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NASA may have originated the concept of the digital twin, but the idea has moved far beyond simulated space missions. Businesses have adopted digital twins, virtual replicas of real-world systems, to revolutionize how they manage both their people and their spaces.
Imagine being able to simulate an office environment, from the flow of employees through the workspace to the impact of shifting teams or redesigning the floor plan. With digital twins, this is no longer science fiction.
Organizations can now test new ideas, predict outcomes and optimize operations in a virtual environment that eliminates the cost and risk of real-world trial and error. Leaders can explore “what if” scenarios: What if we switched to a hybrid model? What if we reconfigured our office footprint? What if we introduced flexible shift patterns or remote work policies?
This data-driven approach is transforming workforce planning. Instead of relying on gut feelings or guesswork, organizations use digital twins to run rich, adaptive simulations that continuously learn and improve over time.
As these virtual models grow more sophisticated, they do not just help companies optimize processes — they also prompt important conversations about the future of work. What does it mean for employees when their workplace is modeled and managed in real time? How will company culture evolve as digital twins become integral to daily operations?
Improving Team Structures and Facilities With Digital Twins
The answers to these questions will shape not only how organizations function, but also how we define the nature of “the workplace” itself. In fact, digital twins are helping organizations simulate everything from team structures to facility use, said AI/XR/spatial computing expert Barton Goldenberg.
Companies are creating virtual replicas of their workforce ecosystems — including job roles, work habits, collaboration patterns and office layouts — to model how changes might affect productivity, engagement and costs. Here he cites the example of virtually testing seating arrangements, remote work policies or staffing plans before rolling them out.
“With a digital twin, companies can test different remote or hybrid work models and instantly see the potential impacts on collaboration, productivity and real estate costs,” Goldenberg said. “Instead of relying on assumptions or surveys, leaders can simulate different scenarios — like a four-day in-office schedule versus full remote — and make data-driven decisions that align with business goals and employee experience.”
Essential Data Types to Support Digital Twins
To build accurate digital twins, organizations need to provide a mix of operational, behavioral and environmental data in a digital twin platform, Goldenberg said. This should include information such as employee schedules, task completion rates, meeting patterns, space use and environmental sensors that track occupancy or air quality. The key is integrating both quantitative and qualitative insights to reflect the human dynamics at play.
Three sets of data are critical to building an accurate digital twin of the office, said Honghao Deng, CEO and co-founder of Butlr. They are:
1. Building data
Building plans, age, how it is used, what types of equipment are in it and how often that equipment is used
2. Office data
Foot traffic, occupancy, space use and workforce distribution throughout the office
For example, you may have sufficient square footage, but if most employees work on the west side of the building while the east side remains empty, that will affect collaboration, productivity, heating/cooling distribution and maintenance, Deng said. It will also influence both top line contributions such as innovation and collaboration, as well as bottom-line energy costs including building maintenance and cleaning.
3. Environmental data
Location and temperatures inside and outside the building, materials used to build the structure, how the building is heated/cooled and lighting
Tracking Organizational Dynamics
Workforce digital twins give companies something they’ve never had before: the ability to see the currents of productivity flowing through their organizations and redirect them in real time, said Ram Srinivasan, managing director of consulting for JLL Work Dynamics.
Moreover, beyond operational planning, organizations are now deploying digital employees — AI agents that function as twins of expert workers, capable of answering complex questions, solving analytical problems and navigating multiple systems with autonomy. “While the potential is transformative, implementation requires careful governance, continuous monitoring and robust ethical frameworks to ensure these powerful tools enhance rather than diminish the human workforce experience,” Srinivasan said.
Offering an interface between human capital data and physical environment metrics, these new digital twins create unprecedented visibility into organizational dynamics.
Organizations that successfully integrate these diverse data streams find out important things about workplace optimization. For example, they discover correlations between environmental factors and team performance, helping them make better decisions about office design and resource allocation.
“Digital twins are like organizational MRIs — they reveal the inner workings that have always been present but previously invisible to decision-makers. A common revelation is the significant underutilization of office space,” Srinivasan said. “Real-time occupancy tracking frequently exposes that actual usage is far below assumptions, sometimes by 30-40%, signaling inefficiencies in conventional planning and opportunities for strategic spatial realignment.”
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AI analysis of digital twin datasets often reveals other information about workflow dynamics and behavioral patterns, Srinivasan added. Organizations discover that formal organizational charts often bear little resemblance to actual collaboration networks. These hidden patterns reveal both unexpected innovation hubs and previously invisible process bottlenecks.
“They also challenge workplace design assumptions, showing that informal areas are more important for collaboration than costly, underused amenities,” Srinivasan said. “Their greatest value lies in revealing unexpected insights that question long-held beliefs and encourage rethinking organizational spaces.”
Privacy and Ethical Concerns Around Digital Twins
At first glance, the idea of simulating employee behavior and workplace dynamics with digital twins sounds like a futuristic leap forward — and in many ways, it is, Willow CEO Bert Van Hoof said.
However, with this technological promise come ethical and privacy concerns. When companies model how employees move, collaborate and use space, questions arise: Is personal data being anonymized? Are individuals being watched too closely? Could this feel like surveillance rather than support?
Responsible companies are already navigating these issues with care, Van Hoof said. Their approach ensures that while the organization gains insight into workplace patterns, the individual’s privacy remains protected. Consent, transparency and data minimization are important for ethical implementation.
Yet digital twins have their limits — especially when it comes to the unpredictability of human behavior, Van Hoof said. These models are only as powerful as the data they receive. They can anticipate daily occupancy trends or routine movement patterns, but without access to systems such as event calendars or ad-hoc meeting schedules, they cannot foresee anomalies, like a sudden influx of people for a last-minute all-hands meeting.
Nonetheless, digital twins are no longer just tools for massive corporations with sprawling campuses. While large enterprises were early adopters, the technology is steadily becoming more accessible. Lower costs, improved platforms and cloud-based solutions are helping smaller organizations explore and implement digital twins, signaling a shift toward wider use.
It’s important to remember, though, that human beings are the ultimate confounding variable, said Irina Raicu, director of internet ethics at the Markkula Center for Applied Ethics.
They are collections of confounding variables, and collaborations among them, especially on complex tasks that involve judgment calls, can be difficult to turn into accurate data representations, she said Most good managers understand this and will likely be reluctant to base many decisions on digital 'twin' simulations,” she said. “The key question is which types of workplace decisions might benefit from such efforts."
Editor's Note: Catch up on other stories of how the future of work is now:
- Digital Twins in Meetings? Not Any Time Soon — Zoom CEO Eric Yuan recently suggested digital twins would attend meetings in our place. For now, that's more dream than reality.
- How Agentic AI Will Change the Workplace: An Insider View — Employees of some of the major tech vendors in the agentic AI space discuss opportunities and challenges associated with the technology.
- The Fake Startup That Exposed the Real Limits of Autonomous Workers —The Carnegie Mellon study confirmed what many suspected: in spite of the promises of world-dominating results, agentic AI isn’t ready to run the ship.