Augmented reality (AR) overlays digital information onto the physical environment to create enhanced and interactive experiences. Once considered niche, AR technology has hit an inflection point with a market projected to reach $300 billion globally by 2024 according to Bloomberg Intelligence. We are seeing widespread business application and record levels of investment.
This potential remains largely untapped, however, as enterprises grapple with adoption challenges from technology hurdles to talent gaps. Our research shows that using analytics and data science techniques to extract insights from AR has become pivotal in driving value.
As data analysts leveraging expertise in emerging technology and quantitative methods, we provide perspectives on the data-driven business impacts unlocked by AR across diverse use cases today. We also highlight proven strategies to accelerate and streamline AR solution implementation for data-focused organizations.
Defining the Extended Reality Landscape
While often used interchangeably with the umbrella term “extended reality” (XR), augmented reality (AR), virtual reality (VR) and mixed reality (MR) each enable targeted experiences:
Augmented reality overlays digital information and media within one’s physical surroundings through an interface like a smartphone camera. For example, consumers can preview virtual furniture in their living room.
Virtual reality fully immerses users in interactive, 360° digital environments isolated from the real world often utilizing a VR headset device. Architects may design buildings in VR simulation before any construction.
Mixed reality combines physical and virtual elements, enabling interaction between them. Complex data visualizations appearing on smart glasses as one walks around exemplify MR technology.
As hardware performance improves alongside declining costs, these technologies see growing real-world application creating competitive differentiation and advantage for leading companies. Gartner surveys show over 70% of enterprises have now implemented some form of XR or are in short-term planning stages.
XR adoption trends across enterprises. Source: Gartner
Total spending continues rising at a rapid pace:
| Year | XR Spending | Growth |
|---|---|---|
| 2022 | $16.8 billion | +47% |
| 2023 | $19 billion | +13% |
| 2024 | $30 billion | +58% |
Global XR spending growth (Source: IDC)
With increasing investment comes greater expectations to quantify and maximize the impact from AR and associated technologies. We next explore the role of analytics in enabling data-driven value.
Convergence of Augmented Reality and Data Analytics
Augmented reality converges multiple data streams—3D digital objects, cameras and sensors, localization maps, wearable inputs etc.— into integrated experiences. The number of data points generated from AR-enabled processes can quickly scale into what is classified as “big data”.
Consider employees reviewing equipment repair instructions using AR glasses: every hand gesture, eye movement, real-time geolocation stamp and manual step visualized generates new multivariate data captured from the integrated software and hardware system.
While AR provides the medium for rich user interaction, the underlying data holds immense and often untapped potential. Applying analytics and AI techniques allows extracting actionable intelligence—above and beyond enabling visual overlays—to create significant strategic upside:
- Derive behavioral insights on how users interact with AR experiences from attention, motion and other comportment metrics
- Enhance personalization with contextual data convergence from wearables, Internet of Things sensors
- Apply predictive analytics using machine learning on aggregated AR usage data
- Quantify performance gains using productivity tracking in enterprise AR deployments
- Model total cost of ownership with return on investment analysis methodologies
Let’s examine some real-world examples demonstrating AR analytics in practice:
- Monitoring gaze time, heatmaps and object interaction to optimize retail store shelf layouts and product placements
- Analyzing motion data, reaction times and decision logic to improve healthcare patient care workflows
- Gathering multi-user movement, collaboration and content usage data to enhance enterprise remote work solutions
As solutions mature, privacy and responsible data stewardship gain importance in managing personal data flows. Companies like Occulus (Meta) and LeapMotion have formed ethical data use guidelines that serve as frameworks encompassing transparency, consent, minimalism and accountability for the industry.
In aggregate, augmented reality analytics unlocks immense potential. Accenture estimates over $1.5 trillion in enterprise value creation applying extended reality solutions over the next decade.
Overcoming Adoption Hurdles
Recent research identifies three primary barriers curtailing broader enterprise AR adoption:
Cost – Development and deployment costs remain high for custom solutions built natively, while many emerging AR platforms still lack mature ecosystem support
Talent – Significant 3D and mobile development skills gaps exist with AR programmer roles seeing low fill rates for open positions
Strategy – Clear ROI validation and alignment to business objectives lag due to AR knowledge and talent gaps
Innovators have actively tackled these hurdles through multiple methods:
- Emergence of MRaaS cloud offerings reduce infrastructure costs for on-demand access to AR experiences and tools
- New codeless AR platforms empower non-technical staff to build solutions sans developer help
- Affordable and scalable headset options like the HoloLens 2 and Magic Leap 1 entering markets
- Expanding developer communities publishing open-source projects, templates and extensions
As more turnkey solutions appear, AR integration increasingly comes within reach whether running trials or planning wide deployment.
