Show Me the Metaverse

Actually, we can’t — it doesn’t exist yet, even if existing virtual worlds and games try to pretend otherwise by simply relabeling themselves as “metaverse.” At the same time, the metaverse isn’t something that one day will suddenly be there: The journey has already started, and these environments are metaverse precursors. Future experiences will be more immersive, increasingly blending the physical and digital; many of the technologies underpinning these experiences already exist. Some are close to delivering business benefits, as outlined by my colleagues Brian Hopkins and Julie Ask. Others will take five years or more to transition into the mainstream. Four of these longer-term technologies appear in our list of top emerging technologies: extended reality (XR), Web3, Zero Trust edge (ZTE), and TuringBots.

Let’s take a look at the current state of these technologies:

• XR delivers value today but is at least five years from mainstream adoption. XR includes augmented reality (AR), mixed reality (MR), and virtual reality (VR). Traditionally distinct, these technologies have been converging and will continue to merge. In the future, XR will reshape how consumers interact, and many job roles will move to an XR-first approach. Today, poor user experiences and immaturity of the hardware limit consumer adoption of XR, especially outside of gaming. It’s a different story on the enterprise side, where both AR and VR have been delivering benefits in a range of use cases, such as maintenance, training, and employee onboarding. It’ll be some time before XR hardware is sufficiently advanced to deliver seamless and engaging experiences without discomfort. Until that point has been reached and larger numbers of consumers are ready to adopt, XR deployments will predominantly serve business-to-employee use cases.
• Web3 aspirations and Web3 reality are far apart, but Web3 isn’t going away. Web3 promises to deliver a more equitable version of today’s web, giving control back to the user. How the vision will become reality is less clear, in particular as Web3 today plays host to the same value-extracting and rent-seeking behaviors it aims to replace. This obscures the innovation potential stemming from the underlying technology: At the micro level, asset tokenization is here to stay, and NFTs offer benefits way beyond the sale of collectibles. At the macro level, blockchain-based networks offer the opportunity to build new business and trust models, but we need to develop them first. Much work also remains to be done to ensure the technology is fit for purpose — resilient, highly performant, secure, and usable by people other than cryptocurrency enthusiasts and tech utopians. The pace of innovation, though, is tremendous, and it’s likely that technology issues will be resolved before the emergence of viable governance models.
• ZTE helps digital business happen everywhere, securely. Organizations with large remote workforces and numerous remote locations need the ability to protect their workers, retail outlets, and branches. Achieving this is often a challenge with existing networking and security software; ZTE solutions address this by providing high-performance networks with embedded security. To become mainstream, they need to evolve beyond today’s solutions, which often consist of existing products with bolt-ons and no unified control interface. Technology progress alone won’t be enough, though, and technology leaders also need to embrace next-generation meshed solutions.
• TuringBots will improve developer productivity. Fast-changing environments require fast-changing applications and services; the bottleneck is often developer capacity to deliver those changes. This is where TuringBots come in. Forrester defines TuringBots as AI-powered software that can help and augment developers and their teams’ intelligence and ability to design, build, change, test, and refactor software code and applications in automatic and autonomous ways. Forrester coined the term TuringBot in honor of Alan Turing in 2020, and we have been tracking their progression since then. They first appeared in software testing in 2019-2020 and quickly progressed to writing sample applications. The most sophisticated in 2022 can take in text (up to half a page) of a well-described, complex problem, solve it, and write the code. While progressing quickly, the technology is far from mainstream, but it has the potential to disrupt software development and give a competitive advantage to those that harness it.

The original article by Martha Bennett, Forrester's vice president and principal analyst, is here.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/BlackSalmon