Interfaces in new places: Spatial computing and the industrial metaverse
As the industrial metaverse transforms to enterprise tool, spatial technologies are taking hold in industrial applications, using data and AI to replicate real-life processes.
More often than not, novel technologies spark excitement with early adopters and consumers before quietly receding from the public eye, only to reappear months or years later as productive business tools. Some see this pattern as a movement along research firm Gartner’s technology hype cycle,1 while others understand it as a move from tech to toy to tool, as we discussed in Tech Trends 2023: In last year’s trend “Through the glass: Immersive internet for the enterprise,” we projected that the metaverse, or the immersive internet, would soon graduate to a full-blown enterprise tool as companies discover and build around new interaction capabilities such as augmented and virtual reality (AR/VR) simulations.2
This year, we’ve seen some of those metaverse capabilities progress in new directions, toward the broader realm of spatial computing. As they’ve turned the corner from consumer toy to enterprise tool, spatial technologies are especially taking hold in industrial applications, where companies are focused on digital twins,3 spatial simulation,4 augmented work instructions, and collaborative digital spaces5 that make factories and businesses safer and more efficient. The opportunities are promising: Revenue driven by the industrial metaverse is projected to reach nearly US$100 billion by 2030, far outpacing the consumer (US$50 billion) and enterprise (US$30 billion) segments.6
Whether through time-tested devices such as tablets or experimental ones such as smart glasses, factory workers, designers, and engineers are benefiting from immersive 3D interaction in ways that traditional knowledge workers haven’t yet experienced. The industrial metaverse is defined by real-world physics, using spatial data and artificial intelligence to render immersive visualizations that exactly replicate real-life processes. Imagine line workers using smart glasses to call an expert at a plant across the country, or engineers prototyping new equipment in physics-based, photorealistic digital twins. Where organizations have the opportunity to build new facilities, many are adopting a “simulation first” strategy before construction.
Improved and accessible high-fidelity 3D assets and hardware for extended reality (an umbrella term for immersive technologies such as AR, VR, and mixed reality) can pave the way to an operationalized spatial web, where a digital layer atop reality accelerates ways of working across industries. Eventually, this progress can lead to a simplified era of operations, where autonomous systems, instant 3D models, and quantum computing are paired with optimized human involvement for applications such as remote surgeries. Or imagine an entire factory floor staffed by a single well-connected worker.
Now: Simulating the enterprise
Over the past few years, advancements in technology have been building the scaffolding for the industrial metaverse. Investments in digital twins, 5G enablement, cloud, edge, and AI have driven significant value and addressed long-standing pain points. That’s why 92% of manufacturing executives surveyed in a recent Deloitte study said that their company is experimenting with or implementing at least one metaverse-related use case, and, on average, they are currently running more than six.7 These executives already expect a 12% to 14% improvement in areas such as sales, throughput, and quality from investing in industrial metaverse use cases in the coming years.
The most common use cases highlighted by executives were process simulation and digital twins.8 In industrial settings where operations are complex, pricey, and exact, robust simulations are a lifesaver. When connected to real-time data and models through the Internet of Things (IoT) and advanced networking, simulations can increase the chances of successfully building a new operation or optimizing an existing one. It’s no surprise, then, that some analysts believe the global market for digital twins could grow from US$6.5 billion in 2021 to US$125.7 billion in 2030.9
The optimal way to interact with these full-scale digital twins is through AR, a medium that can overlay the physical world with a digital layer to create a shared, three-dimensional immersive internet. As a result, the global market for AR devices has been estimated at US$38.6 billion in 2022, with an annual growth rate of 36% through 2030 for related software and hardware.10 While industrial and manufacturing applications currently make up the largest market share for AR, health care applications (such as training, surgical simulation, and vein visualization) are expected to grow by a compound annual growth rate of 44% through 2030. Consumer applications, catalyzed by the e-commerce boom of the pandemic, also abound, proving that the use cases for digital twins extend beyond just the enterprise.11
Spatial operations are just beginning, and enabling technologies continue to improve. Imagine powerful satellite networks combined with IoT sensors in a remote factory, processing real-time data on output and performance.12 As technologies advance, a new era of digital twins is on the horizon, where simulations could be photorealistic, based on physics, and enabled by AI,13 all while linked to company ecosystems, such as BMW’s Omniverse platform.14 This evolution is poised to affect multiple areas of the enterprise, from space planning to design to operations.
New: The spatial web is under construction
The impending spatial web (also known as Web 3.0) promises to eliminate the boundary between digital content and physical objects, effectively blending these two realities into one.15 Through next-gen interfaces such as smart glasses, the spatial web can allow us to interact with real-time information prompted by our physical environment, through geolocation, computer vision, or biometric commands like voice and gestures. Given the possibilities, the market for spatial computing is poised to dwarf previous estimates for the metaverse, with some projections estimating upward of US$600 billion by 2032.16
While the true potential of the spatial web is still years away, innovators are building its infrastructure now. In the next 18 to 24 months, companies should pay attention to the value opportunities for adopting spatial operations and arming their employees with tech that supercharges their work.
Augmented workforce
As workers in industrial settings continue to adopt AR/VR tools, companies are reaping the benefits of efficiency and effectiveness across a few key areas:
- Increased monitoring. As AR devices and spatial immersion allow employees to be in multiple “places” at once, fewer experts could monitor a greater number of facilities. For instance, Nokia’s real-time eXtended Reality Multimedia provides 360-degree views, 3D audio, and live streaming to allow human operators to immerse themselves in a physical space many miles away.17 This can bolster preemptive maintenance, security, and quality control.
