Category: Health

Christina Cardoza: Hello and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech. And today we’re going to be talking about the rise of intelligent networks thanks to 5G and AI with Ian Fogg from CCS Insights. Hey, Ian, how are you doing?

Ian Fogg: Hey, doing well.

Christina Cardoza: Thanks for joining us today. Before we dive into the conversation, can you tell our audience a little bit more about yourself and what you do at CCS Insight?

Ian Fogg: Sure. So, we’re a research and analysis company. I lead the networks or the network-technology research at CCS Insight. Before CCS Insight I’ve worked with operators, analytics companies, other analyst firms. So, really many, many years of experience in network technology.

Christina Cardoza: Awesome. Looking forward to dive into it. We just had your colleagues Martin Garner and Bola Rotibi on the podcast. We were talking about IoT protections for 2024, specifically in the edge and AI space. But as part of that report—and I encourage all our listeners to go take a look at that report to see what’s coming over the next couple of years—but as part of that report there was a lot about 5G and networks in there. So I wanted to chat with you today a little bit more about what can we expect in that space, and these things sort of run parallel sometimes.

So before we jump into what we have coming, let’s take a look about where we are today, or what got us here today. So can we just start off explaining how has the 5G- and IoT-network landscape changed over the last few years? What have you been seeing?

Ian Fogg: Sure. Well, I mean 5G first launched back in 2019, but that was really very early versions of the 5G standards. And what we’ve seen more recently is tremendous enhancements in what 5G is capable of. We’ve seen 5G being used for more and more different things.

So one of those is, for example, private networks, and we’re tracking the number of private networks that are launching or are being announced. For example, in 2023 up to Q3, we saw 1,279 private networks announced with revenues of over €100,000. That’s up from 1,081 in 2022 and 761 in 2021. 5G was deployed in 45% of those networks we saw announced in 2023.

We’re seeing other things happen too. We’re seeing non-terrestrial networks arrive. We saw a lot of activity in that last year around this time, with announcements from, at the time, Qualcomm, and that’s part of the upcoming release 17 5G standard as well. We’ve seen more focus around REDCap—reduced capability—on 5G starting to be talked about by the vendors, but not really out there yet in the market.

One of the other things we’ve seen happen last year is the operators announce OpenAPI initiative, something the GSMA—the operators organization—has been very big on. And that includes network APIs too, to manage network quality and other network-type settings. So we’re seeing all kinds of things happening over that last year.

Christina Cardoza: Absolutely. A lot happening and, like you mentioned, 5G started to come around, maybe around 2019. The conversation started well before that, and the conversations are still happening. It always amazes me how much 5G is being adopted or deployed, and how much there is still to come and how much we still have work in this space.

So, what would you say, looking to 2024 or even beyond that, what would be the next step for 5G in these IoT networks coming up?

Ian Fogg: Well, this takes us back to the predictions that we put together at the end of last year. So, some of these are related to what I just said, some of them are looking a bit beyond that.

So, one of the predictions we had was that by 2025 a digital marketplace for app-based network functionality offers more than a hundred versions of network capabilities and APIs. We’ve seen some small initiatives, but we expect that to expand tremendously over the next 18 months or so.

We’re also expecting that hybrid private and public 5G, through network slicing, emerge as the dominant option for private networks by 2030. So what that is, is that a standalone private network is using a dedicated network just for that offering. But a hybrid solution is using some of the new capabilities of standalone 5G, network slicing to give you a quality of service that is different to other people using the wider cellular 5G network. And that then bridges the gap between a location where an enterprise may have the dedicated private network, but they maybe want people or devices to move between those dedicated sites. And the macro network, the regular 5G network with a network slice, bridges the gap—a hybrid solution. So that’s something we see becoming very dominant by 2030. And obviously it’ll happen not just suddenly in 2029; it’ll happen gradually over time as we see something happening.

Something else we see—although there’s been some negativity around NTN—we see that continue to grow. It’s valuable for the IoT space. If you think about container tracking, it doesn’t require very high bandwidth services. But there are other things that we see happening very near term, like the smartphone space, where we see that’s still growing despite some of the negativity; there’s a lot of activity in that space. It’s part of the upcoming 5G standards, part of release 17 to have a non-terrestrial network capability. And by 2027 we expect 15% of smartphone users have satellite-enabled devices.

Now, what does that mean for IoT? Well, often what has happened in the past is the consumer space has driven innovation that then gets reused for other things because there’s a commonality. Once you’ve built that satellite capability, the satellite players can choose to support more than one type of customer.

Christina Cardoza: Great. Now, you mentioned more of a rise in hybrid private and public networks. When I think of these terms, I equate them to the cloud: hybrid cloud, private cloud, public cloud. Is this the same concept of using networks? So, for instance, when you have more mission-critical solutions or applications, those would be on a private network, much like they’d be on a private cloud. What’s the distinction there, or the similarities between the different types of cloud uses and then the network uses? Will these things be parallel? Also, if you’re using a hybrid cloud, would you likely be using a hybrid network?

