Evaluating AI-driven predictions for the interior design of 2070 technology stores
Submitted: 2025-11-19
|Accepted: 2026-05-26
|Published: 2026-06-09
Copyright (c) 2026 VITRUVIO - International Journal of Architectural Technology and Sustainability
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Keywords:
AI-driven design forecasting, artificial intelligence in architecture, future retail design, human-centered design, technology store interiors
Supporting agencies:
Abstract:
This study explores the role of AI-powered predictions in shaping the interior design of technology stores projected for the year 2070, with a particular focus on emerging retail trends and the integration of artificial intelligence into architectural design processes. The research sought to understand not only how AI systems generate design proposals, but also how these outputs align with established professional standards. To achieve this, a structured survey was conducted with a group of architects and interior designers. Participants were asked to evaluate AI-generated visualizations, assessing their compliance with standard design criteria. The collected expert evaluations were then systematically compared with parallel assessments produced by ChatGPT 4.0, creating a basis for measuring similarities, differences, and potential biases between human and AI perspectives. Critical design parameters were carefully analyzed, including floor durability, the effective use of display areas, integration of advanced technology into spatial solutions, circulation efficiency, and considerations of user comfort and well-being. The results demonstrate clear differences between human and AI assessments, alongside notable professional divergences among human evaluators. While AI showed notable strength in areas such as technology integration and circulation optimization, human professionals identified significant weaknesses in other domains, particularly regarding customer orientation systems, signage clarity, and the organization of checkout areas. Furthermore, comparative analyses between professional groups revealed that architects placed a significantly higher emphasis on material diversity and circulation efficiency compared to interior designers, highlighting a professional prioritization of structural and flow-related parameters. A Bland-Altman analysis further revealed a systematic bias, showing that AI-generated evaluations were approximately 9% more positive compared to those of human experts. This suggests that AI tends to adopt a more optimistic lens, whereas human experts approach the same criteria with a more cautious and conservative stance. The study emphasizes the necessity of integrating human expertise into AI-driven design processes, both to ensure methodological rigor and to uphold ethical responsibility. Ultimately, by combining computational efficiency with human judgment, this research contributes to the development of more innovative, resilient, and human-centered design strategies for future retail environments.
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