7 minute read
Lighting the Way With AI
from Aug 2025
From Concept to Construction
By Randy Reid
Cover Photo: “Architect using AI tools to analyze stacks of documents and urban data before a project” prompt. Midjourney 7, Midjourney, Inc. Generated on 16 Aug. 2025.
Artificial intelligence (AI) is no longer an abstract promise for the future. It’s already transforming how lighting designers work across every stage of a project.
In recent conversations, Brian Stacy of Arup and Foad Shafighi of HGA shared their perspectives on where AI is delivering real value today and where the next breakthroughs are likely to emerge.
Notably, Foad is developing LightingAgent.AI, a specialized platform currently in alpha testing which helps lighting designers harness AI more effectively in their daily workflows.
Below, we explore how AI is contributing—phase by phase.
Pre-Design / Research
Brian emphasized that AI is particularly well-suited to proposal development. In the early stages, designers often receive thousands of pages of competition briefs and reference documents.
Brian described how his team uses Copilot, an enterprise version of ChatGPT, to safely reconcile all requirements and pull together previous proposal language. Copilot’s Researcher tool helps scan public datasets, transit reports, and articles about crime, usage patterns, or neighborhood economic trends— valuable context before design begins.
Foad shared that large language models (LLMs) like ChatGPT and Gemini are already indispensable for research and brainstorming. For example, before designing a renovation for a church, using voice, he prompted ChatGPT to walk him through every architectural element of ecclesiastical spaces, creating a kind of real-time conversation with an architectural encyclopedia.
He also highlighted the models’ strengths for drafting emails, proofreading, and summarizing proposals.
However, he stressed a critical limitation: never rely on AI for codes and standards, since models often hallucinate or lack up-to-date references (more on that later).
Schematic Design (SD)
The schematic phase is where ideas begin to take visual shape. Brian described using image processors like DALL·E and tools connected to Unreal Engine and V-Ray to transform initial concepts into exploratory visuals.
His team works carefully to anonymize sensitive project details and uses secure environments to avoid leaking proprietary designs. In his words, if you’re designing a hypothetical Mars arena, you wouldn’t want AI to auto-publish it to the Internet.
Foad prefers Midjourney at this stage, especially for ideas. Rather than starting with a technical drawing, he uses Midjourney to generate inspirational images that capture mood, atmosphere, and lighting character. As he put it, “Midjourney is like an extension of your mind. It imagines what you have in words and shows you something you didn’t know you were thinking.”
Design Development (DD)
When initial concepts need refinement, AI offers a different set of tools. Brian and his team uses Make.ai, a workflow platform that helps link data between AI tools and Revit models. This allows them to build specifications and coordinate inputs across many design team members.
He also highlighted the contributions of Kuldeep Vali and LumiBuilder.ai. Brian noted that Kuldeep is doing important educational work to help lighting designers understand how to integrate AI into their practice, while also developing smaller tools aimed at bridging theory and practical workflows. In Brian’s words, “Kuldeep has a cool little thing going on, helping folks understand lighting practices and how to be able to use AI.”
Foad described how Stable Diffusion is his preferred platform for Design Development imagery. Unlike Midjourney, Stable Diffusion can preserve the parameters of a space and let the designer adjust only the lighting component—like swapping a pendant for a linear fixture— while leaving the rest untouched. This iteration workflow has no equivalent in older rendering pipelines.
Construction Documents (CD)
In the construction documentation phase, AI has started to streamline production tasks.
Brian said his team is exploring Copilot inside Word and Excel to automatically build specification tables and link them to BIM models. They also apply internal automations to calculate lighting power densities across platforms—reducing the time it takes to finalize schedules.
Foad agreed that construction documentation is an area where AI has not yet reached full maturity. While no single tool can yet produce a fixture schedule end-to-end, he noted that Gemini’s million-token capacity helps with analyzing large specification documents. For example, you can feed it an entire schedule and ask targeted questions about part numbers or compatibility.
However, this approach has limitations. “General AI tools lack the specialized knowledge our industry needs,” he explained, adding, “We need dedicated tools that understand our needs and solve our pain points. Tools that are designed by lighting designers for lighting designers.”
Bidding & Procurement
The bidding phase showcases how different AI approaches serve different industry needs. While Parspec has secured significant investment to help distributors assemble bid packages and VE alternates, Foad's LightingAgent takes a designer-first approach.
“Parspec optimizes the supply chain, but designers need tools that understand lighting design principles, codes, and standards from the ground up,” Foad explained.
Ethical and Workflow Considerations
Both Brian and Foad stressed that AI must be used thoughtfully.
Brian noted that AI often outputs hallucinations and that any result should be scrutinized, just as you would an intern’s draft. He also warned that copyrighted codes or standards cannot be used without proper licensing.
Foad echoed this point, adding that LLMs are great for ideation but unreliable for compliance and technical documentation.
Brian also raised the possibility that AI will disrupt traditional workflows. Just as BIM required the profession to develop standardized LOD (Level of Development) milestones, he predicts the lighting industry will need new frameworks to define AI-integrated project phases.
A Quick Experiment
After speaking with both gentlemen, I did a quick search asking ChatGPT about the IES Recommended Practice for elementary school light levels—and it came back with a surprisingly detailed answer, shown below.
But upon a closer look, the response revealed exactly what both experts warned about: no specific standard citations, no edition years, no consideration of different classroom activities, and no way to verify the information.
It's a stark reminder that while general AI can synthesize plausible-sounding answers, lighting professionals need tools built on verified, current stand rather than best guesses.
Looking Ahead
While AI won’t replace expertise, it is already changing how designers research, visualize, specify, and communicate. Both Brian and Foad are optimistic that the right safeguards, along with a clear-eyed understanding of each tool’s strengths and limits, will help lighting designers unlock potential while protecting the value of their work.
At the 2025 IALD Enlighten Europe conference in Valencia, Foad delivered a presentation entitled “Illuminate and Innovate: A Workflow Revolution with AI in Lighting Design.” He began by saying, “I’m aware that some of you worry that AI will replace designers … My plan is simple: learn how to use it before it learns how to use us.”
It’s a perspective that resonates across the profession. AI isn’t going away, and whether it becomes a collaborator or a competitor will depend on how quickly and thoroughly designers embrace its possibilities.