Ian Fogg: I think it depends on the use case. You think about a hybrid network, the key thing that’s really driving that’s, that’s enabling that, is this switch from the initial versions of 5G that started back in 2019, which were using what’s called non-standalone access. They relied on a 4G core network, which means you didn’t get all the capabilities of 5G that were being hyped in the 2017, 2018, 2019 period. You need to have the 5G core network up and running at the mobile operator, at the service provider. And that enables a whole load of new network functions, and one of those is this thing called network slicing, where you can have essentially a dedicated quality of service. So that’s something that’s happening.

I think the cloud space is parallel, but I think it’s an interesting analogy to say, well, there’s more than one type of cloud; there’s more than one type of network that can offer a high quality of service.

Christina Cardoza: Great. And at the same time that all of this is happening, 5G is getting more advanced and we’re adding more capabilities to it. The demands and the needs of the Internet of Things is growing also; companies want to connect to the internet more. They want fast, reliable, real-time information, and that requires the network to work fast also. So how can the network and 5G keep up with this ever-growing demand of IoT and some of these more intelligent solutions and devices coming online?

Ian Fogg: Well, I think this hybrid capability is particularly important, because it does bridge the gap between maybe a dedicated network that’s maybe a dedicated private network that’s maybe in a port or in a manufacturing facility or in maybe a warehouse or a barn or something.

I mean, one of the areas we looked at here actually for hybrid private networks or hybrid 5G was around precision agriculture. And if you imagine agriculture, you have the farm, you have some farm buildings where you may have a dedicated capability, but you can’t put that over the whole farm area. It’s far too big, far too problematic. And that’s a classic example where a hybrid solution enables an agricultural offering to have a high quality of service right really across a wide range of areas.

One of the other things I think we see as an important thing at the moment, and increasing so, will be using AI in a whole range of different areas. We think AI is going to be important in a range of types of products in different parts of the network. But one of them is we see that AI enables 5G networks to improve their availability significantly, perhaps even to move beyond five-nines availability by managing the traffic patterns better, by making sure that the network isn’t just on, it’s offering a good enough quality of service and managing around outages or downtime issues to give a self-healing element to the experience. So that’s something else we see increasingly important on the network side.

Christina Cardoza: I love that example of the agriculture and in the farm, because that’s one of the examples that IoT is just growing and demand for it—farming, you wouldn’t really think becoming online or using these advanced capabilities, but that’s just the reality today. Every industry around the world is leveraging Internet of Things and and network.

I want to dig deeper a little bit into the role of AI. You mentioned that it’s going to be improving availability and it can do things like self-healing. So exactly what’s going on in this space? How can AI be utilized and be applied to do these things and enhance the 5G and IoT networks?

Ian Fogg: Well, the network guys are using AI on all kinds of areas. They’re using it to improve the RAN management, because as you’ve gone from original 4G to 4G Advanced or LT Advanced, and then onto 5G and then onto release 17 and onwards, the complexity of the RAN has got much greater, and there are more settings that need to be managed. The interaction between the base stations, between different frequency bands, is much more complex, and AI is a key way of enabling ongoing management of that RAN to improve the coverage and improve the performance.

We see it being very important in the Open RAN rollout too. So, Open RAN is something where, historically, service providers have bought a base station from a network vendor, and everything is basically integrated and included from the same vendor. The concept of Open RAN is that there are interfaces within that base station so that a service provider can mix and match different suppliers. And we think the complexity there is something that AI can help improve the Open RAN experience and help drive Open RAN adoption. So we think that that’s very important too.

Something else we think is interesting and important is around green issues: hitting carbon targets, managing energy costs on the network. And, again, what you need to do there, if you’re a service provider, is you want to keep the performance for your user base good, but minimize the energy usage. And so you want to drop the energy usage but still maintain the network experience. So how far can you cut back network resources and yet still offer the experience that users need.

And that’s something where a machine learning tool can help with that RAN optimization. And we feel by 2025 a combination of intelligent radio access network–technology, automation, and AI-driven power-down techniques enables at least three leading operators to bring forward their carbon-neutral targets by several years. It’s one of the predictions in our report.

Christina Cardoza: Yeah, I was just going to ask that. It’s interesting because I think over the last couple of years sustainability and green issues have been a top concern for industries all over the place and being able to use AI and even these 5G networks to hit some of these goals. So I was just going to ask what you predict for the next couple of years: is it going to be more important, and do you see organizations and industries actually being able to reach some of their goals, or those goals really becoming a reality over the next couple of years with some of the capabilities happening in 5G and IoT networks?

Ian Fogg: One of the sustainability angles here is around smart grid. There’s obviously a massive drive to remove coal, oil, and gas carbon technologies from power generation. One of the options to replace there is obviously nuclear. Nuclear has enormous capital cost, long lead times, a lot of complexity. So a lot of people are looking to solar and wind power as a cost-effective and versatile way of generating green electricity.

The challenge there is that solar and wind power generation is not always predictable—depends on cloud cover, on the solar side, and time of year. And on the wind power, it just depends on what the weather systems are doing at the time things are happening. And you could have night times where there’s too much power being generated and you want to encourage end users to consume some of that electricity. There may be other times you want users to drop their energy consumption because it’s too expensive or there isn’t enough green power being generated.