- Reduced onboarding time. New employees can follow standard operating procedures that are built into simulations, along with visual cues that help them learn while in the flow of work, instead of having to separate learning from practice. For example, new employees at a global carmarker's manufacturing plants use AR devices to collaborate in real time with experts across the United States. Sharing the same vision and sound, the experienced line workers can instruct exactly where and how to strike a hammer on a door.18
- Reduced safety risk. As we discussed last year, companies can arm workers with AR/VR to better prepare them for risky settings. Stanford Medicine is piloting a VR system that combines images from MRIs and CT scans, among others, to create a 3D model of a patient’s body prior to surgery. Surgeons can see and manipulate this anatomical digital twin, not only in training settings but in the operating room itself, as a more detailed guide to the body than 2D images. Doctors are already seeing benefits in improved accuracy and safety of some of the most complex procedures in medicine, such as brain surgeries.19
Product design, development, and sales
Use cases for spatial operations are not just limited to improving the bottom line; AR technologies can improve top-line revenue growth as well. For example, leading AR companies are enabling clothing retailers to integrate AR technology into their apps, websites, and physical locations to further differentiate their offerings. With generative AI, these retailers can soon use AR technology to create 3D models from 2D images, increasing the availability of digital assets for customer engagement in a spatial web.
Such AR technology can do much more than superimpose an image of clothing over a shopper. For example, it can simulate how fabric will fall on a customer or how different lines in the stitching create shadows. And the results are clear: Some retailers have seen an increase in revenue per visitor of more than 50% after building in AR technology.20 As brands aim to stay relevant in spatial computing, AR companies are envisioning impact beyond retail, in sectors like education, entertainment, and travel.
Another way to take advantage of spatial operations is in design and testing of products under simulated conditions, which can lead to major improvements in agility, time to market, and even sustainability. For instance, instead of automakers subjecting their vehicles to hundreds of crash tests, they could use an initial set of data to simulate thousands of such tests and even consider events like natural disasters that can’t be easily replicated in the real world. Pharmaceutical giant GSK applied these principles to employ simulations for vaccine production, enabling it to cut its time to run experiments from three weeks to a few minutes.21 And in heavy asset industries such as mining, simulations can help fine-tune machine movements for efficiency and reduce emissions while preparing for the move to more renewable energy.
Space planning and simulation
The old adage of “measure twice, cut once” takes on new meaning in the age of spatial computing. Companies can employ spatial computing to visualize, simulate, and test layouts of facilities before undertaking costly investments: Measure 3,000 times, cut once. Architects can design an exact replica of a factory or hospital, replete with predictions of how many humans and machines will be present and how they’ll interact and move. For instance, a busy hallway for triaging ER patients may need to be expanded after a hospital simulates its usual intake numbers. Or an auto manufacturer may want to predict how a planned factory will handle a surge in demand for electric vehicles in the years to come.
That’s exactly what Hyundai Motor had in mind when partnering with Unity to build a pioneering full-scale factory simulation. The automaker plans to test the factory virtually to calculate an optimal method of operations and spacing, as well as one day enable plant managers to assess issues remotely.22 Similarly, Siemens, a pioneer in the industrial metaverse field, has announced a new factory in Germany that will be entirely planned and simulated in the digital world first.23 Only after adjusting its blueprints based on digital insights does the company plan to build the real-world campus.
Apart from the use cases for designing new spaces, spatial computing can also optimize a company’s use of existing physical locations. For instance, the retail planning team at GUESS planned out in-store updates digitally and moved forward only after virtual testing, resulting in a 30% cost reduction and a lower carbon footprint from reducing travel to make in-store updates.24
Next: Let’s get digital
The impending release of the Apple Vision Pro has made the term “spatial computing” more mainstream than ever.25 While some may wonder if this latest trend may be a passing fad, we would not bet against simplicity. The history of technology has proven that simpler interaction modalities have reliably unlocked massive step changes in the accessibility, and in turn, use of technologies.26 Spatial computing may be another such step change—where our natural gestures and ways of interacting with the physical world can be mapped onto the digital world, creating an ideal match between biology and technology.
As interaction technology continues to expand beyond computer science into the natural sciences (as we discuss in xTech dimensions27), brain-computer interfaces (BCIs) represent the furthest star of progress for simplicity. While today’s BCI functionality is concentrated in restoring human capabilities (such as the ability to walk), future endeavors may augment human capabilities, enabling us to accomplish digital and physical tasks at a speed and scale that were previously unimaginable.
For that to take place, we’ll need enabling technologies such as 6G networking and IoT. Through high-speed connectivity and massive machine-type communications, machines of the future may be able to coordinate with each other seamlessly.28 And the World Economic Forum has already predicted that omnipresent IoT sensors can one day digitize physical human work, enabling a higher degree of automation.29 Such advancements could pave the way for our interactions with machines to be much simpler as they become smarter at communicating about their environment and status.
Imagine a future of interaction where BCIs enable us to start, monitor, and modify an interconnected series of machines on an assembly line. Industrial work could also become remote work, carried out from a desk. And language could feel like a bottleneck compared with the efficiency of human thought.
While the possibilities are exciting, companies are at a crossroads: They need to move beyond the buzzwords if they want to be early movers—or find themselves trying to catch up with innovators. Beyond hiring or training their engineers on computer vision, sensor tech, and spatial mapping algorithms, they should also get ahead of the potential risks. Opening up the physical world to digital manipulation comes with its fair share of privacy issues (as computer vision expands), cybersecurity issues (as the physical world becomes hackable), and data protection issues.30 Fortunately, the progress of digital twin technologies and early 3D models offers valuable lessons for steps forward.
Once the initial benefits of spatial operations are underway in industrial settings, enterprises should be prepared: The natural evolution of spatial computing may radically change the way we interact with consumer and enterprise applications in the years to come.