- [Jennifer] Hi, I'm Jennifer Isabella. - [Sharon] And I'm Sharon Leaver, your co-host for Forrester's podcast, "What It Means," where we explore the latest market dynamics impacting executives and their customers. Today we're joined by VP of Emerging Tech Portfolio, Brian Hopkins, and VP and Principal Analyst, Julie Ask, to discuss the 10 emerging technologies that should be on every technology leader's list to review this year. Welcome both. - [Brian] See, I'm happy to be here. - [Julie] Thank you. I'm excited to be here.
- [Jennifer] So let's start with economic uncertainty that's in every news outlet today. Where is spending on emerging tech sort of fitting within the tech leaders plans and agendas right now, with that as the backdrop? - [Brian] Well, I mean, the latest survey we ran kind of mid-year tells us that 2/3 of executives are still planning on increasing their spend on emerging technologies. So that's pretty important.
And furthermore, when we when to dig into that, 85% of companies have some kind of an emerging technology function. I realize that some of this data that we got kind of predated some of the economic uncertainty we're running into right now. But as we've seen in the past, I think a lot of clients that I talk to are looking towards emerging technology as a way to help them cut costs in other areas. But we're gonna have to look at the data as it plays out to see how that actually runs.
'Cause typically in downturns, there is some flattening of investment, and emerging tech might follow that a little bit. - [Jennifer] So Brian, quickly, before we get into the list, how would you advise a client or anybody thinking about emerging technology who wants to save it in their budget, make sure that that doesn't get pulled out. How do they go about doing that? How do they ensure that there's at least still some budget put aside for emerging tech? - [Brian] Well, we're gonna see a big shift away from those innovative things that have long timeframes; more towards the things that are closer, like in the 12- to 18-month range. So it just means a lot of firms that are mature enough to stretch to some of those bigger ROI kind of things are gonna turn more towards some of those emerging technologies.
And linking them to innovation investments that can deliver that shorter benefit, and probably lower some risk a little bit as well. - [Julie] So if I were gonna offer an opinion too, one of the roles that I play at Forrester is looking into the future and thinking about the future of consumer digital experiences. And when we look at that future, it's a future that will be built through incremental investments in emerging technology along the way.
You can't dial us back to 10, 15 years ago and say, "Well, I didn't have money for a mobile app. And I can just go build one in three months and catch up." When we look at the technologies that it takes to create more invisible experiences that drive this convenience for consumers, there are so many of these underlying technologies like AI and machine learning: it's very incremental.
You have to start today. At least make some small investments and keep building towards that future. You can't just take big leaps in the future. So you've gotta stay in the game today. - [Sharon] I think it's an important reminder, 'cause especially since with the pandemic, folks were forced to invest in digital real fast.
And this time around with the turndown, I worry that folks are gonna think, "Okay, well this time we don't have to. We can pull back on digital. We can pull back on technology." Which sounds like you two are saying that's absolutely the wrong idea. - [Julie] I think it's the wrong idea for two reasons.
So I think the first one is is when companies went fast, they focused on getting the job done, but not getting the job done well with a great user experience around the technologies that they rolled out. So I feel like now they've got more time to make those experiences better. And then I go back to the first thing I said about how the improvements here over the next 5 to 10 years are gonna feel very incremental, and you've gotta stay in the game. - [Brian] I think the other thing playing out, Sharon, is one of the things we saw through the pandemic, and we've talked about this before, CIOs and technology leaders actually stepped forward and were able to demonstrate how to get their business through a lot of the tough times using technologies, and making progress faster than they'd ever been asked to before.
So this demonstration of capability I think has built more trust with members of the leadership team. So that I think now that we're hitting this downturn that's kind of on the tail end coming outta the pandemic, we're gonna see a different behavior, at least with some firms because of the leadership team. And we're already seeing this with clients that I'm working to are saying, "Look, you did it then. How do we use technologies? How do we innovate? How do we use some of these emerging technologies to get us through this troubled time as well?" It's just like I said. I think a lot of the technologies that we're focusing on are gonna be those that have that nearer-term return on investment for a while. - [Sharon] Yeah, that makes sense.