So we think greater use of solar and wind power necessitates that smart grid technology to manage the supply and demand. And we expect smart grid technology will become widely adopted in most advanced economies from 2028, if not before. But we can see some signs of that happening even now.

Something else we see as important is power-as-a-service, an integral part of tower infrastructure services by 2025, because one of the challenges or one of the difficulties of getting power to tower sites: it’s difficult, it can be time consuming, it can depend on permits. But what we see happening there potentially is the tower company managing the power to the site. So, taking a greater role in the site management than they have done before. And we think that’ll become a cornerstone of tower companies’ offerings by 2025.

Christina Cardoza: One thing that interests me about the smart grid is obviously we have all of these new and intelligent devices connecting to the network and going online, and we need to prepare the grid to be able to handle all of this at the same time we’re trying to be more sustainable. And then as part of being sustainable people are using more—electric vehicle technology or electric technology and plugging that into the grid.

So is there anything happening in the 5G or network space that is going to be able to help that demand or help the smart grid really become smart and become more sustainable at the same time?

Ian Fogg: So, if you take electric car EV charging, typically you want to do that overnight if you can, if it’s on a residential solution. So you can see a range of ways that network technology come in there. Many EVs have cellular capability, so the user can remotely control their car and set the power-saving modes, tell it where and when to schedule the charge. Many EV chargers in the home have also a similar remote control—often that’s on Wi-Fi or something else.

But then you have smart meters in the home, which typically have a cellular connectivity. So the power company can monitor what’s being used and charge people—in some cases charge people in very granular ways. There’s a power company in the UK, for example, which has a tariff which has half-hourly pricing. So the pricing varies dynamically during the day based on what the power generation and the overall consumption is. So you can see it in different places—whether it’s in the EV, you have connectivity; whether it’s in the EV charger; whether it’s in the smart meter—three different places just involved in the end-user EV charging process where you could see network technology becoming very important.

Christina Cardoza: Great. Yeah, it’s definitely very interesting to see. We always talk about these elements different from one another, as silos: this is what AI’s doing in this space, this is what network’s doing in this space. But it’s really interesting to see it as an end-to-end solution, how we’re using all of these technologies to really meet these goals and to make some of these ideas as a reality.

One thing I wanted to talk about is, obviously from this conversation it sounds like there’s still a lot of work to go in 5G. 5G is still going to be around for a while and keep improving itself and improving industries and businesses and other technologies. But we’re already hearing some rumblings about 6G come up. So I’m not sure if it’s too early to start talking about 6G—what’s the reality there? People are getting hyped about this, but where are we with 6G? When should we prepare for 6G, and how long will 5G still be dominant?

Ian Fogg: So there’s absolutely work happening on 6G, and I’ll talk about that in a second. But I think you are absolutely right: that 4G is still important in the 5G era. You think about that EV scenario I mentioned a second ago: most EVs, they have cellular; it’s a 4G cellular radio. You have a smart meter: it might even have a 2G radio in it, let alone 3G or 4G. Although they’re obviously progressing and upgrading them to 4G to enable a 2G switch-off to happen. So these network eras tend to overlap.

So even when 6G arrives, 5G will continue to be important. 4G will still be probably around as well, because these things are interoperable and they will continue to exist. The reason 6G is interesting and the things we can already see happening are we can see spectrum discussions being advanced.

We saw WRC—the international conference that happens every few years to coordinate spectrum alignments globally—so there are large economies of scale in any of these offerings. Discussion happened there around 6G bands—typically in the cellular space—people looking at the 7 to 16 gigahertz range. But there’s also some terahertz capacity, which is very, very high frequency. If you’re familiar with some of the 5G offerings using millimeter wave, this is even higher frequency than that, which is also being discussed—very line of sight, very, very high capacity, probably very short range. So there’s work happening.

There’s also work happening on the use cases for 6G. One of the use cases, which is different to what we’ve seen before, is using the cellular network to sense what’s happening. It could be sensing how much traffic there is in the roads, sensing people walking down a pavement. And that is something which is—you can see examples of that are happening now. Some of the—in the home, for example, some of the Wi-Fi access points can sense whether people are at home and use that as an alarm system, like a crude alarm system. But that’s quite a crude offering at the moment.

But part of the thinking around 6G is the 6G network would have a wider sense of capability to sense things happening across cities, across large areas. And then of course that means you can then draw analytics from it and make actions on the back of that. And that’s one of the key new use cases that’s being discussed around 6G.

In terms of timescale, which you asked about, is stuff’s happening now. I guess it depends who you are. If you are a company looking to deploy something today, 6G isn’t probably relevant. If your product roadmap is much longer, if you’re looking at kind of around 2029, 2030 or onwards time, and if you are starting to work on those sorts of things in your roadmap now, then 6G should be something that’s in that roadmap. They’re obviously not imminent, but back off. If you are a network vendor, then your R&D labs are fast furiously working on 6G things at the moment. And you are much more advanced in your 6G thinking.

Christina Cardoza: I think that point you made about there will still be some overlap and these technologies are interoperable, so I think that’s a really important takeaway for listeners. Also, obviously you just mentioned all of these benefits and capabilities and new use cases that are coming with 6G that can make the industry very excited to hop on it, but it doesn’t have to be a “6G is here now; move everything to this technology.” There is overlap, there is interoperability, so you can move things over slowly, what makes sense and with time, and be more purposeful about these changes coming, rather than going in all or nothing. So I think that that’s a great point. This has been a great conversation.

