Despite the headlines in the last month or so, such as the releases of Snap Spectacles 5, HTC Focus Vision and Pico 4 Ultra, the XR industry is struggling. The big players and startups alike have been unable to make significant sales in either the consumer or enterprise markets. Everyone is still trying to find product market fit.
Meta is the leading player in the XR space at the moment in terms of investment, innovation and adoption, and all eyes will be on what they have to say this week at Meta Connect. The timing of these latest headsets is not by chance; Snap, HTC and Pico want to get ahead of the impending announcement of Meta's new MR/XR headset.
Interestingly, it is likely that Meta, despite its name, will focus heavily on its AI investments in its message this week. The question I have - why is arguably the leader in the XR market today pivoting its message to AI instead of XR, and what impact does this have on the XR industry at large?
In this blog, I outline several factors that may be contributing to this shift:
Limited Adoption: XR devices have struggled to gain widespread adoption among consumers because the high price point relative to the overall experience has hindered its appeal.
Enterprise Challenges: In the enterprise market, XR has faced challenges in demonstrating tangible ROI, and integrating seamlessly into existing workflows.
AI's Growing Potential: AI has shown tremendous promise in various applications, from natural language processing to image recognition.
Why is the XR industry struggling?
The industry itself suffers because it is looking to revolutionise peoples lives, without a commonly used name with which to refer to itself, and whilst navigating wider economic issues:
Revolutionary, not evolutionary: Unlike AI, which seamlessly integrates into existing workflows, XR often requires new hardware and learning curves.
Lack of a unified term: The industry's use of various terms like "metaverse," "spatial computing," and "XR" creates confusion. I recently found this article which is where I found the image above, whilst I like the concept of the 'virtuality continuum' it is not going to fly with the average person on the street as too much explanation is required.
Economic downturn: The post-COVID economic climate has made investors more risk-averse, prioritising profitability over growth, impacting XR funding.
Lack of scalable interconnectivity: the metaverse, where people can enjoy a shared experience regardless of the tech they want to use, is possible today but is limited by our devices being unable to really understand the world around us without us manually teaching the device - this tech is evolving, but is needed to move us forward.
The bubble is real: the industry exists inside a bubble, where enthusiasts and experts are consumed by their belief that XR is the future, now - this can blind them to the fact that the world is not embracing XR.
Why is XR tech not resonating with Consumers?
Consumers are mainly not buying XR devices en masse due to cost, limited use cases and wearability:
Price of entry: The high cost of XR devices remains a significant barrier for consumers. Even as prices have declined, they still exceed the price point that many consumers are willing to pay for a product that will not be used every day.
Limited Use Cases: Many XR experiences focus on gaming or fitness, which may not appeal to all consumers.
Hardware Barriers: Headsets and AR glasses can be cumbersome and expensive, limiting their accessibility.
Unclear Value Proposition: Companies often focus on selling the technology rather than addressing the specific needs of consumers.
Why is Enterprise adoption of XR slow?
Adoption in XR is slow in Enterprise because it is unclear what value it brings, or how to measure it:
Unclear value proposition: Companies are hesitant to invest in XR without a clear demonstration of how it can improve their operations and bottom line.
Not clear which solution is best: The variety of XR headsets on the market makes it challenging for businesses to evaluate and select the best solution. Often the decision is made based on enterprise level support, or access to ecosystem partners.
Lack of measurable results: Many companies struggle to quantify the benefits of XR, making it difficult to justify the investment. However, those that do have success are more likely to keep their results to themselves to maintain differentiation.
True real world simulation is not possible: One beneficial use case for XR is to safely simulate dlife-threatening situations. However, XR faces the challenge of accurately replicating real-world environments because unless it is 100% accurate 1:1, then ultimately it is unusable for life or death type training such as surgery.
What issues do developers and content creators have?
It is difficult to create world class content or to make any money from that content:
No standardisation: The XR industry is dominated by a handful of major players, but each has their own proprietary platforms and devices. Whilst OpenXR has attempted to set the standard, everyone appears to implement it differently, and the role of 'extensions' has made it even more fragmented.
Specialist skills are required: Whilst low or no code tools remove the need for a developer, creating a good experience requires specialist user interaction design expertise and an understanding of how to utilise 3D space effectively.
No real marketplace to make decent money: The Steam Store is a great place for developers to make money on PC games, but there are a lot less users of SteamVR. The Meta Store is starting to gain momentum, but again the numbers of users are nothing compared to Steam users. Making money as an indie-game developer is difficult.
What can XR learn from the success of AI?
In contrast to XR, AI has been more successful in gaining widespread adoption due to several factors:
Accessibility: AI works on devices that people already own and use, such as smartphones and laptops.
Tangible benefits: AI offers clear benefits to users, such as improved efficiency, personalisation, and convenience.
Ease of adoption: AI applications are generally easier to use and require less instructions than XR technologies.
Evolution not revolution: AI is evolving how we do things today - not revolutionising how we do things today. It has the potential to revolutionise, but this revolution needs to happen gradually or people will fear it.
Conclusion: Is the future of XR bleak?
The XR industry faces significant hurdles that have limited its widespread adoption. These challenges include:
Economic factors: The post-COVID economic downturn has made investors more risk-averse, impacting funding for XR projects.
Technological limitations: XR devices can be expensive, cumbersome, and limited in their use cases.
Lack of standardisation: The industry's fragmentation and lack of a unified platform make it difficult for developers to create content that works across different devices.
Limited monetisation opportunities: The lack of a robust marketplace for XR content makes it difficult for developers to generate revenue.
The potential remains undeniable, however to overcome these challenges the XR industry must focus on:
Improving accessibility: Making XR devices more affordable and user-friendly.
Expanding use cases: Developing compelling applications that address real-world needs.
Enhancing standardisation: Collaborating and promoting the adoption of open standards and frameworks.
Creating a vibrant ecosystem: Fostering a thriving community of developers and content creators.
As AI continues to evolve, its integration with XR offers exciting new possibilities. By focusing on creating practical, valuable, and accessible experiences, the XR industry can overcome its current hurdles and achieve widespread adoption.
Afterthoughts
The recent partnership between Ray-Ban and Meta to create smart-glasses has shown that the future is bright. I am not particularly interested in the latest 'XR' headset from Meta, however the Meta Ray-Bans update is one I will have my eye on this week. I have been looking to get a pair for myself, but I am waiting to find out if the latest update will be a new hardware update because if there is, it will hopefully drive down the cost of the existing models. This is the first smart-glasses product I have seen that I would genuinely wear, despite not being a glasses wearer myself. Unfortunately though, I'd like to try the AI features, but they do not work in the UK (without using a workaround of course).
It makes sense for tech giants to team up with companies that know how to make and sell 'stylish' glasses - starting with a form factor that we know is desired and working backwards feels like it would make more sense. The fact that the Meta Ray-Bans are 'style over trying to cram a load of functionality in there' is also a great strategy because ultimately this tech will be adopted gradually. Start with what works - not what you want people to want. Eventually, hopefully fully functioning AR glasses will be able to look like this too.
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