So you all published a top 10 list. So let's get into the top 10 list. But before we do, there are a couple technologies that folks might expect to be on this list that are not on that list.
One in particular that I know is top of mind. Julie, do you wanna hit that first before we get into what is actually on the list? - [Julie] The metaverse is not on the list. So to be fair, and as Brian will talk through, the metaverse did make our list of top 20, but it didn't make our list of top 10. And I'll give you a few reasons why I think that was the case. So the first one is is there is no metaverse, and we don't expect there to be a metaverse for at least another 5 to 10 years. And so folks may say, "Well, there's a lot of press around the metaverse."
And I say what there is is a lot of press around online virtual immersive experiences that people have relabeled as the metaverse. So when we talk about why it's not an emerging technology, I would say what the core of it is is kids and teenagers and adults have been playing online immersive games for years, for decades. That's not new.
This has been been going on for years. And the idea that brands are doing product placements in these games and allowing people to put a Gucci bag or a Ralph Lauren shirt onto an avatar does not make it the metaverse. Those aren't new. I mean, they're interesting and it's gotten a lot of media attention, but they're not new ideas. It's not like literally a new technology that's enabling us to do that today.
- [Brian] I'm seeing that from a couple of places, Julia. You're absolutely right. From an enterprise collaboration perspective, we're seeing a lot of vendors who have been in the space of online virtual collaboration that got accelerated because of the pandemic. Now seeing what's happening, looking at what Facebook has relabeled itself. And now they're relabeling their product as metaverse. That's happening on the enterprise side.
On the consumer side or or the CMO side, we're seeing a lot of interest from marketers and CMOs who are being campaigned by their agencies, let us help you develop a metaverse strategy. So that's coming back to us is who do I go with? Should I have a metaverse strategy? And how should I get that strategy? I mean, should you have a metaverse strategy? I don't know, Julie. What do you think. - [Julie] You should at least think about whether or not you should have a metaverse strategy. Actually, so we've got a report about that coming out. But the metaverse is just like a lot of other technologies when it comes to making a decision about whether or not you should invest. You always start with my target audience.
Are they on one of these platforms? The largest platform we have today is Roblox with over 54 million daily active users. And you know what? 2/3 of those consumers are under the age of 16 years. So that may or may not be your target audience. And by the way, most of that is happening on a smartphone. It's not happening in virtual reality which is one of the other myths. And then you have to know what your business objectives are and what you wanna do before you decide is the metaverse the right channel to engage my consumers? And then if so, is it a good fit, what I wanna do? So what we're seeing today is a lot of virtual goods for avatars and a lot of parkour games.
And in some places that makes sense. If you look at China, there's far more familiarity with the metaverse and demand for that because consumers are more locked down, they've got less mobility, and so there is more interest in these virtual and immersive environments. And the United States comes up next on the list.
And then familiarity in Europe is even lower. So what the metaverse is competing with is the real world today. - [Jennifer] So let's bring it in one click in.
So that's what didn't make the list. I know the technologies on this list are sort of categorized for how far out they are, how emerging they really are versus how close they are. Let's start from the furthest ones out. I think there are four on the list that are sort of across the chasm. Brian, you wanna take us, what those are? - [Brian] Well I mean, there's two of those technologies that are definitely part of what we call metaverse precursors. They're gonna be important pieces to the metaverse.
I'm gonna address one. I wanna talk about Web3 just really quickly. And then the next one, extended reality. We're gonna go back to Julie 'cause obviously she knows a lot about that.
But let's talk about Web3 for a sec. That word kind of gets slammed onto the end of metaverse in a lot of inquiries we have. And that idea has been reinforced in the media quite a bit.
And Web3 did make our list, because we're seeing a lot more tangible things happening around Web3 technology, specifically when you start to see applications built on the Ethereum platform. And people usually think of Ethereum as a coin, as a cryptocurrency. But what it really is is it's a platform for building applications, and the underlying programming language is something called smart contracts. And you can actually build distributed applications that run on this Ethereum platform. And we're seeing quite a few of those. The problem with Web3 today is that's one vision of what it is.