We’re running a little bit out of time, but I’m just curious, in this space, are there any final key thoughts or any predictions you want to leave us with, what we can expect to come?

Ian Fogg: I think just one last one on the 6G side. So, one of the predictions we had around that was that by 2030 the first 6G-powered, massive twin city is announced. Digital twinning is this idea of having a replica of the physical world in the digital world. And we see 6G being important in that, partly because what we just talked about around sensing and around smart city–type uses, 6G will have a lot more capacity; it’ll probably have much lower latency, more consistency, and it’ll have this sensing capability too.

I mean, one of the classic areas I think this might get deployed is perhaps in the Middle East, in the Gulf region, where there’s enormous efforts to build a number of massive new cities basically from scratch. Greenfield—well, not greenfield, because it’s the Middle East—but in new locations, a planned city. And if you are building something from scratch, you are able to do things differently, and it may well be that the first massive digital twin city 6G enabled happens in that region for those reasons.

Christina Cardoza: Wow, 2030 sounds like a long ways away, but we’re already in 2024, so, yeah. It’s going to be here before you know it. So I’m excited to see how this space progresses to get us there over the next six years, where else 5G and IoT networks are going.

But it’s been a pleasure talking to you today, Ian, about this. Again, it’s been an insightful conversation, and for our listeners who want to learn more about the CCS Insight predictions, we will have that ready for you. You could dig into the edge AI and this network space also. So thank you again for joining us, and, until next time, this has been the IoT Chat.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel^® trademark information.

This transcript was edited by Erin Noble, copy editor.

Christina Cardoza: Hello and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech. And it’s that time of year again where we’re going to look at the top IoT and AI predictions for 2024. And joining us again on this topic we have Martin Garner and Bola Rotibi from CCS Insight.

So for those of you who aren’t familiar or didn’t get to hear our last podcast with these two experts, let’s get to know them a little bit before we jump into the conversation. Bola, I’ll start with you. What can you tell us about what you do at CCS Insight?

Bola Rotibi: I’m the Chief of Enterprise Research at CCS Insight. I have a team that covers software development, workplace transformation, cloud, AI of course, security—quite a whole load, but everything to do with the enterprise.

Christina Cardoza: Great. And Martin, welcome back to the show. What can you tell us about CCS Insight and yourself?

Martin Garner: Thank you, Christina. Well, yes, I’ve been at CCS Insight for 14 years. I lead the work we do in IoT, mostly focusing on the industrial side, and so work very closely with Bola on those areas.

Christina Cardoza: Great. And, Martin, since you’ve been at the company for, like you said, 14 years now, we’ve worked a bit over the last couple of years. You guys always have an IoT prediction you put out at the end of the year, and we’ve always worked to talk about that and to see what’s coming next.

So I’m wondering, in the last year or even the last couple of years there’s been a big push to edge and AI. So I’m wondering how that impacted this year’s predictions and what we see coming for 2024.

Martin Garner: Sure. Well, obviously 2023 was a huge year for both of those areas. Edge was already growing strongly coming into this year, and I think 13 months ago ChatGPT had just launched and has clearly had a massive impact during this year and has really opened the world’s eyes to what AI can do—and quite a few things that it can’t do yet. So I think it’s fair to say that the world is now thinking rather differently about the two areas, and we are too.

So in our predictions last year we had lots about edge and some AI. I think for anyone who downloads the booklets at the end of the podcast you’ll see that we really dialed up the AI predictions this year. And it’s important: it’s not just generative AI like ChatGPT, and it’s not just what individuals can do with AI.

And there’s one prediction I’d like just to give as a little example of that, which is that by 2028 a major healthcare provider offers its customers a digital twin service that proactively monitors their health. Now today there is a lot of data about you scattered around—so we have online health records in many countries; we have fitness bands; we have smart watches and they show activities, sleep, and so on. There’s lots of data on your phone, but it’s all a bit messy and it’s not joined up at all.

So we think that healthcare providers over three to four years will start to combine these sources. We’ll use AI and we’ll basically do what the industrial guys are already doing, which is predictive maintenance on people. And of course the aim is early intervention gives smaller intervention, and it’s usually cheaper intervention too. The outcomes are just better if you get there earlier. So that’s an example of how we think AI will start to develop from here.

Christina Cardoza: Yeah. And I love what you said—we’ve learned a lot about what we can actually do with AI, or what’s possible. There’s always that hype or that trend that everybody wants to jump on right away. So I want to dig a little bit into that.

But before we get there, just this movement to—with AI and this movement to edge and having, wanting to get information at real time and faster—there’s been a lot of movement also to the cloud with all of these solutions and applications. And I know there’s always that cloud-edge versus on-premise debate. Will that continue? Or will people continue to move to the cloud over the next couple of years, or is on-premise still going to remain steady?

Martin Garner: Well, it’s a good question, and I think that debate is going to remain live for a good few years. And I want to draw out just a couple of ways of that. So one is quite short term. I think in many countries there are fears about where the economy’s going. We’re not quite out of all the pandemic effects yet. So one prediction is that recession fears push workloads from the cloud to on-premises through 2024.

