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It’s that time again: prediction season. Here at insight.tech we make an annual tradition of highlighting the top IoT predictions from CCS Insight, this year including plenty of edge and AI. We’ll break it all down with the CCS Insight Head of IoT Research, Martin Garner, and Bola Rotibi, its Chief of Enterprise Research (Video 1). And once again we’re hosting the complete research paper for our readers: Edge Computing and IoT Predictions for 2024 and Beyond. Be sure to check it out.

It’s clear that there are lots of benefits and opportunities associated with AI; it has the ability to transform industries and our lives. But it also comes with a certain level of discomfort on the part of the public—how is their data going to be used, how secure is it, and who is doing what to safeguard it in this Wild West of innovation and expansion? And nervousness, too, on the part of businesses trying to future-proof their investments. But one thing is sure: No one camp is responsible for getting the AI situation right. It’s going to be a collaborative effort from everyone building and using these solutions.

How is the push toward edge and AI impacting IoT predictions for 2024?

Martin Garner: Obviously, 2023 was a huge year for both edge and AI. ChatGPT clearly had a massive impact and has really opened the world’s eyes to what AI can do—and to quite a few things that it can’t do yet. In our predictions for last year, we had lots about edge and some about AI. We really dialed up the AI predictions this year. And it’s not just generative AI, like ChatGPT; it’s not just what individuals can do with AI.

One prediction that’s an example of this is that by 2028, a major healthcare provider will offer its customers a digital twin service that monitors their health proactively. Now, today there is a lot of data about you scattered around—online health records, fitness bands, smart watches, data that’s on your phone, and so on. But it’s all a bit messy and not joined up at all. So we think that healthcare providers will start to combine these sources. They’ll use AI and basically do what the industrial guys are already doing—predictive maintenance—but on people. And of course the aim is early intervention, which often means smaller intervention, and usually cheaper intervention, too. So that’s an example of how we think AI will start to develop from here.

Will there be a continued move to the cloud because of these advancements?

Martin Garner: I think that the cloud-versus-edge debate is going to remain live for a good few years. I think in many countries there are worries about the economy, and we’re not quite out of all the pandemic effects yet, either. So one prediction is that recession fears push workloads from the cloud to on-premises through 2024. The best candidates for doing that are companies that are using hybrid cloud already. And it may be that a hardware refresh is a good opportunity for some companies to repatriate some of their workloads to on-premises—and take some cost savings while they’re doing it. That’s the short term.

Longer term, we think there are several areas where there are pendulum swings—like insourcing versus outsourcing—and edge to cloud could be one of those. But one area where we have another prediction is that by the end of 2028, there will be a repricing of cloud providers’ edge-computing services.

Now, what does that mean really? The major cloud providers 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 the on-ramp for the public cloud, and they’re priced that way. But the forecasts for edge computing show it growing bigger than the public cloud over five years—possibly a lot bigger. And if that happens, then we’d be in a position where the big part is subsidized by the smaller part, which makes no sense at all.

So we really expect the prices of edge-cloud services to move upward over three to five years, and that could be a significant price rise. Many industrial companies might want to consider their own edge computing to put themselves in a better position, one where they have more options. It’s edge as a hedge, if you like.

What can we expect in terms of AI solutions development over the next year?

Bola Rotibi: 2023 was a year of launches, especially from IT solution providers, with a wealth of new tools—obviously ChatGPT spawned massive interest. But I would say that the development of AI has actually been happening for quite some time, with machine learning and other sorts of models and algorithms that people have been using behind the scenes. Searching through pictures on your mobile phone—those are AI solutions, AI models.

What we are seeing is the power of generative AI, especially as a productivity solution. That ability of generative AI to simplify complex queries and bring back concise information that is also relevant information. So everyone’s jumping on that. Over the past year we’ve seen pretty much every provider—Intel among them—bring out generative AI capabilities, as well as beefing up their AI solutions. We’ve seen Microsoft launch with its AI-powered assistance Copilot and AWS with Amazon Q.

So we have a prediction that AI investment and development will accelerate in 2024—despite some calls for caution. Because quite a few of the main protagonists over recent months have said, “Hold on just a minute. We need to kind of slow this down.” People are also a bit worried about security; they’re worried about whether the regulations are out there and whether they are effective enough. But at the same time, I think there’s a real thirst to get AI and to develop it, because people have been just blown away by the new experiences and the engagement levels.

What is the reality of generative AI over the next year?

Bola Rotibi: 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. And another prediction—despite all of the froth and the fact that we’ll see lots of new tools—is that we do think there will be some level of slowdown in 2024. That’s partly because people will get to grips with the reality of the costs and some of the risks and complexities that have started to be exposed this year.

The excitement of 2023 will start tempering down into more of a level-headed, nuanced approach, and people will start to play with generative AI properly, 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.