On the talent side—while early bottlenecks slowed traction—the availability of experienced AR solution architects, Unity 3D developers, UX/UI designers and technical strategists shows consistent improvement. We see specialization taking hold across solution providers and consultancies focused wholly on augmented reality.
Gaps certainly remain, but can get addressed methodically provided enterprise leadership backs AR-oriented skills development and centers implementation decisions on tangible ROI.
Measuring the Business Impact of AR Solutions
Given AR’s status as an emerging technology, building internal buy-in and securing funding means showcasing hard ROIs—a task historically seen as difficult to achieve consistently. Based on our hands-on collaboration with clients across industries, measuring success boils down to three key performance indicators (KPIs):
Efficiency – Quantify reductions in task times, steps and bottlenecks from AR optimization
Costs – Capture direct savings in training, travel, equipment plus opportunity cost recovery
Revenues – Link feature usage to conversion gains, sales and profit increase
We often recommend A/B testing with control groups when launching new AR workflows to establish baselines before systemwide rollout. Various statistical and predictive models can then integrate findings into extrapolated forecasts and compelling narratives on scaling projections.
For example, Boeing uses AR tablets and headsets to provide aircraft technicians immersive interactive work instructions overlaid directly within their field of view. Technicians can visualize the schematics and reference needed data immediately without workspace disruption to reference cumbersome manuals.
Comparing techs leveraging the AR system against those relying on legacy paper materials, Boeing registered a 90% productivity gain per tasks completed hourly and a 25% decrease in procedural errors. Had they scaled the AR solution across their entire maintenance staff, they projected over $500 million in cost savings plus substantial revenue upside from faster aircraft turnaround and servicing capacity increases.
This large-scale impact gets built from small, iterative measured wins. Companies focused on quick demonstration of AR effectiveness and ROIs—then reinforcing analytics rigor over time—show the most implementation success. Evidence trumps speculation with business leadership; data-driven methodology cuts through any lingering skepticism.
Bright Outlook for Mainstream Adoption
Recent advances in smartphone technology and wireless networks will further advance AR adoption by improving cross-compatibility and access. 5G rollout begins optimizing mobile devices for AR applications requiring responsiveness, graphics processing and unhindered data transfers.
On the hardware front, though early AR headset attempts like Google Glass struggled, rapid specifications improvements have benefited new releases like the Microsoft HoloLens 2 and Magic Leap 1. Further price-performance improvements will likely yield an inflection point in the mid-2020s triggering mass appeal for enhanced reality wearables.
Indeed IDC predicts a near-$65 billion augmented reality hardware market by 2025, suggesting we soon hit key thresholds for mainstreaming AR equipment. Paired with phones or everyday smart glasses, businesses can tap AR capabilities at consumer smartphone-grade pricing and simplicity within a short horizon. Cloud, big data and IoT ecosystem convergence will further support this democratization.
As solutions get embedded across domains from shop floors to operating rooms, another wave of data network effects takes hold. Expect a compounding effect where leading companies co-opt consumer-led adoption to build interfaces leveraging AR data at enormous scales for predictive modeling, revenue generation and hyper-personalization powered by AI and advanced analytics.
Conclusion
Augmented reality has progressed rapidly from scattered experimentation to transforming how businesses function through immersive experiences grounded in complex data convergence. While proliferation has started selectively around areas offering clear productivity and workflow enhancements today, exponential tech improvements will likely expand applications and provide universal access shortly.
Data scientists have only begun scratching the surface uncovering insights from AR data streams that will cascade business impacts over the coming decade. We encourage data analytics leaders to actively builder foundations now within their organizations—datasets, interim use cases, skills development, partner ecosystems—to prepare for the major disruptions and opportunities AR adoption poses in the near-term. Harnessing this potential requires crossing the digital and physical worlds, with data as the connective tissue binding them together.
