Latest Reports

When it was proposed in 2019, repurposing underutilized space at the University of Georgia for an industry partner’s fermentation lab appeared to be a good deal for everyone involved. It was a win for the pharmaceutical company that wanted to contract with the university to help it develop new products and needed a fermentation lab that met, at a minimum, biosafety level 2 (BSL-2) standards. It was a plus for staff at the university’s Bioexpression and Fermentation Facility who would perform the work. It represented an advance for the university that wanted to form new industry relationships and had available space at its Athens, Ga. campus inside the Animal Health Research Center (AHRC). And it was a win for the AHRC, a 75,000-sf biocontainment facility that would host a new industry partner in addition to other laboratories performing BSL-2, animal biosafety level 2 (ABSL-2), biosafety level 3 (BSL-3), animal biosafety level 3 (ABSL-3), and animal biosafety level 3-agricultural (ABSL-3Ag) research work.

Artificial intelligence is no longer a futuristic concept; it’s a transformative force actively reshaping how research is conducted, how buildings are designed, and how energy is consumed. From self-driving labs—defined as laboratories where scientific systems can autonomously perform multiple cycles of the scientific method—to smart energy systems, AI is ushering in a new era of efficiency, collaboration, and complexity. This shift was evident in a series of think tank sessions hosted by SmithGroup’s Science & Technology, Artificial Intelligence, and Energy Advisory Board, where leaders from academia, private industry, the energy sector, design, engineering and planning explored the rapid evolution of AI and its impact on research environments. In just six months between sessions, the pace of change was striking: Half of the experts expressed openness to selective technological enhancements, an idea nearly all had rejected earlier. This growing acceptance signals a more tangible AI-driven future, though strategies around governance and energy are still emerging. The following report offers insights into how AI is transforming research ecosystems, the energy infrastructure needed to support this growth, and the challenges and opportunities ahead.

Academic STEM facilities need the flexibility to accommodate an expanding range of disciplines and pedagogical methods while equipped with an adaptable infrastructure responsive to occupancy shifts and technology advances. Today’s projects often span the complexity spectrum, from soft spaces and graduate student workstations outside the lab to a zero-point energy (ZPE) environment for quantum physics research or an engineering lab housing a wind tunnel. While the terms “flexibility” and “adaptability” are often used interchangeably to describe the requirements of a lab building, planners at Research Facilities Design (RFD) draw a clear distinction between the two. In their context, flexibility is what occurs below the ceiling, for example, movable casework that allows a lab to accommodate new equipment or new research opportunities. Adaptability refers to what happens above the ceiling, such as robust MEP systems, well-organized ductwork and piping racks, and spare capacity at the electrical panel to support new or expanded programs in the building. 

In an era of expanding research portfolios and heightened expectations for interdisciplinary collaboration, universities face intensifying pressure to strategically plan, manage, and optimize research space. Research facilities, wet labs, maker spaces, core facilities, and computational suites, represent some of the most limited and costly assets in the academic environment. As competition for high-quality laboratories and specialized rooms grows, institutions are re-evaluating entrenched practices, strengthening policy frameworks, and adopting data-driven systems to ensure that space is allocated efficiently, transparently, and equitably. The most successful universities treat research space not as a static inheritance but as a strategic resource that must evolve with the institution’s mission.

Optimizing facilities is about the people and animals inside the buildings just as much as it is about the buildings themselves. As a facility with a One Health focus, University of Washington (UW) vivariums operate within the framework that humans, animals, and the environment are interconnected, and that caring for one means caring for the other two. While the concept behind One Health has informed the global scientific community since the beginning of modern medicine, the term and its application to vivarium facilities management is relatively new.