Tech Trends 2022 has been saved
Cover image by: Bose Collins
Mike Bechtel: It is a frothy space. As hype cycles go, it’s not just towards the top of the page, it’s off the page.
Scott Buchholz: And it’s not just french-fry-making robots and smart hospital devices and smart manufacturing machines, but it’s also drones. We’re seeing autonomously driven forklifts in warehouses. We’re suddenly having far more technology [in places] where the technology is interacting with humans—not in a digital way—but in a physical way.
Tanya Ott: I’m Tanya Ott, and this is the Press Room from Deloitte Insights.
We’re now in year two of the pandemic. Many of us are still remote—we’re still Zooming. We’re using apps and other technologies that we might not have even known about a few years ago. COVID-19 has forced companies to get serious about their tech infrastructure. It’s escalated schedules and amplified the importance of innovation.
And that’s why I asked Mike Bechtel and Scott Buchholz to join me today.
Mike is the chief futurist for Deloitte Consulting LLP. That means he’s responsible for looking at what’s new and next in tech.
And Scott oversees Deloitte Consulting LLP’s emerging technology research, which includes the annual Tech Trends report. This year’s report starts with a letter from the editors where they make clear that they think that, right now, tech has “the opportunity to engineer a better future—not just repave the old cow paths IT.”
I asked Scott to explain.
Scott Buchholz: There’s an apocryphal story that if you look at the city of Boston—the reason why the roads are so twisted is because they were actually originally cow paths that were eventually paved over. If you look at modern engineered cities—like those in the Midwest—what you see is they’re laid out on grids, and they tend to be much more efficient to get to and easier to understand because they were not designed by nature, but [they were designed] by deliberate effort. What we’re trying to say is, as people look forward, the future of IT is more engineering, it’s more automation, it’s more nimble and agile. It’s more reliable and secure. It’s more digital. It’s all of those things together. And the way to get there is not by doubling down on the things that have been successful for the past 40 years, but in a number of cases, by rethinking the design and the approach so that you can do things differently going forward.
Tanya Ott: So, this is the 13th year of Tech Trends. What’s the big picture for this year?
Mike Bechtel: Well, this year’s trends really break [down] into 2.1 groupings. The first we call “advancing the enterprise,” which are really ecosystem stories capturing the ways [in which] organizations are playing differently, acting differently, engaging differently with those around them, [and] with those outside the four walls of the organization. The next three trends are about optimizing IT—those improvements that make the way we work inside the four walls of the organization more efficient, more effective. Then our seventh trend—a mini-grouping if you will—[that] we call field notes from the future. And it’s really an opportunity to allow ourselves to not just chronicle what’s new, with crunchy case studies from organizations you've heard of, but to project a bit as to what’s next; to look over the horizon and see where’s it all going?
Tanya Ott: Let's just break this down—So, we start with ecosystems, and one of the major trends that you’re talking about is data-sharing made easy. Tell us a little bit about that one.
Scott Buchholz: We’ve said data is the new oil now for probably a decade. If you look, however, in many organizations, what we see is that people collectively don't feel like they have unlocked the value of that digital oil. This idea of data-sharing made easy is that there is a combination of new cloud-based database technologies that are enabling sharing of information in real time across organizations. There are a variety of techniques that help preserve privacy—everything ranging from clean rooms to homomorphic encryption to all sorts of other techniques. These combinations put together are actually helping organizations get comfortable with the idea that they can share information in real time and generate value that didn’t exist before. We’ve seen manufacturing organizations finding ways to sell sales-pipeline information to hedge funds. Nobody in that ecosystem expected to find value in those two matchups, and yet, the hedge funds found tremendous value, and the manufacturers found a new income stream.
Tanya Ott: One of the really timely examples of this kind of data-sharing has been during the pandemic because there was a lot of data-pooling in the early days, and that's what allowed us to accelerate things like treatments and vaccines for COVID-19.