Now, the best candidates for that are companies which are using hybrid cloud. It’s not so much those who’ve gone all-in on the cloud. And there are a few new initiatives, like HPE GreenLake and Dell APEX, which bring the flexible consumption model that we have in the cloud—they bring it to hardware and allow you to do that at the edge as well. So it may be that a hardware refresh in some of those companies is a good opportunity to rationalize some aspects, sort of repatriate some of their workloads to on-premises and take some cost savings while they’re doing it. So that’s the short term.

Longer term, we think there are several areas where there are sort of pendulum swings, like insourcing versus outsourcing, and edge to cloud could be one of those. And it’s partly also that there are new tools and different economics coming up in both areas. So it’s all changing quite fast.

But one area where we have another prediction is that a repricing of cloud providers’ edge computing services takes place by the end of 2028. Now, what does that mean really? Well, the big cloud providers, they all have edge computing services, but actually the public cloud is the big part of the business. And the edge services, they’re sort of on-ramp for the public cloud, and they’re priced to do that. But the forecasts for edge computing, they show it growing bigger than the public cloud over five years, possibly a lot bigger than the public cloud.

Now, if that happens, then we’d be in a position where the big part is subsidized by the smaller part, and that makes no sense at all. So we really expect the edge-cloud services, their prices to be moved upwards over three to five years, and that could be a significant price rise. So we think many industrial companies might want to consider their own edge computing, just in case—put themselves in a better position so they have more options. It’s edge as a hedge, if you like, and kind of gives them more options about how they go forwards.

Christina Cardoza: Yeah, absolutely. And that’s a great point. Companies, they don’t want to be locked in with a vendor. Like you said, more opportunities. They want to make sure any investments they make—because they do make a lot of investments to move to these solutions to build these—they want to make sure any investments they do make they can future-proof them. I think a lot of it driving it too is the type of solution that they’re building. If it’s more critical workload or they need more security, they tend to move on premise. If they need real-time analytics or they need faster results, that’s sometimes the cloud and the—where the edge computing comes in.

So I want to talk a little bit about AI development with you, Bola. What can we expect in terms of the AI solutions or the developments happening over the next year within enterprises?

Bola Rotibi: Well, I think—I mean it’s a good question actually, because I think we’re going to expect quite a lot, and I think, whilst 2023 has been kind of a year of—we’ve seen a year of launches, especially from many of the IT solution providers, there’s been a wealth of new tools. I mean, obviously when ChatGPT launched last in the end of November 2022, it really spawned massive interest, and we’ve seen it exponentially grow, especially with generative AI.

But I would say that the development of AI has actually been happening for quite some time, because it’s been machine learning and various other sort of models and algorithms that people have used behind the scenes. So anything that you’ve been using on your mobile phone to search through pictures and all those, those are kind of like AI solutions, AI models. So this AI itself is not new, right?

But what we are seeing is the power of generative AI, especially as we think about the productivity. You know, everyone has sort of latched on to the conversational aspect of generative AI and its ability to simplify even sort of complex queries and bring back concise information that is relevant information. So everyone’s jumping on that because we see that as a productivity solution.

So what we’re seeing now is a launch of lots and lots of solutions. Over the last year we’ve seen pretty much every provider—Intel amongst those as well—bringing out generative AI capabilities, as well as beefing up their own AI solutions. But one of the things that we’ve seen here, we’ve seen Microsoft launch with the Copilot AI-powered assistance. We’ve seen others from other providers like AWS with Amazon Q.

But I think what we’re—what one of the things that we do think is that despite all this frothiness around the interest, we did have a prediction which actually said AI investment and development will accelerate in 2024, it does accelerate in 2024—despite calls for caution. And we’re already seeing the throughput of this already. And the reason we see this is that actually quite a few of the main protagonists, I mean over the recent months have said, “Well, hold on just a minute. We need to kind of slow this down. Things are moving rather fast.” And people are a bit worried about security; they’re worried about whether the regulations are out there, whether they are effective enough. And all of this caution is still kind of wrapped around.

But at the same time I think there’s a real thirst to get AI, to develop it, to really get their hands on it. Because people have been blown away by the new experiences and the engagement levels that they can have, especially with generative AI. So I think there’s going to be even more acceleration next year.

Christina Cardoza: Yeah, absolutely. And a lot to dig in there. I want to start off with the generative AI piece. And, like you mentioned, the possibilities—it brings so many benefits that a lot of companies are trying to jump on this, and I always hear in the back of my head, one of our guests on the podcast was saying, “You want to create solutions that solve a problem, not create solutions just to create a solution, just to jump on the latest trend.”

So I’m curious with generative AI, because obviously, we’re seeing all of these companies talk about it—all of these releases and with AI toolkits adding generative AI capabilities, there’s been a lot of hype. What’s the reality? What do you think will actually come out of this space in the next year, and what can we be looking for? What are the applications or use cases that are possible?

