GENERATIVE AI FOR CLIMATE-ADAPTIVE ARCHITECTURAL DESIGN: OPTIMIZING BUILDING ENERGY RESILIENCE IN PAKISTAN
Keywords:
Generative artificial intelligence; Climate-adaptive architecture; Building energy resilience; Sustainable building design; Building-performance simulation; PakistanAbstract
The rapid development of generative artificial intelligence (GenAI) has created new opportunities for optimizing architectural design in response to climate and energy challenges. This study examined the role of GenAI-assisted architectural design in enhancing building energy resilience in Pakistan. A quantitative, cross-sectional research design was employed, and data were collected from 300 architects, engineers, academics, energy consultants, and building professionals through a structured questionnaire. The study examined four dimensions of GenAI-assisted design: AI-Assisted Passive Design Optimization, Climate-Responsive Design Generation, Building-Envelope Optimization, and AI-Enabled Climate and Energy Scenario Simulation. Architectural AI Competence was examined as a moderating variable, while Building Energy Resilience was the dependent variable. Descriptive statistics, correlation analysis, multiple regression, and moderation analysis were employed to test the proposed relationships. The findings indicated that all four GenAI-assisted design dimensions had significant positive effects on building energy resilience, with Climate-Responsive Design Generation demonstrating the strongest effect. Architectural AI Competence also significantly strengthened the relationship between GenAI-assisted architectural design and building energy resilience. The findings suggest that GenAI can support climate-adaptive architectural decision-making by facilitating rapid design exploration, passive-design optimization, envelope performance improvement, and scenario-based evaluation. The study contributes to Resilience Theory by conceptualizing AI-enabled architectural design as a proactive mechanism for strengthening building resistance, adaptability, and robustness under climatic and energy disturbances. The study recommends integrating GenAI with local climate data, building-performance simulation, professional expertise, and Pakistan's Energy Conservation Building Code to develop more resilient and energy-responsive buildings.