Scott Buchholz: That’s absolutely right, and one of our stories was from CVS, which was on the front lines of pulling in information from dozens of different places to figure out where to get vaccines to the right places. Acknowledging that the vaccines expired quickly, that they were complex to move around, that they had a finite supply, they had a really interesting challenge—to try to figure out how to make sure the supplies got to the right places at the right time. So, absolutely, the pandemic was a great example of this.
Tanya Ott: The next trend that you talk about within this ecosystem idea is cloud going vertical. What do you mean by that?
Mike Bechtel: Ten years ago, cloud was a really interesting thing for your competitors to try first—that has evolved to the point where it’s become much more of a thing of, well, why wouldn’t I do it, as opposed to why would I? Now, that said, it’s not a big binary flip, right? The original cloud business cases were lift and shift—your-mess-for-less infrastructure moves [and] infrastructure-as-a-service. And then we saw the emergence of platform-as-a-service, the ability to run application layers and virtual servers somewhere else. And then we saw business-process-as-a-service—this idea that we could run horizontal applications, things like HR or customer relationship management ERP in the cloud. Well, with cloud goes vertical, what we're seeing is the next act in that play. The idea is that as the business case and the abstraction elevate—as it moves up the proverbial stack—it can’t help but become industry-specific, sector-specific, [and] verticalized. And so, we’ve spoken to hospitality organizations that say, “Hey, we’re here to compete on luxurious rooms [and] beautiful grounds. Reservation capabilities are not how we compete. They’re not how we win. And so, let’s outsource that. Let’s cloud-source that to any number of cloud-based reservations capabilities that would be happy to take that off our plate.” Insurance organizations [are] saying, “Yes, we’re in the insurance business, and yes, claims are part of what we do, but that's not where we win. So, let’s cloud-source claims management to an ERP hyperscaler and open-source software provider who’re happy to manage that function. The real point is, as cloud goes up, it can’t help but ladder up, specialize, and become evermore industry-focused.
Tanya Ott: In talking about laddering up, you all project that the value of the cloud market could reach US$640 billion in the next five years. That’s substantial.
Mike Bechtel: Well, it’s where organizations are increasingly living. One of the things we’ve seen, Tanya, is that if an organization wishes to take advantage of all of those wonderful toys available from open-source software providers, ERPs, hyperscalers, etc., being cloud-native or at least cloud-centric is table stakes. That’s where the action is.
Tanya Ott: The third theme in ecosystems is blockchain ready for business, and I was just reading an article this week where The Associated Press is going to start selling NFTs of its photojournalism. Cryptocurrency, NFTs—they’re everywhere, celebrities are doing it, news organizations doing it, politicians, athletes, you name it. There’s a lot of action in that sector right now.
Mike Bechtel: It is a frothy space. As hype cycles go, it’s not just towards the top of the page, it’s off the page. And it’s understandable because there’s a lot of innovation afoot. But in talking to our enterprise clients, we find that the enterprise-focused utility is less around NFTs, crypto, and digital scarcity at the moment—the creator economy, Web3—less around that, [and] more around the emergence of merely very useful business cases anchored in what we’ve come to call business process reengineering across organizational boundaries. Let me make this clear as mud for you—There are business cases wherein a jointly held version of truth maintained by all of us is more trustworthy than a single version of the truth brokered by any one of us. And so, examples: We spoke with a jeweler out of Hong Kong. They have a very interesting process wherein they laser-engrave the diamonds that they cut and save that serial into a jointly managed blockchain between themselves and the Gemological Institute of America (GIA). Why? Because two months from now, 20 years from now, 200 years from now, when your great-great granddaughter finds that stone in a drawer, should she just trust the appraiser at the local strip mall or whatever the 200-years-from-now version of the strip mall might be? Or, does she trust the original, immutable color-cut-clarity-carat as stored in that blockchain, which again lives across the web and is not maintained by any party with any one profit motive? These are the sort of brass-tacks, lead-with-need, no-nonsense stories that we’re seeing in the enterprise space. Supply-chain stories that used to be hairy, record-keeping messes are becoming leaner, meaner, [and] cleaner thanks to blockchain becoming ready for prime time.