Bola Rotibi: Oh gosh, that’s lots and lots of questions. Well, first of all I think there is a lot of froth around with generative AI, but that’s because everyone’s been, as I said earlier, been blown away by the productivity that they’ve seen from it and actually the intuitiveness of it all, and just really being able to talk or put together natural language queries and then get back concise information.

That said, I mean, one of our predictions that we outlined is that despite all of the excitement around generative AI and the fact that we’ll see lots and lots of new tools, we do think that, 2024, we’ll see some level of slowdown—partly because as people kind of get to the grips with the reality of the costs, some of the risks and the complexities that really, that become, start to be exposed and have been starting to be exposed this year, I think that we’ll see a slow, a slight slowdown.

But, despite that, I mean I’ve—it’s a bit of a thing where you’re sort of saying on one hand it’s going to be really, really great and really fast. On the other hand we’re going to see some slowdown. What I think, as with any technology, there will be people just trying all sorts of capabilities.

Nowadays you can go in and you can start typing in queries, and then immediately get very, very concise answers back. And what we’re also seeing is that we’re seeing generative AI in multiple perspectives. So we’re seeing it as an assistant to providing information to relevant information across lots and lots of different data types. We’ve also seen it being able to create, generate code that is very good quality—that at least is a starting point, especially the experts to finalize it and sort of do a little bit more quality control.

So I think we’re going to see—so on one side I think 2024 is really where people get to start to play with it properly. And the tools, they’ll get to start to understand some of the limitations of the tools, as well as what they’re going to be able to achieve. So I think it’s going to be, on one hand the hype of 2023 will start tempering down into much more of a more level-headed sort of approach to it and more nuanced, as well as the excitement of actually delving into some of the capabilities, like generated code. We’ll start seeing it across different types of workplace solutions, helping knowledge workers, but also helping expert professionals—whether those be expert developers or other professions as well.

Christina Cardoza: Yeah, it’s interesting because we may see a slowdown in some of the hype or everybody jumping onto this trend. But, like you mentioned, we’re going to see an increase in acceleration in AI investments maybe in other areas. And, like you mentioned, that we’re going to see an acceleration despite the need to maybe take a slowdown to take a step back and look how we’re developing things.

And, Martin, I know we’ve spoken in conversations outside of the podcast that AI oversight committees, this might be something that is coming. So can you talk a little bit more about what that means? How can we develop, or how do you anticipate ethical AI initiatives to spring up as this investment and this acceleration continues?

Martin Garner: Well, yes, of course. And you’re right, we touched on it before. It’s a big subject and we could talk all day about that. We’re not going to. So the short answer is, yes, there’s going to be a lot more of that. And I think you already said it, Christina, that AI does have the potential for many, many good uses in society. But also used wrongly it has the potential to do a huge amount of damage, and it’s a bit like medicine, where regulated drugs are generally good for society and unregulated drugs like opioids and fake Wegovy and things, generally not so good.

And the big difference with medicine is that there’s no professional body, there’s no Hippocratic oath. You can’t be struck off as an AI practitioner, at least not yet. And so at the moment instead we have the opposite, where the AI leading companies, they seem to be on a big push. As soon as something new is developed they open source it and push it out into the world as fast as possible. And that obviously puts a huge imperative on suppliers and developers to take their own ethical stance in how they use it—which customers are they going to deal with or not deal with, how to train their staff, internal governments. There’s lots to get right there. But it also puts an onus on companies who are using AI as customers, and they need to step up too.

And so we do have a prediction, which is that AI oversight committees become commonplace in large organizations in this coming year, 2024. And those are likely to be committees of ethics experts, AI experts, legal advisors, data scientists, HR, representative from the different business units, and so on. And they’re going to have to review the use of AI across the company and in the company’s products. And their job really is to bridge the gap between the tech teams who are all engineers—they’re not typically ethicists—and the organization and its goals and what it wants to do with it.

And we think that’s going to be quite a significant overhead for a lot of companies. Quite difficult to get right. Lots of training to come up to speed and to stay on top of it, because it’s all moving so fast that the committee will have to move fast too. And all that because the AI industry is largely not doing a good job of self-regulation.

Christina Cardoza: One thing I’m curious about is the EU is putting together the AI Act, and I’m wondering what will this mean for developing solutions with the GDPR? You know that that was in the EU, but that was a global impact. So do you anticipate the same thing happening when the AI Act has passed?

Martin Garner: I think probably Bola is the better one to talk on that, if I may. Can I hand that one to Bola? I know you’ve been looking—

Bola Rotibi: Yeah, no. Yes, I think definitely actually, because at the end of the day I do think that the regulators are coming together. The EU has been first out the door for starters with the EU AI Act. But when the act does come in, it will be like the GDPR Act. And I think what will happen, and we’ve already seen the ratification of the Digital Markets Act, and we’ve already seen the effects of that with some of the companies who are being highlighted are still trying to get bedded in into whether they are the main gateways.

But I think when it finally does come through, I think there will be sort of a bedding-in process as people try to get used to it, try to understand what it means, what all the constructs, see all of the rules and regulations. So there will be kind of like teething problems, but I think it will actually, it will become a thing, a regulation for people to rally around.

