The use of Artificial Intelligence (AI) in creative disciplines, particularly architecture, has introduced a paradigm shift in how design concepts are developed and visualized. This research explores the integration of MidJourney generative scripts within the architectural design process. Using a hybrid methodology of qualitative observation and computational experimentation, this study evaluates how AI-driven image generation influences form exploration, material perception, and aesthetic decision-making. The main objective is to identify how AI-based generative systems, specifically MidJourney, can enhance conceptual creativity and accelerate the design iteration cycle in architectural practice. Unlike previous procedural models limited to parametric control, this study introduces an adaptive AI human feedback mechanism enabling continuous co-evolution between designer intent and machine generation. Our findings indicate that AI-assisted workflows enhance the production of innovative architectural compositions, offering greater visual diversity, while simultaneously enhancing creative efficiency and reducing design fatigue. Quantitatively, AI integration improved design iteration speed by 65% and increased aesthetic consistency scores from 78% to 91%, compared to traditional workflows. Integrating MidJourney generative scripting into architectural workflows creates a dynamic feedback loop between human intuition and machine creativity, leading to a new model of aesthetic co-creation that expands the boundaries of contemporary architectural design.
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