Tanya Ott: That’s a great example. Very, very easy to understand, even for those folks who, you know, think about this stuff and are a little bit confused by it. Let’s move from ecosystems to systems. Sort of the second big classification in this Tech Trends report [is] IT disrupt thyself. We’ve got automation at scale, and you talk about starting to see some CIOs radically reengineering their IT organizations to automate even more. I want to get a sense of what they’re doing and why they’re doing it.
Scott Buchholz: What we’re seeing leading CIOs do, Tanya, is rethink the way IT organizations work. If you [had] walked into the typical IT organization in the 1980s, you would have seen an army of people staring at screens with blinking lights, furiously pounding away on keyboards when things went red. If you walk into many IT organizations today, you see an army of people staring at screens pounding on keyboards. The interesting thing that we’ve learned is [that] when the cloud providers came along, they took a look at that model and they didn’t say, “Let’s figure out how to scale that up.” They said, “New technology has emerged. Let’s figure out how to reinvent IT.” And what a lot of organizations are learning is that they can adopt the models the cloud providers have taken—which is small teams of engineers supported by a plethora of automation—can actually manage technology better than an army of humans reacting to events. This actually has a number of virtues. It doesn’t just improve reliability and scalability and repeatability, and all of the things we’re after—[but] security as well. But it also enables people to spend less time focusing down and in on the mechanics of it and spend more time focusing up and out on what the business needs, what the mission is after, and how to basically meet the business where it is. When we were talking with Capital One, they were actually saying that after years of hard work to transform the way that they operate, what they’re starting to see is [that] their developers are actually getting increasingly curious and motivated about what they can do to help the business. Part of the reason for that is they have to spend less time checking boxes and filling out forms and doing other things that just waste time and sap energy. So, the future is that IT looks a lot more like what we’ve helped businesses do for the past 20 or 30 years, that is, use automation, reengineer processes, automate low-value tasks, and get humans into better jobs where they have more interesting and more thoughtful work to do.
Tanya Ott: One of the things that I’ve been thinking a lot about is the cyberthreats that we have out there. You know, I don’t have the skills anyway, but I’d sure hate to be on a cybersecurity team because it seems like there are these potential bad actors everywhere. And just the volume of the threat and the sophistication with which attacks are being launched right now could be completely overwhelming.
Mike Bechtel: Tanya, you’ve articulated the complication admirably. What we found in our research is that traditional four-year universities are not minting good guys nearly fast enough to keep up with the proliferation of baddies that you mentioned. There are a couple of reasons here. One, in the heroic work that our clients and our client leaders did to virtualize the digital workplace as a response to the pandemic, there was a trade-off. In that work-from-anywhere new normal, we’ve greatly expanded what cyber pros called the attack surface. In plain English, there’s a lot more ways to get at us than there used to be in a work-from-anywhere world. You throw 5G on top of that and the proliferation of advanced networking technologies like it—and the baddies can not only find you in more places, but they can find you with more speed and more gusto. So, there’s this asymmetry. More bad actors. More incentives. More financial incentives in a cryptocurrency world, in a corporate espionage world, in a nation-state–meddling world. The real takeaway here, Tanya, is the good guys have decided that, rather than lament their momentary disadvantage, they can call on robot reinforcements, robot backup in the form of unsupervised AI and ML—artificial intelligence and machine learning technologies—that can be deployed into an environment and trained on what’s normal, what does normal look like. Why? So that should Scott log in from Belgium at 3 a.m., and begin to download the ERP inventories, the system can react and say, “Wait a minute, that's not normal, that’s not Scott,” and clamp it down. Part of what’s important here is that it can clamp it down in a microsecond. A human analyst could arrive at the same set of insights, given a week’s time and reporting, but the robot reinforcements allow us to detect novelty, react to it, and nip it in the bud super, super quickly. This paired up with zero trust postures, which were part of our trends last year, creates a sort of “guilty until proven innocent” defense mode, wherein those folks who try to do something unusual are detected quickly and stopped from getting anywhere else.
