The U.S. office vacancy rate reached another all-time high in the second quarter of 2025 at 20.7%, as Moody’s recently reported. That’s the highest vacancy rate in three decades, ABC News reported, with more than 900 million square feet of empty office space—enough to fill New York City’s One World Trade Center 300 times.
U.S. companies are losing an estimated $9 billion to $22.5 billion each year maintaining more than 900 million square feet of unused commercial space, with operating costs ranging from $10 to $25 per square foot. Causes of the vacancy crisis include the work-from-home and hybrid work models that took hold during the pandemic and remain widespread today and, according to global investment firm Brookfield, older buildings lacking modern technology.
While property managers work on increasing occupancy to raise revenue and cover costs, they can also optimize the cost of operating and maintaining empty buildings and spaces. With digital twin and artificial intelligence (AI)-based building management technology, it’s now possible to monitor empty building performance and optimize management and costs.
Digital Twins Provide Insights into Empty Building Performance
Information technology (IT) such as networks, computers, and sensors, and operational technology (OT), including building or campus lighting, plumbing, and HVAC, used to be difficult or impossible to integrate. But now, digital twins and smart building technology including AI, application programming interfaces (APIs), sensors, and building management systems (BMS) can capture, aggregate, display, analyze, suggest courses of action, and even automate building equipment operation. Digital twins, which are digital representations of the IT and OT systems, provide insights into the performance of these assets, enabling building managers to make informed decisions based on data, rather than assumptions.
If a building or a space is empty, a digital twin and BMS can optimize cost and provide operational insights until—and after—the space is filled. For example, rather than running an HVAC system at a constant temperature, the digital twin can adjust the settings of that system according to weather patterns to optimize temperature and cost. After a building or a space is occupied, a digital twin can provide insights into how facilities are used, who’s using them, when, and how frequently. It can then correlate energy consumption to the use of space.
Real Estate Needs a ‘Data Estate’ to Enable Digital Twins and AI-Based Management
To prepare for the insights digital twins can provide, real estate organizations need a “data estate” for their real estate. They must conquer data silos and overcome the historical challenges between different suppliers of IT and OT assets, which have their own databases and systems. Organizations need to access and bring disparate IT and OT data into a data cloud and a BMS in a unified manner, enabling them to monitor, understand, and act on building performance and occupancy. Without a data estate for real estate, digital twins, comprehensive insights, and AI are not possible because data is sequestered. A data estate for real estate enables building managers to create a digital twin, visualize what was formerly hidden, and have insights into building performance that were formerly impossible.
Digital Twins Help Inform Decisions Regarding Use and Maintenance
Digital twins can also help determine the best use of empty buildings and spaces. For example, digital twin technology could enable a university to assess how best to meet the evolving needs of faculty, students, researchers, and staff when space is available for classrooms, labs, and other purposes. For capital requests, digital twins provide the data and analysis of current and potential future uses of space to drive productive conversations and optimize decisions. Not only do digital twins reduce the guesswork when there are many possibilities and priorities for converting empty space to productive use, but they can also help determine if new construction is required, or if an organization can employ available space to address evolving needs.
Forecasting building use and simulating how to change or extend a space is yet another building management use case for digital twins. A digital twin and BMS can provide various recommendations for optimizing the use and cost of both occupied and empty space. Based on data and analysis, managers may decide to consolidate occupied space to free larger blocks of empty space until they are developed for future use, for example.
Businesses and universities aren’t the only organizations that can benefit from digital twins. K–12 schools are usually mostly empty during the summer months, while colleges and universities often are less occupied during the spring and summer semesters than during the fall and winter semesters—weather patterns are also different during these periods. Digital twins can monitor building use and correlate use and requirements with weather patterns to optimize management and cost. Organizations with commercial and K-12 educational buildings, which tend to be relatively empty on weekends and at night, can also leverage digital twins to adjust facility climates during these quiet periods.
Additionally, digital twins can predict and model building maintenance. Empty buildings or spaces usually receive less attention than occupied spaces, which can lead to maintenance issues. Digital twins can monitor the performance of all IT and OT systems against design and maintenance specifications, report problems immediately, predict performance issues, and remind management of maintenance schedules. Regular and proactive maintenance optimizes cost, performance, and the human resources required for smooth operation of empty and occupied spaces.
Real estate companies can also tout their use of digital twins, BMS, and AI in their sales and marketing campaigns to drive occupancy. Prospective tenants and occupants may appreciate the investment in modern BMS, as well as the intelligence and precision in monitoring and optimizing building performance and maintenance. After all, a smart building represents a smart organization.
The bottom line? Whether a building or a campus is entirely, partially, or occasionally empty, digital twins and AI-based BMS can yield significant cost savings (in some cases, in the millions of dollars) and open the door to enlightened—and enriching—decisions regarding maintenance, operations, and planning.
Joshua Ridley is the co-founder and chief growth officer of AI-driven platform provider Willow.