Hype cycles occur when expectations, narratives, and messaging outpace technological capability. Virtual reality is an instructive example of a hype cycle — products like Apple Vision Pro and Meta Quest demonstrate what happens when leaders of tech companies push ahead and overpromise, even if the real technology isn’t ready. AI faces a similar fate: while innovation has steadily progressed, AI hype has ballooned beyond the bounds of reality, creating a rift between the promised AI experience and actual one.

The Hype Cycle Explained

We know hype when we see it: grand predictions of enormous growth, promises of breakthroughs just around the corner, press releases about revolutionary new platforms. Research firm Gartner defines the period of hype as the “peak of Inflated expectations.” 

New technologies often generate unrealistic expectations, which rapidly decline, but eventually interest and perception become more realistic. Peaks of inflated expectations and troughs of disillusionment can repeat throughout a technology’s lifespan.

Virtual reality (VR), sometimes referred to as spatial computing, is a headset-based technology that presents a fully digital immersive experience to the user. VR experiences typically block out the real world, creating a feeling of “presence” in a digital environment. This “presence” can be enhanced by interacting with the virtual environment with hands or controllers.

At its most hyped, VR proponents promise it will revolutionize workflows by seamlessly merging digital and physical experiences, enabling intuitive interactions with digital information systems, and creating immersive remote collaboration opportunities.  However, strategic and marketing efforts have not resulted in a commensurate revolution in sales or adoption for VR products.

Despite the subjectively strong entertainment experience, Apple Vision Pro was simply too expensive at $3,500 USD to justify wide adoption without more benefits. Factors such as battery life and poor ergonomics (weight balance) negatively impact the user experience of such an expensive device.

Meta has also placed overinflated expectations and hype on the “metaverse” with its VR devices. Meta promised the Metaverse would support collaborative remote work, exciting games to play, opportunities for creative socialization, and more. Meta continues to pour tens of billions of dollars into VR development, but adoption and revenue from virtual reality have not grown as Meta had hoped.

The “Reality” of Virtual Reality

VR’s path to mainstream adoption is blocked by significant technical challenges, but niche applications are viable. The cost of entry has come down significantly: consumer-grade headsets are available for a few hundred dollars. However, more capable systems like Apple’s Vision Pro are too expensive, and the highest-fidelity experiences (such as the Varjo XR-4) still require a connection to a powerful external PC.

Even on expensive devices, the resolution of current displays is roughly half of what the human eye can perceive, limiting detail. A narrow field of view in most headsets creates a “ski-goggles” effect that also hampers full immersion.

Finally, the physical ergonomics of wearing a heavy device on your face and the performance limitations of standalone processors mean that most VR sessions are, by necessity, short and cannot yet replicate the sustained productivity of a traditional computer.

Despite these challenges, steady progress has cultivated success in specific, well-suited domains where the benefits of VR clearly outweigh the drawbacks. Since the 1990s, folks have been chipping away at the downsides and building the upsides of VR technology. VR companies such as Varjo, BigScreen, 3M, and Immersive Factory have found applications like entertainment, flight simulation, or workplace training, that make sense, despite the significant tradeoffs.

VR hasn’t had a breakout moment or spikes in innovation. Instead, VR has enjoyed steady progress and incremental improvements. These improvements include a lighter, more powerful headset with a higher resolution and a broader field of view. The software experience of virtual reality has also incrementally improved over time, introducing more intuitive controls like hand-tracking or Valve’s “knuckle” controllers, and including new modalities such as eye tracking into experiences.

Entertainment stands as VR’s most prominent consumer success. For an hour or two, users can be given a unique immersive interactive experience. A game like Half-Life: Alyx is a prime example of a memorable, engrossing VR experience. While users find real value here, the experiences need to be designed to limit playtime to stay within comfort boundaries.

VR has also been successfully applied in specialized professional contexts. Visualizing and interacting with three-dimensional data in three dimensions is more intuitive. In medical contexts, three-dimensional data such as scans of the human body are often flattened onto two-dimensional screens. The United States Food and Drug Administration has already approved certain AR/VR devices for use in surgical planning or operation, where three-dimensional visualization can positively impact patient outcomes.

Similarly, VR is valuable for hazardous-environment safety training. VR allows companies to place trainees into dangerous scenarios like chemical spills, infectious-disease research, or industrial fires without any physical risk, providing a cost-effective alternative to building physical mockups.