Tanya Ott: Scott, you better tamp down that extracurricular activity of yours.
Scott Buchholz: I am just disappointed that Mike called me out on it this time.
Tanya Ott: You know, going on at the same time, we have so many more devices coming online. We've got smart factories. We've got automated cooking robots. We've got inspection drones, a whole lot of data that needs—in a very basic way—monitoring and oversight. So, the tech stack is really important.
Scott Buchholz: That’s right. And it’s not just french-fry-making robots and smart hospital devices and smart manufacturing machines, but it’s also drones. We're seeing autonomously driven forklifts in warehouses. We’re suddenly having far more technology [in places] where the technology is interacting with humans—not in a digital way—but in a physical way. What that means is suddenly we have a new set of concerns. We have a new set of problems that we have to manage; a new set of opportunities. You can’t afford to have a drone fall out of the sky because there’s a software glitch. You can’t afford to have things go offline when you’re in the middle of peak service hours at a restaurant. You can’t afford to have a hospital monitor have a hiccup when it’s monitoring somebody’s health. What this means is that we have a new set of problems, a new set of challenges, a new set of reliability standards, and organizations are starting to rethink how they actually handle these things. We’ve suddenly created a new set of computers, in essence, these smart devices that have to be managed, maintained, connected, secured, and so forth. And in most cases, who better to do that than the IT organization, which is accustomed to doing this? And if you think about it, using the robot reinforcements for cybersecurity, using automation to clean up some of the IT back office—suddenly, now, IT has the capacity to take on these new roles and missions as we start putting more devices in our physical world and start making more digital products with which we interact every day. You can see all manner of examples, whether it’s Southern California Edison replacing helicopters for inspections with drones and learning that sometimes you have to put company jackets on folks so that people aren’t asking whether you’re checking the electrical pole or checking out their swimming pool. We saw examples from hospitals where [with] the latest trends in machine learning and artificial intelligence, they project that in 20 or 30 years, most surgery will actually be automated by computers, and that the surgeons will just be there for the tricky bits in the middle. All sorts of really interesting things [are] going on as we look forward to what’s new and what’s next.
Tanya Ott: Well, speaking of what’s new and what’s next, Mike, you are the futurist and you’ve got some field notes for the future for us.
Mike Bechtel: Yeah. You know, Tanya, every year over the [last] 13 that we’ve done Tech Trends, there’s been a recognition and a nod that as crunchy and enterprise-relevant as these novel client case studies are, there is a natural human need and business need for our clients to look around the corner and say, “Yeah, this is interesting, but where’s it going?” Well, for the last couple of years, we’ve begun researching and putting together a framework that we call our macro-technology forces. And lest that sound a little too nerdy, I would tell everybody that it’s a taxonomy for understanding where we’re headed by looking at where we’ve been. And in doing so, one of the things we found was that, you know, for the last 30 years—heck, the last 150 years—of information technology, innovations have been less a la carte revolutions and more reasonably straightforward evolutions along three specific train tracks. Those are interaction, information, and computation. Think of it as the user interfaces with which we connect to technology, the information and data and knowledge, [and] the insights we seek to extract from it, and then, under it all, the number crunching, [and] the computation that makes it go.
Well, with that frame in tow, we’re projecting that what’s next in terms of the way we interact with machines is something called ambient experience. MIT coined the term several years ago. What we’re finding is that with the quiet proliferation of everything from smart speakers to AR/VR technologies to screens not just getting smaller but going away entirely, the way we interact with technology is less about looking down at a glowing rectangle and more about reengaging with the world, asking to get our needs met, gesturing to get our needs met—better still, the technology proactively saying, “Hey, I have an intuition about what your needs might be. Let me help you get them met.”
