DPR Construction has released new research examining how artificial intelligence is changing healthcare operations and when those changes begin to affect facilities and capital decisions. The study found that AI is already influencing clinical operations and capital priorities, while its longer-term effects on space and infrastructure are still developing.
For healthcare owners, this creates an opportunity to test assumptions and preserve flexibility before major capital decisions are set.
How Artificial Intelligence is Reshaping the Healthcare Built Environment
Planning with Intelligence: How Artificial Intelligence Is Reshaping the Healthcare Built Environment draws on perspectives from dozens of professionals across health systems, technology, finance, advisory services, healthcare planning, architecture, and consulting.
Among the findings, 91% of respondents said AI is breaking down traditional project delivery silos, while the research indicates space is more likely to be redistributed than uniformly reduced as operational needs change.
“Health systems can make smart capital decisions today without knowing exactly what AI will look like years from now,” said Hamilton Espinosa, DPR Construction Healthcare Leader. “The key is understanding what is changing operationally, what that could mean for facilities and where preserving options today can create value as technology continues to evolve.”
Key Findings of the AI Research on Healthcare Operations
The research addresses a fundamental planning challenge: AI applications and operating models can change quickly, while major healthcare facilities can take five to 10 years to plan and deliver and are expected to remain in service for 30 years or longer.
A central finding is that operations are likely to change before physical buildings do. Facility implications emerge as technology begins to affect workflows, staffing, throughput, equipment or the location of care.
- AI is likely to shift space needs across healthcare facilities. AI may reduce demand associated with some administrative and support functions while increasing needs for higher-acuity care, virtual operations, automation, equipment support, and technical infrastructure.
- Capital planning should preserve options. Scenario testing, phased investment, conversion strategies, and explicit decision points can help owners maintain flexibility as technology evolves.
- Infrastructure may determine the pace of adoption. Power, cooling, connectivity, pathways, and data readiness can become limiting factors, making infrastructure headroom a capital planning consideration.
- AI requires integrated governance. Increasingly clinical operations, facilities, IT, cybersecurity, and capital planning need to work together around shared systems, infrastructure, and data.
Bringing clinical, technology, facilities, and capital leaders together earlier can help owners understand what they need now and where they should preserve flexibility for what comes next.
– Hamilton Espinosa, Healthcare Leader, DPR Construction
A capability-based approach allows health systems to plan for the functions their facilities may need to support as AI evolves. Those capabilities could include virtual observation, automated logistics, continuous monitoring and predictive maintenance.
Health systems can then determine the infrastructure and performance requirements needed to enable them. The research encourages health systems to focus on capital decisions that remain valuable as technology, care delivery, and operations continue to change.
Explore DPR’s Healthcare Insights for perspectives on how AI is already changing healthcare operations, which implications for facilities are still emerging, and how health systems can make capital decisions that remain valuable as technology evolves.
