In this episode, I talk with Jesse Light, S.E., P.E., president & senior structural engineer at SML - Consulting Structural & Forensic Engineers, about how AI in structural engineering and automation are transforming workflows and creating real client value. We explore practical ways firms can integrate digital tools to streamline design, improve accuracy, and enhance forensic investigations.
Engineering Quotes:



Here Are Some of the Questions I Ask Jesse Light, S.E., P.E.:

How have your experiences with NSF, IUCRC, and the VISER/VISA Center shaped your outlook on the future role of AI in structural engineering and project delivery?
What example can you share where process optimization improved capacity or reduced material usage in a project element?
How do you see generative design, machine learning, and other emerging technologies transforming AI in structural engineering workflows, and what role should leaders play in guiding their teams through these changes?
In what ways are AI and digital tools shaping your approach to forensic investigations and post-event analysis?
What factors should firms weigh when deciding between adopting off-the-shelf software with limitations and developing custom tools tailored to their needs?
Which mindset shifts and organizational challenges do leaders need to address to successfully embrace digital and AI-driven workflows?
What final piece of advice would you share with engineering and technology leaders as they plan how their businesses will evolve during this wave of change?

Here Are Some Key Points Discussed in This Episode About How AI in Structural Engineering Is Driving Digital Transformation:


Experiences with NSF, IUCRC, and the VISER/VISA Center highlight how pooled industry and university resources accelerate AI in structural engineering research that directly benefits project delivery. This approach gives firms, including small and midsize practices, influence over which technologies are developed while lowering the cost of access.
A streamlined workflow linking RISA, Excel, Mathcad, and Hilti reduces manual input, minimizes errors, and enables optimization on a load-case level. This process results in thinner base plates, smaller anchor sizes, and significant savings in both material and shipping costs.
Generative design and machine learning provide the ability to test multiple structural options quickly and handle complex, organic forms more efficiently. Leaders play a critical role by encouraging teams to use AI in structural engineering for scripting and automation while keeping engineers responsible for calculations and code compliance.
AI and digital tools reshape forensic engineering by using drones, LiDAR, and point clouds to identify structural issues faster and more accurately than traditional inspections. Shared datasets and specialized AI resources allow teams to process large volumes of data quickly and develop reliable repair strategies.
Firms evaluating technology choices must balance the ease and speed of off-the-shelf solutions against the precision and flexibility of custom-built tools. Leveraging existing platforms like Excel, RISA, Mathcad, and AutoCAD, combined with project databases through APIs, helps maximize value with minimal disruption.
Leaders face cost concerns, uncertainty around ROI, and legal risks tied to unverifiable outputs. Addressing these challenges requires small, incremental steps, cross-trained talent, and building on tools that teams already understand.
The most important step is to begin now with a small but meaningful improvement that frees up time for engineering work. Progress comes from persistence, steady iteration, and making practical connections between existing systems.

More Details in This Episode…