On the information layer, what really seems to be next is exponential intelligence, or let’s call it emotional artificial intelligence. The idea here with AI is that AI is not new. Larry Tesler, an engineer back at Xerox PARC years and years ago, said AI is just whatever the heck computers can’t do yet. And so, in 1995, that was beating Garry Kasparov at chess, in 2005, it was beating Ken Jennings at Jeopardy, and then, in 2017, [it was beating] Lee Sedol at Go.
Tanya Ott: Just breaking in here to say that Mike’s a little off on the dates—Deep Blue beat Kasparov in 1997, Watson beat Jennings in 2011, and AlphaGo beat Lee in 2016. Next time, we’ll ask an AI to weigh in on dates, and let Mike concentrate on the squishy concepts that humans do best.
Mike Bechtel: We doubt these milestones before they happen. It’ll never happen! But then, we sort of brush them off when they do. Why? Because we have this pride of place as people that we want to create amazing things, but not so amazing as us; and so, when we project what’s next and AI—gasp! It’s increasingly human capabilities, the detection and emulation of human emotion, empathy, charm. A charismatic robot? It’ll never happen! Well, it’s already beginning to happen in call centers. You just don’t know it yet. That’s how you know it’s working. You don’t know it’s there. Moving a step forward, we’ll see creative artificial intelligence, generative AI. I like to say AI is moving from the math team to the theater club. And it’s just getting started.
Finally, in computation, what really seems to be next is this turn from digital to postdigital. Quantum computing represents an honest-to-goodness revolution in the way we go about solving tricky problems, turning the corner from math to physics and the wonky properties of subatomic particles, to solve problems not one at a time but in parallel. Massively parallel physical manners allow us to turn optimization problems, chemical modeling, [and] simulation problems from intractable 15-year slogs into reasonably straightforward 15-second solutions.
Tanya Ott: I got to say we’re having this conversation at the same time when I am watching the television series Foundation, which is based on Isaac Asimov’s book. And there’re just so many thoughts going through my head right now. But Scott, why don’t you bring us home with your final thoughts on the Tech Trends report and what we’re seeing there?
Scott Buchholz: What’s really interesting is that, mentioning Asimov, Tanya, we watch history repeat itself again and again—and part of that history is [the fact that] we’re all inspired by the imaginations of people, by the imaginations of writers, by the authors of science fiction. And, as we look around us, again and again and again, the things that people have imagined are starting to become real. As we look further out, the imaginings of the holodeck in Star Trek and the musings of Neal Stephenson in Snow Crash become these really interesting starting places for the metaverse, and what people think about that. As we try to imagine what’s over the horizon, we have all of these antecedents that people have cleverly thought of. With that said, the future is coming—whether it’s evenly distributed or not we can talk about over a beer—but the larger point is organizations that are delaying starting any of these journeys are in the process, and will be, and continue to be in the process of finding themselves further and further behind because many organizations are embracing these journeys. They are getting inspired from the science fiction. They are inspired by the future. And we would encourage everybody to get started on the journey, and they are always welcome to reach out if they have questions about what we think is new or next, or [is] just really interesting.
Tanya Ott: Mike, Scott, thank you so much. We’re going to be looking forward to watching what develops over the year and then bringing you back next year to talk about Tech Trends 2023.
Scott Buchholz: Looking forward to it.
Mike Bechtel: Thank you.
Tanya Ott: Mike Bechtel is chief futurist and Scott Buchholz oversees emerging technology research, including the Tech Trends report, for Deloitte Consulting LLP. There’s so much packed into the 2022 edition of the report—we weren’t able to get to it all. But you can find at Deloitteinsights.com.
We’re on Twitter at @deloitteinsight and I’m at @tanyaott1. Thanks for listening, and have a great day!
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