Complexity of the ARMR Market: Software and Platforms

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By Eric Abbruzzese | 2Q 2017 | IN-4516

The augmented and mixed reality ecosystems continue to grow, both in scale and complexity. This Insight looks at the software, content, and platform sides of the equation, which are complemented by a sister Insight on the hardware market.

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Added Complexity


Rumors are again surfacing around Apple’s potential involvement in augmented reality (AR), this time with the iPhone front and center. While Apple continues to keep its AR cards close to the vest, there still exists a growing level of complexity, along with scale, in AR that Apple could play a role in solving. There is very little cohesion in the space currently—not uncommon in nascent and fast growing markets. This is exacerbated by the nature of the products available; definitions and roles surrounding AR, mixed reality (MR), merged reality, and virtual reality (VR) are opaque, and as a result, so are the accompanying software and platform offerings. A related ABI Research Insight goes into detail regarding the hardware component of the market. 

Both New and Old


The current state of the ARMR markets is such that traditional technology incumbents are the newcomers: Microsoft, Epson, Intel, and others are mostly on level ground with a host of companies founded at the onset of the ARMR era. Even so, the more established players are not lessening the level of complexity. Some platforms are end-to end, while others focus on more singular use cases; ideally, these more narrow platforms will integrate easily into other, more expansive platforms, as well as into existing infrastructure. However, that is not always the case. Content creation and publishing, machine vision implementation (for head tracking, image tracking, georegistration of content, etc.), and input/interaction methods all vary by approach and level of focus.

The variability in these devices and platforms introduced use cases and content types that are specific to a device, platform, form factor, etc. While this variability can allow for tailored and high-quality content, it is inherently limiting, and creates complexity for users, whether on the consumer or enterprise side of the market. So far, AR implementations favored simpler use cases to avoid the platform and content complexity; uses such as see-what-I-see, remote expertise, and 2D data visualization/manipulation are already beginning to be implemented by early-adopter AR customers. This is primarily seen in the enterprise market; the consumer market is not yet large enough to meaningfully discuss content complexity, though there are several notable parallels to tease out in the mobile device market; Android vs. iOS acts as a high-level fragmentation, with further segmentation in devices, components, etc., continuing on. Despite this, developers are often driven to make content available across the market, with help from well-established software development kits (SDKs). AR/MR SDKs are beginning to grow in number, but uniformity and device applicability across these SDKs is lacking.

Wide Applicability Requires Simplicity, as Well as Time


Complexity is not a new issue; fragmented early days—common in novel markets—leads to more advanced and deep-seated fragmentation as the market matures. Sometimes, this fragmentation is sorted out with time, while in other instances, fragmentation persists. While many markets deal with fragmentation, the ARMR markets are losing some traction due to it, and this is expected to continue. Customers will shy away from new use cases until system integration and implementation complexity is reduced, which requires both time and active pushes toward simplifying the software and content ecosystems.

These problems are exacerbated by the fact that many ARMR implementations require local resources and development time to fully integrate AR into the workforce. For instance, detailed 3D or CAD model interaction requires those 3D models or CAD data to be available in AR. There are a number of companies that offer services covering this (Upskill and Ubimax, for example), but there are gaps between coverage. As the complexity and scale of a customer’s implementation grows, the chance that a single company’s offering covers all of a customer’s needs lessens. IoT integration, existing infrastructure support, and complex security obstacles are all problems to be solved, and when combined, can hinder a customer’s ability to scale his or her own AR efforts.

Overall, the market does not need to be flawlessly streamlined for AR and MR to reach ubiquity. Over time, understanding will grow. For enterprise customers, this includes how ARMR can be best implemented and what is required to do so; for consumers, this is more extensive: public education of ARMR capabilities, compelling and user-friendly use cases, general availability of devices, and accessible upfront cost. Some of these obstacles will not be solved by simplifying the ecosystem—product price and availability will follow a standard pattern of greater selection and lower prices as the technology matures. However, general accessibility of ARMR, both for consumers and enterprises, can be improved through a simpler software and content ecosystem from creation to consumption. 


Companies Mentioned