“2023 was a huge year for both edge and #AI. #ChatGPT clearly had a massive impact and has really opened the world’s eyes to what AI can do—and to quite a few things that it can’t do yet”. – Martin Garner, @CCSInsight via @insightdottech

As investment accelerates, do you anticipate an increase in ethical-AI initiatives?

Martin Garner: The short answer is: Yes, there’s going to be a lot more of that. AI has the potential for many good uses in society, but used wrongly, it has the potential to do a huge amount of damage. It’s a bit like medicine, with regulated and unregulated drugs. But the big difference 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.

At the moment we have the opposite situation, where as soon as something new is developed, the AI-leading companies open source it and push it out into the world as fast as possible. That obviously puts a huge imperative on suppliers and developers to take an ethical stance in how they use it, as well as on companies that are using AI as customers. There’s lots to get right there.

We do have a prediction that AI-oversight committees will become commonplace in large organizations in 2024—committees of ethics experts, AI experts, legal advisors, data scientists, HR teams, representatives from the different business units—to review use of AI across the company. Their job will be to bridge the gap between the tech teams—who are all engineers and not typically ethicists—and the organization and its goals.

That’s going to require quite a significant amount of overhead for a lot of companies, and lots of training to come up to speed and to stay on top of it. All that because the AI industry is largely not doing a good job of self-regulation.

What does the EU’s AI Act mean for development of AI solutions?

Bola Rotibi: The EU has been first out the door with this AI Act, which will be like GDPR. And we’ve already seen the ratification in the EU of the Digital Markets Act. But the EU is not the only one; there’s the US, the UK, China, and other regions as well. So I do think that the regulators are coming together, and we’re going to start seeing some level of improvement toward the end of 2024. But I think there will be a sort of bedding-in process, as people try to get used to it and understand what it all means—teething problems. But I think it will become something for people to rally around.

The other thing that’s actually happening is regulation at the industry level. Recently, 50 organizations—including IBM, Meta, and Intel—have launched the AI Alliance. It’s aimed at bringing the industry together to work collectively on standardizing; to bring working groups together; to come up with ideas for strategies and approaches to handling certain AI challenges and opportunities; and to be a hub for interactions between end users.

What are some considerations for developers building AI solutions?

Bola Rotibi: It isn’t just on the developers. In the same way that security is the responsibility of everyone in the workflow, so is an ethical approach to AI. Of course, developers could ask themselves, “Well, just because I can do it, should I do it?” But, at the same time, if you want a level of consistency, you have to provide guidelines and principles that are distributed and circulated right across the organization. It needs to come from the ground up, and it needs to go from the top down.

So I see that there will be a layered approach going forward. That may mean the oversight committee Martin mentioned thinks about where the organization is from an ethical standpoint and starts building policies. And then those policies will be put into the tools to act as guardrails. But there’s also going to be guidance and training of developers in terms of them taking a responsible-AI approach in the development process.

Lots of organizations have been thinking about impact, about sustainability, and all those kinds of things, so there is a wealth of ideas and initiatives already for making people think at multiple levels, not just about responsible AI but about doing the right thing in general.

Where does 5G fit into this? And when is it time to start looking at 6G?

Martin Garner: One of the things 5G will do is enable a lot more use of AI, thanks to the very high capacity, time-sensitive networking location services it will bring in. We’ll see a lot more AI in use around domains like autonomous vehicles, and the 5G that we have now—as well as the newer bits of 5G that are nearly here—is one of the key enablers of that.

But I think the other interesting bit is the impact of AI on 5G. The 5G networks—they’re complicated things; the whole optimization and management is a big deal. And we have a prediction around that, which is that AI will enable 5G networks to move beyond five-nines availability. That would come through analyzing traffic patterns and ensuring that the network is set up best to handle that particular type of traffic, to identify problems, to do predictive maintenance, and to configure the network so it has graceful degradation or can even become self-healing if things go wrong.

It is a tiny bit early for 6G, but work is going on, of course. Over the next five years or so, we’re going to be building 6G networks, and we think 2030 is going to be a bit of a headline year for it. So we do have a few 6G predictions. One is that by 2030 the first 6G-powered massive twin city will be announced. We think that cities will be a great showcase for 6G, and massive twinning will be one of the best use cases because of all the layers of a city that could potentially be included in the model. 6G would be needed just for the sheer volume and speed of the real-time data that runs through a city. We think 2030 will be a big headline year for that.

Related Content

To learn more about edge AI trend predictions, listen to Top IoT and Edge AI Predictions for 2024: With CCS Insight and read the report Edge Computing and IoT Predictions for 2024 and Beyond. For the latest innovations from CCS Insight, follow them on Twitter at @ccsinsight and on LinkedIn.
 

This article was edited by Erin Noble, copy editor.