But the EU is not the only one. We’ve got the acts in the US, and we’ve also got the UK pushing to having a really strong play with AI regulations. And then we’ve got China and in other regions as well. So I think we’re going to start seeing some level of improvement in terms of—towards the end of 2024, certainly, as people rush out to see the frameworks regulation. And I think that will be really important.

The other thing that’s actually happening, and it’s not just about regulation at the international level and the national level, but it’s also what the industry is doing. And I think there’s some really exciting things that have been happening. Recently IBM and Meta and Intel amongst—as part of 50 organizations that have launched the AI Alliance, which is aimed to bring the industry together to work on collectively—like any other body—to standardize, like working groups, to bring working groups together, to come up with ideas for strategies and approaches to handling certain AI challenges and opportunities, to be the home or the hub for interactions between end users as well.

Christina Cardoza: I love seeing all of these AI efforts, especially from big tech companies, because AI has a lot of benefits, it has a lot of opportunities and ability to transform industries and transform our lives for the better. But there is that level of uncomfortability from end users—how their privacy is going to be used, how secure the data is, what’s it going to do, how it really is going to transform their lives. So I think this helps put a safeguard and minimize some of the risks that people think that are out there.

And I’m curious—because obviously we can’t wait for some of these acts or some of these efforts to be passed or to take off before we start developing in a more ethical way—so I’m just curious, Bola, you work with developers. How can they continue to develop these AI solutions with privacy and ethics in mind and ensure the safety and security of their solutions and of the end users?

Bola Rotibi: Well, I mean it’s a good one actually, because I think invariably what’s going to happen is that I think lots and lots of—how to say—there’s likely to be oversight committees within organizations. That’s something that we’ve actually put down in the prediction of ours. But I think one of the things is that there will be communities that will work within organizations to kind of understand what it is that they can do. Many of the tools that they are actually using now and many of the providers are building in that responsible AI, ethical AI, from the ground up.

What developers have to then start thinking about—and this isn’t just on the developers, because actually at the end of the day a developer might think, “Well, actually, I’m building code, I’m generating—I’m building a code, I’m writing an application.” But at the same time, in the same way, that security is actually down to everyone. Everyone in that workflow. So is responsibility—responsible AI and an ethical approach. It’s down to everyone.

So I don’t see it’s just a developer requirement, but at the same time you have to say there needs to be frameworks in place, and that needs to be driven around the whole organization. It needs to come from the ground up. It needs to go from the top down. So there needs to be some principles that are used and distributed and circulated across the organization. And there needs to be some sort of guidelines.

Now, the tools are coming with guidelines and guardrails, right? In terms of, “Okay, how do I prevent certain things happening?” Because you can’t expect anyone who’s always developing to have everything in their heads about, “Oh, okay, is this ethical?” Of course, you could ask yourself, “Well, just because I can do it, should I do it?” You know? And that’s always the case.

But, at the same time, if you want a level of consistency, we need to have, provide, those guidelines and to the organization, to the development organization, right across the board. But there needs to be guardrails. And I think many of the tools are recognizing this so that they can actually allow organizations of any size to put their own policies in.

So I see going forward that there will be a layered approach. So that may be an oversight committee within the organization that thinks about what it is that the organization is from an ethical standpoint, from a responsibility standpoint, and start building policies. And those policies will be driven and put into the tools so that they act as guardrails. But there’s also going to be guidance and training of developers in terms of taking an ethical approach, taking a responsible-AI approach.

So I think, going forward, it’s a bit like how do you do right, knowing right from wrong? But this is something that the development community already is aware of. There’s a lot of things out there, a lot of programs, a lot of initiatives out there, things like aiming for doing code for good. Lots of organizations have been thinking about impact, about sustainability, and all those kind of things. So there is a body, sort of a body, a wealth of already ideas and initiatives to make the people think at multiple levels, not just about responsible AI, but doing the right thing, thinking about sustainability. So I think the approach is actually is already there for many developers, but they do need help.

Christina Cardoza: Yeah, and I love what you said: it’s not—one camp is not responsible for this. It’s really a collaborative effort from everybody building it, everybody using these types of solutions, everybody touching AI. So I love that.

We are running a little bit out of time, but before we go I just want to change the conversation to a different topic real quickly while I have Martin on the podcast, because Martin, we’ve talked over the last couple of years: We’ve been talking about 5G. Are we looking to 6G? Where are we in the 5G efforts? Is it still beginning? So I’m just curious, as we’re talking about AI and Edge, where 5G fits into all of this, what the impact of AI is going to be on f 5G networks, and when is it time to start looking at 6G?

Martin Garner: Yeah, 6G, I love that. We’re not, we don’t quite have all the good bits of 5G yet, do we? They’re coming, but they’re not quite here yet. So—but there is work going on 6G.

So in terms of AI and 5G I think the first thing is that organizations who are starting to use 5G in their factory, in their warehouse, in private networks up and down the country and so on—one of the things 5G will do is enable a lot more use of AI thanks to the very high capacity, the time-sensitive networking location services it will bring in. And we’ll see a lot more AI in use around those domains. A lot more autonomous vehicles and things. We can already see good examples of autonomous trucks used in mines in Latin America and in ports in many different continents and so on. Lots and lots more of that to come with 5G and the newer bits of 5G, which are nearly here, as one of the key sort of enablers of that.

