The Future of Labs—Designing for Automation

2025 Lab Design Conference speaker—Yvonne Choe, architect and partner at DIALOG

In the evolving world of science and technology, automation and AI are transforming the way laboratories function—and even more importantly, how they’re designed. As AI continues to advance at a rapid pace, capturing headlines and sparking debates about the future of work, its implications for laboratory environments are already becoming clear. Automation has the potential to not only increase efficiency and enhance safety but also to shift the focus of lab work toward more knowledge-based, intellectually fulfilling tasks. These changes promise to improve user well-being, foster deeper innovation, and drive stronger financial performance. Recognizing that much of this technology is still emerging, it's critical to design laboratories with future-ready infrastructure that can adapt to continued progress.

Yvonne Choe, architect and partner at DIALOG, spoke at the 2025 Lab Design Conference in Denver, where she explored how these shifts are impacting not just workflows, but the very infrastructure of research environments. Drawing on her research and experience, she shared how automation is already influencing lab design today and how her project is strategically positioned to evolve alongside these technological advancements.

Rethinking lab design in the age of automation

Choe began her talk, The Future of Labs—Designing for Automation, with a bold premise: automation is already reshaping the lab landscape. From robotic arms and automated analyzers to intelligent lab management systems and cloud-connected devices, technology is accelerating how experiments are conducted and data is processed. Yet despite this surge, many laboratories are still designed for people, not machines. As Choe put it, “Labs today still look a lot like they did 100 years ago.”

Several forces are converging to drive this change. One is labor. As skilled science professionals become harder to find, automation helps fill the gap by taking over repetitive, manual tasks. This allows human talent to shift toward higher-order problem-solving and innovation. Safety is another factor: robotic systems can perform hazardous tasks, reducing the risk to human researchers. Meanwhile, efficiency and precision improve significantly with systems that can run 24/7 with minimal error.

Automation is also making financial sense. Although initial capital investments can be high, automated systems can ultimately lower operational costs by reducing the need for manual labor, conserving space, and minimizing reagent waste through miniaturization. This is especially relevant for organizations with large-scale operations or tight labor markets.

But automation is not just about hardware. Choe emphasized the role of intelligent software—like Laboratory Information Management Systems (LIMS) and AI-powered data analytics—that enables labs to coordinate workflows, monitor operations, and extract insights from large datasets. These systems are helping researchers move from the benchtop to the desktop, shifting from hands-on experimentation to orchestrating experiments and interpreting results.

Choe showcased several compelling case studies. At the University of California, Berkeley, the A-Lab uses a robotic arm to perform materials testing, allowing students and researchers to focus on writing algorithms rather than mixing compounds. At the Pardini Group in Brazil, a fully automated diagnostic lab has dramatically reduced turnaround times and improved sustainability metrics—cutting water usage by 32 percent and increasing productivity by 37 percent.

Strategies to support a robotic workforce

So, how should laboratories be designed to support this shift?

Choe outlined several architectural strategies. Flexibility is key. Modular lab layouts with larger bays and higher floor-to-floor heights accommodate a range of robotic systems, which are not always shrinking like consumer electronics. Infrastructure—particularly power, HVAC, and data—is another critical factor. Automated systems often require specialized power setups, drainage, and cooling, not to mention uninterrupted connectivity for data continuity.

Space planning must also consider the mobility of robotics. Robots need clear, threshold-free paths, and in some cases, floor vibration mitigation to operate accurately. From an MEP standpoint, integrating automation means rethinking the backbone of the lab—especially if mobile robots or automated tracks are in play. Choe noted, “You may need multiple elevator cores or service routes for mobile robots to move efficiently between lab levels.”

Making space for robots—and researchers

Despite the promise, barriers remain. High upfront costs, limited flexibility in retrofitting older labs, vendor lock-in, and the need for skilled technical staff all challenge widespread adoption. Many organizations lack the bandwidth to plan for automation, and those that do often struggle to scale effectively. “Sometimes the robot ends up in the closet when no one knows how to reprogram it,” Choe remarked.

Still, she remains optimistic. She presented conceptual designs that evolve from traditional labs to fully autonomous ones, with researchers working remotely while robots manage the physical tasks. Even more speculative are humanoid robots—such as those developed by Insilico Medicine—that mimic human movement to navigate legacy lab environments.

But even in this high-tech future, Choe returned to a central idea: people remain at the heart of science. The future lab must not only house automation but also cultivate collaboration and innovation. Drawing from Gensler’s research on innovation, Choe stressed that architecture should support knowledge sharing, dissolve silos, and build strong networks. “It’s not just about technology,” she said. “It’s about creating spaces that inspire, connect, and enable people to think.”

Ultimately, designing for automation means more than accommodating machines—it means anticipating transformation. As Choe concluded, “The future of innovation is about people. And automation is here to support that.”

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