These factors could inhibit the growth of IoT and AI

With every new technology comes a hype cycle followed by a wave of disappointment, says Schneider Electric Chief Digital Officer Herve Coureil.

These factors could inhibit the growth of IoT and AI

Schneider Electric Chief Digital Officer Herve Coureil discusses the cyclical nature of new technology with TechRepublic's Dan Patterson. The following is an edited transcript of the interview.

Dan Patterson: IoT: that's kind of the magic word here. If we look at reports from places like Forrester and other outlets, we see this tremendous growth in the future. Let's say, over the next three to five years, we'll see 20-to 40- or 50-billion... we'll see lots and lots of IoT devices in the market place, maybe. What factors could inhibit the growth of IoT, and, of course, related to that would be, inhibit the growth of artificial intelligence systems?

Herve Coureil: So, the first thing that I see every time you have a technology that's really hyped, you have possibly a wave of disappointment. People saying, "Where's my business value? I mean, I'm thinking about AI or tons of algorithm, but where is really the return on investment for me?"

So I think there's really your first thing, which is making sure that you are looking at solving specific problems. Every time you have a new technology, you have a lot of people who want to experiment in all directions. And then, of course, that can lead to disappointment. So I would say that's probably the first thing.

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Then of course, there's all the... what you read in the paper, in term of data, data residency constraints, regulation, etc. Privacy maybe more in B2C, but data residency constraints in many, many areas that may make a more complicated idea of learning about it on the cloud and of training your model on the cloud, and having inference on the edge.

So those are definitely two things we're looking at. We really think... we see in our early customers with eco-structure, which is really the IoT architecture that we are deploying now, we see a lot of traction. But indeed, we're also very, very careful at being very attentive to what our customer wants, and being always obsessed by starting with the customer. Start by your customer's problem, don't try to solve thing to... horizontally. Try to be very, very specific.

On the other stuff that we're super careful is this notion of edge and cloud, right? Because we want to be able to operate very close to that process.

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