Artificial intelligence is finding its way into nearly every stage of architecture and design. Some of its most practical uses today are helping designers explore early concepts, refine renderings and work through visual options more quickly.

Schemmer’s Alana Kerr, Architectural Designer, has seen AI used professionally and academically. While the technology is advancing quickly, she views it as a tool that still requires clear direction and careful review from a trained designer.

AI in the Design Process

AI is currently most visible in conceptual design, visualization and marketing. Designers can use image generators to produce early concepts, test different wall or furniture colors and explore how changes in lighting might affect an interior space.

Rather than asking an AI platform to generate a design without restrictions, Kerr typically starts with existing information and a defined task.

“The majority of the time, we are implementing both a text prompt and reference imagery to task AI with a specific task rather than allowing fully open generation,” Kerr said.

AI can also help improve existing architectural renderings. A designer might use it to make shadows more dynamic, adjust entourage such as people or landscaping, or add photorealistic detail during post-production. The design team maintains control of the underlying concept while using AI to work more efficiently.

Kerr also uses AI in her academic work for research, ongoing critique and cross-checking. Although much of her interest centers on image generation, she is also exploring how AI could help automate portions of the research process.

Faster Exploration and Iteration

One of AI’s clearest advantages is speed. Early in a project, design teams often need to consider several possibilities before identifying a direction worth developing. Generative tools can help them visualize more of those possibilities in less time.

“I see a lot of benefits today from speed of iteration,” Kerr said. “It is infinitely faster to generate immediate concepts based on prompts, whether to discuss as a team or present to discuss with a client.”

That speed can help teams make design discussions feel more concrete. Instead of relying entirely on a verbal description, architects can give clients a visual starting point and learn what resonates with them. Designers can then test focused changes, such as adjusting a finish, adding an object or exploring a different lighting strategy.

AI can also help identify materials, precedents or potential approaches when provided with information about a client’s goals and project constraints. However, producing an option is not the same as determining whether it will work.

“Because generative AI does not have a concept of items like cost or space, the screening of a human designer is still essential,” Kerr said.

An AI-generated concept may look compelling while overlooking the available space, budget, constructability or other project requirements. Architects must evaluate those ideas and translate the useful ones into viable design solutions.

“It is on us to act as a filter to make sure these ideas actually align with a client’s goals,” Kerr said.

More Time for Design and Storytelling

Visualization is only one area in which AI could affect an architect’s work. The technology may eventually have an even greater impact on repetitive tasks that happen behind the scenes.

Architecture requires research, documentation, procurement, proposal development and model management. Kerr sees opportunities for AI to assist with these processes, including specific tasks such as tagging items in Revit.

“I see AI making these processes faster and it allowing us as designers to spend more time on design and storytelling,” she said.

That shift could give architects more time to consider how a space will look, feel and function for the people using it. These decisions still rely on a human understanding of space and experience.

“Artificial intelligence will never be able to experience spaces like we can,” Kerr said. “The need for us as experts of space will always remain, in my eyes.”

Accuracy, Security and Professional Responsibility

AI’s limitations become especially important when it is used for technical research.

An AI platform can provide an answer that sounds authoritative even when the information is incorrect. Kerr points to building-code research as one example. If a tool does not know the answer, it may confidently cite a provision in the International Building Code that does not exist.

“Regardless of the ways that we utilize AI, the most important thing to remember is that we bear ultimate liability for any errors that it makes,” Kerr said.

Similar problems can occur in visualization. AI does not truly understand gravity, spatial hierarchy or the importance of maintaining specific architectural features. It may unexpectedly alter a wall, window, piece of furniture or another essential part of the design.

Those limitations make professional review critical. Architects remain responsible for verifying information and making sure an AI-assisted image accurately represents the project.

Data security and intellectual property introduce further questions. Before using an AI platform, project teams need to consider what information is being shared, how that data could be stored and what rights may apply to the resulting content.

“Beyond functional errors, there are a lot of unknowns with data security and intellectual property that are still unknown with AI use and disclosure,” Kerr said.

Policies, technology and professional standards will continue to evolve, making it important for architects to stay informed and adjust their practices as more becomes known.

Looking Ahead to AI and BIM

AI is already being used as a visualization tool between architects and clients. As it becomes more precise, it could make it easier to explore specific project components together and clarify design ideas earlier in the process.

Kerr believes some of the most substantial growth over the next five years could happen in automation and building information modeling.

“I would love to see it used as a tool that we can use to talk directly with our model to coordinate with other disciplines or contractors,” she said.

That kind of interaction could help architects, engineers and contractors locate information, identify coordination issues and work through project models more efficiently.

AI’s role in architecture will continue to grow, but its usefulness will depend on how it is directed and reviewed. It can help design teams move faster, explore more alternatives and communicate ideas more clearly. Architects will still be responsible for deciding which ideas serve the client, meet the project’s requirements and deserve to move forward.

Planning a project? Connect with Schemmer to learn how our architecture team can help turn your ideas into thoughtful, practical design solutions.

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