There are many other visions. And $30 billion of investment in Web3 startups in 2021 didn't do anybody any favors. Because there's so much pressure, so much hype, so much now fear of missing out coming on behind that, that no one can decide what Web3 is really.
There's not really a business model for Web3 that has demonstrated the ability to make any return on investment. So we're not quite sure where it's going or kind of whose vision of Web3 is gonna win. Plus, most of the folks developing Web3 are again a much younger generation of users. So it's a really kind of interesting space right now, and it certainly deserves your attention.
And to some extent it gets connected to metaverse because the visionary ideas that at some point these distributed democratic applications, people are gonna interact with those applications and exchange in FTs, for example, in some kind of metaverse environment generally. But that's totally vision. And like Julie said, there is no metaverse today. There's just these online worlds.
And most of the Web3 stuff isn't happening in these online worlds. - [Jennifer] Are there specific industries that should be paying closer attention to Web3 specifically? - [Brian] Yeah, two industries you really need to look at are financial services and what's happening in DeFi, decentralized finance. A lot of stuff happening in there. Did you know that there's this idea of flash loans? And a flash loan is where money is loaned in crypto and taken back in one transaction at next to no interest.
So it's almost free money that you get for a fraction of a second. But in that fraction of a second, you can go do an arbitrage, an arbitrage engagement to go buy and sell two different cryptos or take advantage of cryptocurrency price differences. So you can actually make a fair bit of money doing that. And we see that happening. It'll blow your mind. $4 billion were traded in flash loans in 2021.
That's crazy. - [Jennifer] You are correct. That blew my mind. - [Brian] So it's certainly something to pay attention to, but it is across the chasm; it's on the frontier. It's at least five years from any positive benefit for most organizations. As the second one is extended reality, which I'll let Julie talk about a bit 'cause she worked with me on that research, and it's her point of view.
- [Jennifer] And so Julie, for XR, what do you think? - [Julie] Yeah, so with XR, which is extended reality, which could be either augmented reality, virtual reality, or something in between that we call mixed reality, there's two points of view here. So the first one is the consumer point of view. So the challenge that we have today is there just aren't very many use cases for consumers, and it's not very convenient to access extended reality experiences today. So one of the things that we know about extended reality is that if consumers use it, it has an impact. But in the Moments Map that we have from 2022 that we published recently, we only have 42% of consumers that have even tried using augmented or virtual reality.
And we've only got 28% that are comfortable doing so. So one of the factors and the inhibitors really is that most of us are having these experiences through some kind of a smartphone, which is great. Pokemon GO is a lot of fun. But we haven't really evolved the use cases beyond that. Folks like to speculate about the headsets or the displays. And the challenge of it is is there isn't a lot of content, there aren't a lot of use cases.
And by the way, these headsets are expensive, and they're hard to wear it for very long. The battery doesn't last. They heat up. They're heavy. They're just not comfortable to wear. So when we look at adoption of VR headsets in the United States, it's about 10%.
So the challenge is not only is there not a business case there, there isn't really a use case or consumer demand for those experiences. Then you look into the enterprise. My colleague J.P. Gander has written about lots of case studies of companies using VR headsets, especially for doing training, especially where the alternatives are very expensive. So imagine one-off scenarios like a disaster at a nuclear plant or an emergency at a manufacturing facility. Imagine a quarterback who needs a lot of reps out on a field.
So where we see the use of virtual reality for training tends to be where the alternative is very expensive. So think military, think pilots and things like that. And then you get into things like augmented reality. And these headsets are very expensive. You're talking about folks that are out in the field that need a hands-free way of getting instruction or some kind of tutorial to do a task, when a second person either can't be there or it's cost-prohibitive to have another person there to help.
And so bottom line, just the use cases aren't there and it's not convenient for us today. - [Sharon] So that sounds like a great reason why it's not a very mainstream technology yet. But it also still made the top 10. Is that the way it's always going to be? Or is that just current state and we feel strongly that actually it's gonna take off in other use cases sometime soon? Or else, why the heck is it on the top 10 list? - [Julie] Great question. Because this is an emerging technology that's been around for more than a decade, two decades, something like that. So I think it's a good question, Sharon.
