As generative AI accelerates across creative industries, architecture is quietly undergoing its own transformation. For architectural designer Danny Loza, the technology is less a disruptive threat and more a powerful addition to the toolbox—especially in the earliest stages of design.
"Generative AI has introduced a new way architects and designers visualize and represent projects without spending hours developing 3D models or plans," Loza explains.
Instead of relying on massing models or plans, designers can now upload reference images and combine them with a well-crafted prompt and quickly generate visualizations of buildings, urban developments, or interior spaces. These images sit alongside mood boards, magazines, and Pinterest references, streamlining the communication with stakeholders in the conceptual phase.
AI is also being woven directly into real-time rendering engines such as D5 Render, where inpainting, style transfer, and upscaling tools live inside the software. Loza sees this impact in two ways: AI as an alternate path to illustrate ideas without building a full model with generative tools such as Nanobanana or Midjourney, and AI as an enhancer of traditional real-time workflows like D5 Render or Enscape with Veras AI—introducing new stylization options, faster ideation, and more believable people, vegetation, and atmospherics.
In his consultancy work, one of the biggest potentials of AI comes in the due diligence analysis of a specific parcel. During the pre-design phase, Loza's team uses a custom GPT model to streamline due diligence, guiding staff through parcel data, zoning information, height limits, and municipal requirements. Tasks that once took half a day now take minutes. "I tell project managers: treat AI as you would a junior designer," he says. "You still double-check their work, but they save you hours by gathering information and pointing you in the right direction." Furthermore, the AI can assist the Architects with recommendations on materials, contractors in the area, plan layouts, and code analysis.
In the schematic phase, generative tools like Midjourney and Rendeair replace long searches for the "perfect" reference image. Teams build mood boards, then use AI to generate targeted prompts that embed style, atmosphere, and functional constraints. The result is a series of custom visuals that clarify intent and make client conversations more productive. However, the more the project advances, the more precision and consistency are needed. So the AI becomes an enhancer of 3D modeling tools or Real-time Renderings.
Still, AI-driven imagery faces real constraints. Consistency and control are the main concerns when moving toward final deliverables. Real projects demand accurate surroundings—mountains, trees, neighboring buildings—and repeatable output across a full set of views. AI models often struggle with such specificity, sometimes producing artifacts or distorted details even after upscaling. For that reason, Loza argues AI images "should not be treated as final deliverables," but as catalysts for discussion or as layers that feed into post-production once a proper 3D model exists.
Misconceptions among younger designers, he adds, often stem from overreliance on the tools. Some expect AI to deliver award-winning concepts from a single prompt or assume that compelling images automatically equal good design. "AI outputs are not inherently good design," Loza notes. Fundamentals—proportion, light, geometry, function—still matter, as do context, culture, and user experience. Many confuse compelling images with great design.
Looking ahead, Loza points to three emerging fronts: "BIM 2.0" platforms with AI at their core, AI-powered computational design for feasibility and massing studies, and deeper AI integration in visualization and automated layout tools. New roles are already forming around these capabilities, from 3D artists specializing in AI post-production to technical artists training in-house models.
Loza, who recently completed a master's in digital arts with a specialization in architectural visualization, believes a new baseline is taking shape: every designer should understand at least one large language model for research and one AI visualization tool. But even as the tools evolve, one boundary remains clear.
"AI can elevate, enhance, and streamline the workflow," he says, "but it doesn't replace the need for craftsmanship, precision, narrative, and user-oriented design. The story still belongs to us."
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