This article originally appeared in the October 24 magazine issue of IoT Insider.
By Caitlin Gittins, Editor of IoT Insider
The recent publication of Kigen’s guide for businesses on ‘Cyber smarts for AI’ recognises that AI has become an indispensable technology and a tool for good at the same time it reports that only 4% of businesses say their data is AI-ready. This curious intersection between the explosion of AI and the readiness of businesses regarding their data was something IoT Insider spoke to Vincent Korstanje, CEO of Kigen about, to get his perspective.
Arm, the technology startup, was acquired by SoftBank in 2016. In 2020 Kigen was spun out of Arm and, as Korstanje elaborated, is focusing on facilitating security through SIM and eSIM technology which also provides service providers with connectivity.
“The main vision we had in 2016 was looking at how we secure devices, and we looked at how security starts as the foundation, or what is also called the root key,” explained Korstanje. “We then looked at how we ensure that root key is well protected and how to create products around that.”
Growth of eSIM technology
Kigen’s particular expertise is in SIM and eSIM technology – for good reason. “We realised that the SIM is an interesting asset,” said Korstanje. “We thought about how we could make it easier to use and get more people to adopt it, but also use the technology to secure devices. That’s something we’ve been prototyping, selling, and now leading the market in.”
eSIM technology is markedly different from conventional SIM technology because rather than being a physical card, it’s embedded within a device. Thanks to this functionality, a user can add multiple carrier profiles and switch between them. For the IoT, this is especially useful for service providers operating in different countries.
According to Juniper Research, eSIM and iSIM capable devices are expected to register at 680% CAGR in the next four years – reflecting a vibrant market.
“One aspect of eSIM technology is that it changes who makes the decision on the connectivity,” Korstanje said. “Previously if you were a business who is integrating connectivity into a product, you would have gone to an MNO and got a physical SIM. eSIMs eliminate this bottleneck, empowering IoT business users by placing the decision in their hands.”
In addition to allowing original equipment manufacturers (OEMs) some flexibility about how they want to deploy their connectivity, the versatility of eSIM technology is benefiting a variety of use cases.
In one example, Kigen worked closely with smart meter OEMs to create a secure, yet unbound eSIM – meaning the eSIM is not bound to a network provider – with a tool at the end to allow the OEMs to personalise the eSIM before they ship it to a customer. “Why? They can put that profile onto the device and when the device is shipped to the customer, it will automatically connect with the right connectivity, which is especially important for smart meters, for that country or region.”
Making data ‘AI-ready’
For their cyber smarts report, Kigen spoke to several stakeholders and companies looking at AI. “One thing we noticed was that businesses are thinking about AI in two ways: one, using Gen AI as a conversational, contextual search tool. The other is game changing AI that’s tuned to businesses’ products and processes that enhance value proposition or the business model,” said Korstanje.
“They used to call data the ‘new oil’ and this becomes ever more vital as the engine that can drive game-changing AI for businesses,” he continued. “But you need to understand quite a few things before that data becomes useful. One is, is the data valid? Is the data source secure? Has it been tampered with? Has it been corrupted? If you can’t test that and don’t know the source of the data, it becomes very quickly valueless.”
The figure provided by the report that was especially eye-opening was that only 4% of businesses feel their data is AI-ready; meanwhile 93% recognise AI as a key technology for growth and innovation in manufacturing. This paradox poses the question: why?
“I think everybody can see the immense potential of AI and Generative AI is the tip of the iceberg,” said Korstanje. “At the same time, I think everybody is struggling to figure out how to deploy AI.” There are many considerations about the kind of data that is fed into AI training models, such as the security of the data; the readiness of the data; the cost of doing so, and so on.
Korstanje said he thought GenAI was lighting a “fire” under the industry. “We were talking about smartphones for 10 years,” he explained. “Now they’re very normal. I think Apple broke open this market and the access to the app services economy and I think that is what Gen AI is doing for AI.
“And the development of AI is rapidly evolving so that it will be more in line for use with enterprise data. This is why we have openly shared the insights we have about how businesses can get started, with the right ingredients.”
On his key recommendations for thinking about AI and device security, Korstanje said: “The key AI. “One thing we noticed was that businesses are thinking about AI in two ways: one, using Gen AI as a conversational, contextual search tool. The other is game changing AI that’s tuned to businesses’ products and processes that enhance value proposition or the business model,” said Korstanje.
“They used to call data the ‘new oil’ and this becomes ever more vital as the engine that can drive game-changing AI for businesses,” he continued. “But you need to understand quite a few things before that data becomes useful. One is, is the data valid? Is the data source secure? Has it been tampered with? Has it been corrupted? If you can’t test that and don’t know the source of the data, it becomes very quickly valueless.”
The figure provided by the report that was especially eye-opening was that only 4% of businesses feel their data is AI-ready; meanwhile 93% recognise AI as a key technology for growth and innovation in manufacturing. This paradox poses the question: why?
“I think everybody can see the immense potential of AI and Generative AI is the tip of the iceberg,” said Korstanje. “At the same time, I think everybody is struggling to figure out how to deploy AI.” There are many considerations about the kind of data that is fed into AI training models, such as the security of the data; the readiness of the data; the cost of doing so, and so on.
Korstanje said he thought GenAI was lighting a “fire” under the industry. “We were talking about smartphones for 10 years,” he explained. “Now they’re very normal. I think Apple broke open this market and the access to the app services economy and I think that is what Gen AI is doing for AI.
“And the development of AI is rapidly evolving so that it will be more in line for use with enterprise data. This is why we have openly shared the insights we have about how businesses can get started, with the right ingredients.”
On his key recommendations for thinking about AI and device security, Korstanje said: “The key thing with security is setting your business data in a way that it is easy for game-changing AI. To start, look at what you can directly control – for example, device security.
“Inexpensive and already available secure elements in your devices can keep your data secure and allow your to innovate. This opens the door to your new foundations for ethical and explainable AI. You need to look at a vendor that makes security ease to use in this way.”