And there's a couple of things that we think are on the horizon. So on one hand, we do think that we will see headsets that are affordable to consumers within the next 4 to 5 years. So we expect to see that happen.
And with Facebook rebranding as Meta and pushing more social media and gaming experiences into the devices, we think the investment by the likes of Meta, Microsoft and so forth will push this forward in the next I'd say probably like 4 to 7 years, which is about where we've timed this as a technology having an impact. - [Brian] And there's an enterprise angle to this as well: enterprise uptick. We think the enterprise use of these technologies might actually precede consumer.
So for those reasons, yeah, we think that it definitely deserves a place on the top 10. - [Julie] Yeah, so it's the economics and the enterprise can afford the headsets. - [Sharon] Let's get a little closer in even more: the next group. Maybe if you're an organization, you're not ready for the metaverse, you're not ready for Web3, you're not ready for VR, what should you be ready for, at least in the next two to three years? Maybe use that timeframe? - [Brian] Yeah, so I think one of the things that we see is this notion of how are you gonna trust artificial intelligence. And when we talk to experts like Brandon Purcell about this, the know-how of how do you build a machine learning algorithm, or how do you hire a firm to build a machine learning algorithm for you that can do something fantastic, we've kind of crossed that. It's fairly easy to at least go get the capability today.
The question is is are your executives gonna trust what that thing is doing, to the point where you're gonna bet a significant amount of your business or your customer relationships on it? And when I talk to clients about it today, the biggest gap they have is, well, maybe not. So explainable AI definitely made one of that 2 to 4 list, because that's the technology aspect of a larger program of responsible AI, which is kind of the business initiative necessary to make sure that we're using these technologies, these algorithms, in a way that protects our customer relationships, protects our brand value, and also just tells us what's going on. - [Julie] So intelligent agents are one of these core components as we think about how experiences become more invisible. So an intelligent agent could manifest itself to an employee or to a consumer through some kind of a tech space, chat, or even through some kind of a voice interface.
And the real aha and the magic of these intelligent agents is that they can scale all kinds of coaching and assistance that otherwise would be out of the reach of most consumers today. So whether you're thinking about fitness coaching, health coaching, financial coaching, mental health, and all of the hot topics that we have today, these intelligent agents offer a massive opportunity on the coaching side as well as on the self-service side for consumers, whether they're looking for help in making a purchase or some kind of post-purchase support. - [Brian] It's real interesting, Julie, because when you think about two sides of that coin, when you think about what intelligent agents are able to do, leveraging things like machine learning and AI, what we also have in that kind of mid-timeframe is this idea of edge intelligence.
So 43% of firms today are saying they already invest in edge analytics. And so edge analytics is those IoT type of use cases. You have some piece of equipment or some server out of your data center, out of the cloud, and you're not analyzing this data that's too big or too fast to bring it back to the cloud. Most of those analytics today are heuristics.
They're rules-based analysis: if this then that. If it's in this band, then go do this thing kind of analytics. Well, what we're seeing through use cases like computer vision and some advanced machine learning is the ability to look at videos, look at voice, look at images, understand what's going on in those and make decisions based on that. Today most of that is happening, but it's happening in all the information that those models are learning and training has to go back to some central cloud. And so the deployments of these across many different places, the models can't learn from each other.
So network rail, which is a activity that a government agency in the UK is doing a pilot, a computer vision pilot actually at the London Bridge station. And they're deploying this computer vision platform into the London Bridge station to recognize unsafe conditions: suicide's an issue. How do you recognize that? How does a disabled person, do they need assistance? And they've been very successful. But that particular deployment is only gonna be for those 700 cameras that are in the London Bridge station.
In the future, edge intelligence means that those cameras, as they learn things in one station, will be able to, things like 5G and software-defined networking, transmit those learnings and train and teach other models at other stations. Which means now when you learn what a suicide ritual looks like in one place, you can teach all the cameras in other places that don't see it that often. They can recognize it. So again, that's kind of an advancement. It's gonna take a while. That's why it's in the 2 to 4 years.
But that's definitely where we're headed. - [Jennifer] So what's going mainstream next year? - [Brian] There's two technologies on our list. We really debated this.