But I think the other interesting bit is the impact of AI on the network itself. Now, there are several tricky aspects if you try to buy and use 5G. So things like coverage planning on public and private networks. Very good candidate for using AI to make that simpler so that more people can do it. Also, 5G networks, they’re complicated things. They really are a very high number of settings and things. And so the whole optimization and management is a big deal in a 5G network.

And we have a prediction around that, which is that AI enables 5G networks to move beyond five-nines availability, which anyone who’s used a cellular network will appreciate the importance of that. And that would come through by analyzing traffic patterns and ensuring that the network is set up best to handle that type of traffic, identify problems, predictive maintenance, and configure the network—if things are going to go wrong—so it has graceful degradation or even become self-healing.

And we think there’s a lot more that networks themselves can do with AI to become much better quality and really support not only people up and down the country on the public networks, but also really the OT world—which absolutely, if they use it a lot, they will depend on it, and it’ll be very expensive when things go wrong. So supporting that requires that degree of quality.

Anyway, then 6G. It is a tiny bit early for 6G, but work is going on of course. And over the next five years or so we’re going to be building 6G networks. We think 2030 is going to be a bit of a headline year for 6G. And we have a few 6G predictions. Here’s one: which is that by 2030 the first 6G-powered massive twin city is announced. And we think that cities will be a great showcase and massive twinning is one of the best use cases, because all the layers of a city could be potentially included in the model there. And the 6G network could enable a sort of full representation of the whole city environment.

We don’t think that’s likely to start with older cities—much more with a new project such as they’re doing in Saudi Arabia at the moment. And if we do that, they’re going to need 6G just for the sheer volume and speed of the data in real time that runs through a city. So that was a really good example. We think 2030, big headline year for that.

Christina Cardoza: Yeah, absolutely. And I agree, we still have to fix or finish the 5G aspects that we have there, but of course you have businesses or companies out there already trying to talk about 6G. And I agree that for all of these AI solutions and benefits and opportunities we want to take advantage of we need to make sure the infrastructure is there to make it possible first.

Martin Garner: Yeah, and working as well as it can.

Christina Cardoza: Yeah, absolutely. So this has been a very big conversation. Obviously there’s lots to look forward to. And we have only touched a little bit of the research paper, the CCS Insight IOT predictions that come out every year. We’ve only touched a small subset and this has already been such a big conversation.

So before we go I just want to throw it back to you guys. Are there any final thoughts or key takeaways that you want to leave our listeners with today? Bola, I’ll start with you.

Bola Rotibi: Well, yes, I think the one thing that I do feel that is going to become even more prominent, if people haven’t already identified it yet, which is—and we have a wonderful prediction about this—which is that proficiency in generative AI is a common feature of job adverts for knowledge workers by 2025. And I think it’s actually going to be probably that you could stretch that out to more than knowledge workers—probably for everyone.

And the reason we say that is because what we’ve seen, this swathe of recent announcements for generative AI, we’ve seen them being embedded into workplace tools such as Microsoft Office, Google Workspace—all of the different types of solutions that are out there. I mean, Martin actually mentioned earlier that pretty much you now get generative AI capability right across the board—almost any tool you open up and there’s a generative AI chat box there.

And I think the thing is we have data already showing that the actual—the more proficient you are, i.e., the better that you are in creating those prompts, which means if you’re trained as well, the better the productivity and the better the quality. And I think people are going to recognize that that is going to be a real factor to having an efficiency factor and an effectiveness factor for the workplace, workflows, and especially if you’re trying to streamline your workflows, make them more effective.

So I think that proficiency side is going to be a real big thing. So my advice is to start looking at how best to build out those prompts, and taking some sort of training support in that. It’ll follow the way of many technologies—you know, the better you are with them, the more effective that you can get them to be.

Martin Garner: And I think there is already a job title called Prompt Engineer, isn’t there? I’ve heard about this.

Bola Rotibi: Exactly, yes.

Martin Garner: And what I think you’re saying, Bola, is that that’s going to evaporate and everybody’s going to be good at it.

Bola Rotibi: Yeah, exactly. I mean, prompt engineering is going to be like, well, that’s it. Just another engineering. But the thing is is that we can joke about it, but I think really in the same way that—and it’s going to be a little bit more than just being good at search terms. I think everybody’s going to have to really sort of learn how best to construct your prompts to get the best insights and the best information out of it.

Christina Cardoza: Yeah, absolutely. It’s almost like the AI developers, you don’t really call them AI developers anymore because everyone’s developing for AI. Everyone needs to know how to develop for AI, so they’re just developers. But, Martin, anything you want to leave us with today?

Martin Garner: No, no, I think that sort of wrapped it up really quite nicely. Thank you, Christina.

Christina Cardoza: Yeah, absolutely. Well, thank you guys again. It’s always a pleasure to have both of you on the podcast, and it has been a great, insightful conversation. I invite all of our listeners to take a look at the CCS Insight 2024 prediction for IoT. We will host it and make sure that we make a link available to our listeners to check that out. And I want to thank you guys for listening to the podcast. Until next time, this has been the IOT chat.

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This transcript was edited by Erin Noble, copy editor.