WWDC Spotlight: Apple Vision Pro and the Future of Data Capture

When the Apple Vision Pro was announced in 2023, we immediately recognized its potential to revolutionize the way frontline workers interact with their environment. At the 2024 Worldwide Developer Conference (WWDC), Apple has just announced visionOS 2. There’s a raft of exciting new enterprise capabilities — with a significant emphasis on data capture. Here’s my take on it.

The most exciting announcements for us at Scandit are spatial barcode scanning and opening the main camera access for developers.

This opens the door for the headset’s built-in data capture capabilities to be enhanced with the powerful Scandit Smart Data Capture Platform.

The ability to capture data intelligently from barcodes, text, IDs, and objects unlocks multiple enterprise use cases for the Apple Vision Pro. Using Scandit Smart Data Capture, a host of developers and companies will be able to build their own augmented reality (AR) visionOS applications, enabling real-time decision-making, engagement, and workflow automation at scale.

The focus on spatial barcode scanning is also significant. Let’s be honest. Have you ever seen the humble barcode highlighted as a main feature of an extended reality (XR) announcement before? But the reality is that today, those simple, ubiquitous strips of black and white bars are often the most precise and useful foundation for enterprise data capture and AR.

Why smart data capture unlocks enterprise applications on the Apple Vision Pro

Capturing, processing, and delivering data at scale is the key that will turn the Apple Vision Pro into a co-pilot for frontline workers — in use cases such as smart shelving and restocking, planogram compliance, product information retrieval, enhanced inventory management, and more.

The real world is unstructured and variable. There’s no single “magic bullet” data capture technology that can solve for every scenario and use case.

Enterprise AR needs creative, flexible, practical, multi-modal data capture approaches. These will incorporate not only typical AR sensor technologies such as SLAM (simultaneous localization and depth mapping) but combine them with barcode scanning, text recognition, object recognition, RFID, and more.

Ultimately, I see this evolving into an AI-driven sensor fusion type model, where solutions like our Smart Data Capture Platform ingest and analyze multiple inputs. They’ll capture fully the environment around the user in a complete, precise, and useful way.

At Scandit, we’re already exploring a couple of key areas where we see the Apple Vision Pro combined with smart data capture offering immediate enterprise value.

Going hands free with the Apple Vision Pro

The first of these is hands-free use cases for scenarios where a high volume of items are being processed. The Apple Vision Pro with smart data capture will allow frontline workers in grocery, retail, and supply chain to use both hands to pick, pack, or sort products, without continually interrupting work to record tasks completed or check their next one.

Add in the Apple Vision Pro’s hand tracking, and these physical actions can also lead to automatic data updates — for example, a warehouse worker picking a box and the system automatically registering the item as having been picked. With an average worker picking 60-80 products an hour, time savings of even a few seconds per item add up to big efficiency gains at scale.

Intelligent shelf management with the Apple Vision Pro

Last week, I saw the Apple Vision Pro being used in virtual reality (VR) mode to develop a spatial planogram for Walmart.

It’s a great use case for VR. But it’s also only half a solution. Because once that virtual planogram goes into a physical store, you need to ensure in-store execution by frontline workers to deliver the anticipated sales and profitability boost.

With the new capabilities Apple announced, applications like this can now be built out using smart data capture into fully capable and deployable shelf management solutions.

Shelf management — for example, updating pricing and promotions — is a typical example of a tedious task that can and should be shifted to technology.

The bottom line here is that humans neither like nor are good at repetitive tasks that also require attention to detail. We do them slowly, it’s mentally taxing, and we make mistakes. A recent audit Scandit did with a major US retailer found that 9% of prices on shelves were wrong.

Instead of retail associates checking by eye, Scandit’s price label capture solution compares the displayed price to the catalog price to automatically identify price discrepancies. Associates are advised via an AR overlay which prices need updating.

Today, these AR overlays are viewed on an iPhone. It’s a low-risk, accessible entry point that’s already been shown to reduce the time taken to check a shelf by 80%.

Now imagine that app running on the Apple Vision Pro headset. With a field of view that takes in the whole shelf at once, and continuously gives associates immediate and actionable insights, it becomes a true co-pilot for workers, advising and supporting them at every moment.

The Apple Vision Pro is revolutionary, like the iPhone was revolutionary (and still is today)

We see the Apple Vision Pro as a beacon showing the way forward for spatial computing in enterprises. At the same time, the ubiquitous iPhone offers an easy entry point today for businesses starting on their journey.

The mobile augmented reality market is already estimated to be worth over $20 billion. Much as Netflix started off with existing technology by sending DVDs out to customers while streaming came of age, the iPhones already prevalent in enterprise are fertile ground for testing and iterating AR applications that will ultimately make their way onto the Apple Vision Pro — such as Scandit’s award-winning MatrixScan Find.

Apple’s focus on innovation in data capture in its enterprise APIs for the Apple Vision Pro, together with the increasing number of iPhone applications that prove out enterprise value for AR, are promising moves towards a spatial computing future.