Julie and I and another analyst, Martha, and a few others kind of had a big conversation about are these things really emerging. And the two things that we saw is delivering benefit really quickly, like now to within the next year, are cloud native computing and natural language processing. I'll take the first, and then I'll ask Julie about the second.
A lot of people think cloud native computing, because cloud means you're moving everything on the public cloud. In fact, I've had that conversation with clients a lot. Cloud native computing: "Oh yeah, we do that. We're on Amazon." That's not cloud native computing.
Cloud native computing means that the technologies that Amazon and Microsoft and Google use to do what they do are now coming to everybody else through open source: things like Kubernetes, Docker, service meshes. There's a program called Istio, function as a service. There's a open source project called Knative.
All of these know-hows and software packages necessary to help enterprises get aspects of cloud no matter where they compute on the edge, wherever, are now becoming available to them. And that's cloud native computing. The fact that you can have cloud-like capabilities in your manufacturing plant. Interestingly enough, we just published our predictions on cloud, and the main emphasis of our cloud predictions is that VM-based, virtual machine-based infrastructure management is a thing of the past: it should be considered legacy.
And where we see firms going mainstream is shifting over to using Kubernetes and containers to manage portability of software across multiple environments. We think that's the next big thing and that's what we mean. So it's still emerging because the adoption's ramping up, and there's still a lot of interesting software changes happening.
But it's also something that most enterprises today are moving towards. - [Sharon] They're moving towards it. But how realistic is it, like what percentage are actually gonna get there in the next couple of years? I feel like we've been talking about cloud for it feels like decades at this point. And it's still kind of taking a long time. And now we're saying, "Oh, you did cloud. But really, it wasn't cloud.
It was a lift-and-shift project." And now there's this new thing. So I'm just pushing on this one a little bit 'cause it feels like a new thing to hype about, but is it really? Is it really going mainstream in the next year or two? - [Brian] I think what we've seen is the fact that it's not an all or nothing; it's not a lift and shift. Most organizations have been at least experimenting with container-based infrastructure management for a number of years now. And they've got some of that in their pre-production or in their development environments.
So what we're beginning to see as firms do re-architect their applications, driven primarily by wanting to get the benefits of public cloud, they're gonna discover situations in which a particular public cloud vendor that may be their vendor of choice isn't able to meet the regulatory requirements, for example, to move a certain workload over into the public cloud. Now what enterprises have is another set of tools to integrate and get some of the benefits of public cloud by leaving that workload in a container in their data center, because they can run that same workload in a container in the public cloud. So it's not a all or nothing. It's a gradual migration of using these technologies that will slowly replace virtual machines and other techniques we used in the past. And when we say it's going mainstream, what we think is it's moving from being that thing I use in pre-prod and development to accelerate testing into, no, I'm really running this workload in production. I'm running it in production in a container.
And because I'm doing that, I'm able to discover the benefits of containerization from moving other workloads or distributing those workloads further out to the edge. That's happening. That's real. And that's what we think. - [Julie] Yeah, so I think, Brian, the next one on the list that goes along with cloud native is what we're calling natural language processing. And yeah, I talked earlier about our perspective on the future of experiences.
We talked a little bit about how experiences are becoming more invisible, but at the same time they're becoming more immersive. And the next big leap forward for both consumers and employees in the workplace is more conversational interfaces, whether they be text-based or voice-based. There simply aren't enough humans to scale things like live chat for consumers or employees to get the support that they want, whether they're considering making a purchase or they need some kind of a post-purchase support. And if we look today at the Moments Map which we've published for 10 countries, but if we even just look at the United States, we have 70% of consumers that have adopted using text-based chat to engage with a brand, to get some kind of help. And 42% are comfortable doing so.
So there's all of this demand, yet very few enterprises have stood up. Text-based chat or direct messaging is a channel to support customers. And if we think that's just for product support and making purchases, then if you think about all the services we talked about, whether it's for mental health, healthcare, financial coaching, we can't scale providing this level of service to consumers if we don't use some kind of automation. So if we don't have the ability for consumers to type in natural language questions and then get back answers and get support, and so we need to have natural language processing as well as natural language generation, and like the whole family of technologies that go in to provide a more automated support to consumers and employees through direct messaging or voice-based systems. - [Jennifer] Okay, so great list, guys. Let me ask you to wrap up with maybe some advice for our tech leaders, and business leaders for that matter, thinking about emerging technology.
