiaojuan

A2 - Artizzu, Valentino

A2 - Draxler, Fiona

A2 - Lopez, Gustavo

A2 - Reinschluessel, Anke V.

A2 - Tong, Xin

A2 - Toups Dugas, Phoebe O.

PB - Association for Computing Machinery (ACM)

ER -

Li J, Wang X, Liu C, Chen Y, Fang L, Xu Y et al. AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects. In Oliver N, Shamma DA, Candello H, Cesar P, Lopes P, Bozzon A, Kosch T, Liao V, Ma X, Artizzu V, Draxler F, Lopez G, Reinschluessel AV, Tong X, Toups Dugas PO, editors, CHI 2026 - Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM). 2026. p. 1-22. 85. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3772318.3791643

AI for Creativity: A GenAI-Based Approach for Early Concept Design and Its Impact on Senior Architects

Abstract

Publication series

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this