Building the Environments Advancing Quantum and AI-Enabled Innovation

Fueled by growing public and private investment and its convergence with AI, quantum computing is gaining momentum. Its potential to solve certain complex problems more efficiently is driving new interest across research, healthcare, technology and national security sectors. This potential is driving sizable investment and moving quantum from an emerging research market to a more visible public and private priority. 

At a recent panel hosted by DPR and AIA San Francisco, Michelle Martin, DPR’s higher education strategist, led a conversation with industry leaders from development, research, architecture and engineering firms to explore what quantum means for the built environment now and in the future.

Quantum computing is not meant to replace classical systems. Instead, it focuses on solving a narrow set of highly complex problems, including advanced simulation, encryption and scientific modeling. Its value lies in addressing challenges that classical systems cannot efficiently solve, rather than serving as a universal replacement.

“Quantum computers will not solve everything better or faster,” said Dr. Aziza Suleymanzade, assistant professor of physics and Robert J. Birgeneau chair at UC Berkeley. “The claim is that there are some algorithms that a quantum computer can perform faster or more efficiently.” That distinction matters for facility teams because each research direction creates different physical requirements. 

“We’re seeing a lot more integration of computational work, robotics and advanced technologies within research environments,” said Sarah Williams, vice president of design & construction at Breakthrough Properties. “It’s not just quantum. It’s everything converging at once.”

This convergence is reshaping how facilities are planned. They are hybrid environments that support a combination of academic research, life sciences, advanced technology and mission critical functions.

Across the discussion, five practical facility priorities came into focus: precision at the highest levels, rapid adaptability, robust infrastructure where it matters most and collaborating across industries to solve for environmental impacts. Together, these priorities offer a useful lens for owners and project teams trying to move quantum from research ambition to operational reality.

What differentiates quantum environments from traditional labs is the level of precision required to support them. Building conditions that are often secondary considerations in traditional facilities, such as vibration, power quality, temperature stability and electromagnetic interference, become critical to system performance.

“We are shoulder to shoulder with our architecture partners in every meeting pushing the envelope on quantum’s engineering infrastructure,” said Jason Atkinson, science and technology practice leader at Affiliated Engineers. “The level of concern is much higher than we’ve dealt with before.”

That sensitivity changes how projects are designed. Leslie Ashor, senior principal and director of science and technology at HOK, noted that quantum environments require deeper integration between architecture and engineering. “Quantum environments extend beyond traditional lab planning,” said Ashor. “They require deeper integration between architecture and engineering to ensure systems function as intended.”

Those same requirements extend into construction, where execution becomes a direct factor in performance. Variability introduced during installation can affect equipment stability, making construction cleanliness, coordination and sequencing essential components of project delivery. 

“In these environments, performance isn’t something you check at the end,” said Martin. “It’s built into every step, from how the space is designed and constructed to how systems are installed and coordinated in the field.”

In quantum environments, construction quality and coordination are not simply project delivery concerns. They are operational performance concerns.

In high-performance environments, many of the factors that affect long-term system reliability are established long before occupancy. Early coordination between owners, designers, trade partners and builders helps identify conflicts, reduce rework and maintain the conditions required for sensitive operations.

This approach aligns with other high-performance environments such as cleanrooms, biosafety labs and data centers, where predictability is built into the process rather than verified at the end. Delivery strategies like self-perform work, prefabrication and early coordination of process equipment increase quality, consistency and reduce risk, helping ensure systems operate reliably once in operation.

For owners and developers, the focus shifts from simply building space to delivering controlled environments capable of supporting highly sensitive operations.

One of the defining challenges in quantum is the lack of a single, standardized approach. Competing platforms require different infrastructure, ranging from cryogenic cooling systems with significant power demands to alternative systems with lower mechanical needs but strict environmental requirements.

“We don’t know what’s going to win,” said assistant professor of physics at UC Berkeley, Dr. Aziza Suleymanzade. “Each platform has different requirements.”

Yet, that technical rigor does not mean saying yes to every requirement. It means asking better questions: What must stay online during an outage? Which systems need UPS protection and which can tolerate a short interruption? Where can microenvironments reduce energy use? Which spaces need the highest power density and which can operate with less? Those questions help owners direct limited resources toward the requirements that protect research, equipment and long-term value.

For project teams, that uncertainty shifts the goal from building a fixed end state to designing systems that can adapt as equipment, research prioritie and tenant needs evolve.

This shift is reflected in how building infrastructure is planned. Rather than requiring massive reinvestments every few years, quantum facilities need accessible utilities, empty pathways and delivery strategies that allow systems to be modified or expanded as requirements change. Modular construction approaches, including prefabricated systems and demountable elements, support this flexibility by allowing spaces to be reconfigured without large-scale disruption.

The emphasis is on creating a framework that can evolve alongside research rather than attempting to predict long-term outcomes that remain uncertain.

Many organizations are integrating quantum programs into existing facilities rather than building new ones. This approach can accelerate timelines but introduce constraints that must be addressed early.

Power availability, structural vibration, load capacity and utility routing often limit what can be achieved within an existing building. Without careful planning, these factors can restrict the ability to support specialized equipment and future modifications.

Early evaluation of these conditions allows teams to determine where infrastructure can be adapted and where additional upgrades are necessary. In many cases, success depends on designing environments that can support iterative change without disrupting adjacent operations. Labs must support multiple phases of research, requiring systems that can be modified and expanded over time rather than remaining static.

“I cannot advocate enough: more power, more power, empty conduit,” said Williams. “If you’re building it, put it in, because it is a small investment now that will reap benefits later down the road.”

This adaptability requirement reinforces the importance of early coordination, accessible infrastructure and construction strategies that anticipate future change.

As quantum and AI continue to expand, energy demand is becoming a larger part of the conversation.  Ashor acknowledged that quantum systems are energy-intensive because they require tight temperature control, low humidity, cryogenic systems, cleanroom-level air movement, or uninterrupted operation for long-running experiments and intense computing.

At the same time, the rapid growth of AI infrastructure is driving new approaches to energy efficiency and sustainability. “Rather than addressing these challenges separately, there is an opportunity to apply lessons learned from AI facilities to quantum environments,” said Michelle Martin.

Large-scale data center projects are already incorporating renewable energy sources, advanced cooling technologies and hybrid systems designed to balance performance with resource use. Examples include integrating solar, wind and battery storage with cooling strategies that reduce water consumption and improve efficiency.

These approaches demonstrate how performance and sustainability can be addressed together. As quantum facilities scale, similar strategies are likely to influence how they are designed and operated.

The panelists agreed there’s an opportunity to advance both performance and sustainability from the outset rather than treating them as competing priorities. 

Quantum research and computing are still emerging, but their impact on the built environment is already clear. These facilities require a level of precision, coordination and adaptability that extends beyond traditional building types.

For developers, this means identifying design and construction partners with experience delivering high-performance environments where system reliability is critical. It requires working with teams that understand how to translate evolving technical requirements into spaces that can perform from day one while remaining adaptable over time.

Quantum and AI facilities are more than structures housing technology; they are strategic platforms that drive discovery, competitiveness and collaboration. As technologies evolve, so will the importance of the built environment. Progress will depend not only on research breakthroughs and advances in computing but also on the ability to deliver reliable, agile spaces that meet the demands of increasingly complex systems.