What's your advice for them to take that list and figure out how does it apply to their specific situation, depending on their level of maturity with technology, their industry, their staff, and figure out what to do tomorrow? - [Brian] So I'll lead off. That's a great question. I think the first thing is to understand that our list of 10 is not gonna be the customer's list. Our clients will need their own list of 10, 20, 30, whatever they have the capacity to look at. We think these 10 should be on that list for almost all of our clients. But obviously, each client needs to have their own list. And we have a lot of data behind the scenes.
I'm working with clients every day to help them kind of tailor that list from all the technologies that we track. Given that, the thing that we think that clients need to do is they need to answer two questions: Is this technology ready for their business? Are there opportunities for value? And when might those opportunities for value happen? In the next 12 months? In a couple of years? Someday, maybe five years or more away. But the second question that everyone kind of falls down on is are they ready? Is the client ready for the technology? So is the technology ready for you? Are you ready for the technology? Those are the two questions.
And the second question is harder. So one of the things that we've done is our survey data pretty consistently shows now over a number of years that a maturity spectrum, from a business perspective, is what we call a customer-obsessed maturity spectrum. We think the most advanced companies from a business operating model are customer obsessed. And we have a lot of data to show that these customer-obsessed companies are actually growing faster than companies who are less mature on that spectrum.
What's really interesting about our data, our survey this year, is that we were able to correlate that 3% of companies who are truly customer obsessed, those same 3% of companies are what we call future fit from the way they approach technology, their technology strategy. But what we found is that this 3%, that is where the money is. So when we talk about having 2 to 3 times growth faster than your other competitors in your industry, it's that very small section, a very small percentage who are driving that growth. And they're able to actually take a much more aggressive approach to look at these frontier technologies: the XR, the Turing bots that we didn't talk about, Web3. And they're able to actually start driving those things because they're mature enough to do so. And that's where we see those big advantages that companies, everybody wants from emerging technology is really reserved for that very narrow group.
The more modernized organizations, about 37% of firms are actually modern in their approach. And that modern approach means you can lean a little bit more forward and start piloting and driving some innovation around the technologies in the middle like edge intelligence. The mainstream firms, you've heard us say mainstream, there's 59% of firms that are still traditional in the way that they approach their business and the way they approach technology management. You really need to focus on those near-term cloud native and natural language processing technologies to get as much as you can from those, as you begin to investigate opportunities in the things that are 2 to 4 years out.
Put all the stuff on the frontier, put it on your watch list, understand it, don't pay too much attention to it now, specifically in these times of economic uncertainty. - [Sharon] Julie, what about business leaders, digital leaders, folks that are just as dependent on technology but might not be the CIO or a CTO? - [Julie] So for business leaders, the first thing is don't do anything just to seem innovative or just to seem cool. Be purposeful. Be outside in. So it's kinda like if we think back 10, 15 years ago: "Well, I wanna have an app." Today the version of that: "Well, I wanna do something in the metaverse." Don't use technology that way.
Know your audience. Know your consumers. Know your employees. Know what they're comfortable doing. Have clear business objectives and know what you wanna do before you decide: "Well, is it the metaverse, or what technologies do I want to use?" And then step back and think, "Okay, well, what is the impact of those emerging technologies on the experience that I wanna put in front of consumers or create for employees?" And back into it. Don't start with it. - [Jennifer] Great. Great insights. Thank you both for joining us today. - [Brian] Absolutely. - [Julie] Yeah, a lot of fun.
Thanks for having me. - [Jennifer] Thanks, Julie and Brian. If you liked what you heard today, subscribe to Forrester's "What It Means" podcast on Apple Podcasts, Google Podcasts, or your favorite podcast player. To continue the conversation, follow Forrester on Twitter, Instagram, and LinkedIn, or drop us a note at podcast@forrester.com.
Thanks for listening.
2022-12-02