Advice to UX Practitioners for VR

VR isn’t ready for mainstream adoption yet, but there are concrete ways UX practitioners can prepare for that possible future.

• Avoid throwing effort into learning new platforms or brands before a choice becomes clear. It can be instructive to experiment with new platforms, but when hype is high, don’t commit to any specific platform (e.g., Meta Quest) without a very strong reason. Focus your learning on transferrable knowledge and skills, such as core UX principles and heuristics, which can apply to two- and three-dimensional environments alike. If you need to spend time learning a system, focus on platform-agnostic tools like OpenXR, or game engines like Unreal engine or Unity, as opposed to Apple’s VisionOS or Meta’s Horizon OS.
• Develop your own evaluation of virtual reality, as opposed to listening to marketing. Personally experiencing any new technology is important. With virtual reality, it’s essential. Looking at non-immersive, two-dimensional representations of an immersive three-dimensional experience is inherently limited and inaccurate. However you can prioritize developing a personal experience and opinion of virtual reality, whether that means buying a low-cost headset like a Meta Quest 3S or scheduling a demo of Apple Vision Pro. That direct experience will be more valuable than reading a newsletter or listening to a podcast.
• Identify the core benefits of virtual reality. What makes it uniquely beneficial for your problems? Virtual reality is one of a few technologies which can render three-dimensional objects and data in its native dimensionality, with depth. It has a unique capability to completely immerse users, which can be beneficial for myriad experiences.
• Identify your own tradeoff points — when will it be worth it to adopt the technology? When will it be good enough for your own applications? As a UX professional, you need to decide when to dedicate time and energy to a new tool or medium of technology. To best identify tradeoff points, it’s worth deeply understanding the types of problems your users experience. If you have a good sense of your users’ pain points and problems, it will be easier to understand whether a technology like virtual reality could potentially solve those problems.

What VR Hype Teaches Us About AI Expectations

The virtual-reality hype cycle offers a critical lesson for navigating other emerging technologies, especially artificial intelligence.

Hype occurs when messaging and expectations outstrip technological capability, creating a rift between promises and the actual user experience. Generative AI now faces a similar fate, as expectations have been overinflated to the point that they are in danger of bursting. In fact, AI may be even more susceptible to hype, as its technology is harder to understand and its applications are wider and more amorphous. Additionally, AI has currently been deemed the “next big thing”, bringing with it an immense pressure to succeed, and to be “worth it”. Investors and businesses are highly motivated to inflate what AI can do, whether intentionally or not.

For UX practitioners, the path forward requires caution. The allure of a new technology like AI is powerful, but overinvesting one’s own time or money without a strong value incentive is a significant risk.

You can apply the same advice to the AI hype cycle as with virtual reality:

• Avoid throwing lots of effort into learning proprietary new platforms or specific brands before a choice becomes clear and the dust settles. Focus on learning the transferable skills that are generally applicable across AI platforms. For example, keeping up to date with prompting techniques will be more useful than learning how to use Gemini’s Deep Research tool. Or, avoid using AI-driven data tagging, as it remains inaccurate at this stage.
• Develop your own evaluation of AI, as opposed to listening to marketing. Experiment with AI, just as you would with VR or another emerging technology. Subscribe to at least one representative AI service to track its progress and to draw your own conclusions.
• Identify the core benefits of the AI. What makes it uniquely beneficial for your problem? AI technology can provide flexible, intuitive, conversational layers to products and services, just to name a few unique benefits. Reflect on the problems your users face, or your organization grapples with. Could AI help?
• Identify your own tradeoff points — when will it be worth it to fully adopt AI? When will it be good enough for your own applications? The current downsides of AI technology can be considerable, depending on the application. For example, the accuracy rate of top models can be as low as 55% on certain tasks. As with VR, it’s still worth experimenting and trying new technology like AI, even if it doesn’t meet your own threshold for product development or professional use.

The core drawbacks of a technology must be addressed before it can achieve widespread success. With virtual reality, until the ergonomics and performance of VR improve and costs continue to decrease, more practical alternatives like phone-based augmented reality or traditional 2D applications will often provide a better solution to users’ problems. Ultimately, lasting innovation is built on good products and real user experiences, not the hype that precedes them.