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AI in AEC: Mastering the Implementation Challenge
At the AIA Colorado Practice + Design Conference, Akhil Hemanth, Assoc. AIA, an AI technology architect at Newcomb and Boyd, presented his vision of transforming his firm into an AI-first engineering firm. In his session, “AI in AEC: Mastering the Implementation Challenge,” Akhil explored the transformative potential of AI in the architecture, engineering, and construction (AEC) industry. He emphasized AI’s role in amplifying human creativity, quoting Fei Fei Li: “Artificial intelligence is not a substitute for human intelligence. It is a tool to amplify human creativity and ingenuity.”
Akhil discussed the current state of AI, showcasing tools like Gemini Nano Banana for advanced visualization, Hayog for residential design automation, and Sparkel.ai for hosting models. He emphasized the importance of considering the expanded workflow from RFP to handoff, highlighting process automation examples such as a knowledge management app, Earl for RFP generation, and a CA app for site visit reports. Project automation tools included ChatGPT’s image models, Nano Banana’s visualization capabilities, XFigure AI’s parametric design workflows, and agentic AI for multi-agent collaboration across disciplines.
To guide firms in adopting AI, Akhil introduced the Four E’s framework: exploration, effort, efficiency, and expense. Exploration involves identifying problems AI can solve, effort addresses adoption challenges like training and cultural resistance, efficiency focuses on workflow improvements, and expense evaluates ROI and investment strategies. He compared consultants and internal adoption, explaining that while consultants provide immediate value, internal teams offer long-term innovation.
Akhil shared examples like automating lead calculations and emphasized the importance of pilot programs to evaluate AI tools. He introduced an AI assessment tool with 20 questions across four sections to help firms gauge their readiness for AI adoption.
The session concluded with thought-provoking questions about the future of design, the commoditization of expertise, and the shift from drawings to insights. Akhil encouraged attendees to embrace AI’s transformative potential and become “surfers” riding the wave of change, adapting to the incoming wave of AI disruption in the AEC industry.
Takeaways
AI tools are already achieving significant time savings in design workflows, with some processes that traditionally took 5-6 hours now completed in 10 seconds. This raises important questions about project pricing and timeline expectations when firms can deliver faster results.
So normally would have taken us almost like five to six hours. This does it in 10 minutes. Actually no, 10 seconds… And so now when you’re writing new contracts, are you going to still give the same duration that you would normally give in a design and still price it out the same way, or would you compress the thing knowing that now, you know, it takes say one week to come for design?
The industry is moving from generative AI to agentic AI, where multiple AI agents work together to complete complex tasks autonomously. This represents a shift from single-task automation to multi-disciplinary collaboration, similar to how design teams coordinate across different specialties.
So think of you’re doing as a design, wherein you have a design, but you’re sort of like five people, right? So the designer, you have the structural engineer, MEP and civil. So normally you would, you know, a client comes to you, you would start off with the design concept, then you would send it off to the structure… That’s what agentic AI is, but it’s happening digitally.
The primary obstacle to AI adoption isn’t technical capability but human resistance to change. Successful implementation requires AI champions within the firm, realistic timelines (6-12 months minimum), and dedicated training time despite competing project demands.
And the most important, again like I said, is a big pain point is cultural resistance. The hardest challenge isn’t technical for the most part. It’s human resistance to change often slows down the adoption of new tools… I think having a champion within the firm is, I think is determinant to making AI work within the firm.
Firms face a critical decision between hiring AI consultants for immediate results or building internal capabilities for long-term value. While consultants provide rapid implementation, internal teams achieve higher value after 12-18 months and offer unlimited growth potential without plateauing.
So if you were to map them both consultants provide immediate value but they kind of plateau over time. Internal teams take longer to ramp up but they achieve higher value long term. So in the graph you kind of have a tip over point between the consultant and the in house, in house team, which is I think between 12 to 18 months.
When evaluating AI software vendors, firms should demand evaluation results showing the tool’s accuracy, request 2-week pilot programs to test within their specific workflows, and avoid vendors who won’t provide these. Many current AI tools are overpriced due to market hype.
You should ask for eval or evaluation results. Like what is an evaluation set that they have used to come to a result that they are then showing you? That is one. And you should also push for two week example usage of the app. If they don’t give you that, just walk away.
Firms should conduct comprehensive assessments across the Four E’s framework to understand their AI readiness. This includes evaluating current workflows, identifying automation opportunities, measuring success metrics, and comparing against industry benchmarks to create targeted implementation strategies.
So this framework, before we even get to the framework, what is important is something that you all have to do is look at the current state of the firm workflow, just the current state assessment. What are some of the strengths? What are some of the opportunities that you think that exist but you know you’re not making use of them.
The design profession may be evolving from creating original work to curating and refining AI-generated outputs. This fundamental shift challenges traditional notions of architectural practice and raises questions about where professional value will lie in an AI-augmented future.
What if design becomes more about curating AI outputs than creating things from scratch? What if the most valuable firms in AEC become AI companies rather than traditional design firms? What if our expertise becomes commoditized by AI and our value lies somewhere completely different.
Rather than viewing AI as a threat (the asteroid approaching the dinosaur), AEC professionals should position themselves as surfers riding the wave of technological change. This mindset shift from resistance to adaptation is crucial for thriving in the AI-transformed industry landscape.
The first image, and I know, Mike, you mentioned this is a dinosaur that’s looking at an incoming asteroid. And I personally feel the AC industry, in this case is the dinosaur, and we are looking at AI, which is the incoming asteroid. But having said that, I want us to be the surfer. I want us to be willing to surf the wave of change.
Current AI applications in AEC include knowledge management systems that search through project drawings and documents, automated proposal generation from past projects, and site visit reporting tools that capture photos and generate reports through voice interaction. These tools demonstrate immediate productivity gains.
It’s a knowledge management app, so think ChatGPT, but having access to all of the drawings, completed images of the project sites, details, elevations, and you’re just like talking to your assistant to, you know, try to find these drawings for you, trying to find the images for you. So it’s a complete knowledge management within the firm.
AI implementation should extend beyond traditional project workflows (the five architectural phases) to include process automation covering business development, project setup, project management, knowledge management, and firm operations. This holistic approach maximizes AI’s business value across the entire firm ecosystem.
But there is also this whole aspect of process automation which we also should talk about. Because the entire presentation that I want to give today is from the lens of us looking as a business. So from business as from the lens of the business, if we want to make AI valuable to us, we need to be looking at the entire workflow from when we get an RFP till the handoff.