AI Best Practices in the Real World – Dr. Merlin Stone discusses Artificial Intelligence in the Near Future, Part II

We continue our conversation with Dr. Merlin Stone about the proliferation of artificial intelligence in the real world. Does AI’s use of algorithms always leads to smarter decisions? The answer may surprise you!

Artificial Intelligence helping human intelligence; thinking like your customers, customer mindset

Dr. Stone:  None. So what we’d dream up as the ideal system would be quite something: a unified database, or the equivalent in whatever industry, planning it as you would for a physical facility. But there must be a similar situation that could be triggered by industry.

Peter: Or even sensors on the trucks so that you can actually see how a customer is using the truck and possibly see that it isn’t very efficient the way they’re doing it; we can replace that with three machines at a fraction of the cost and improve your productivity by x percent.

Dr. Stone:  Yes, we are seeing this in some industries.

When I was at IBM we went to visit Caterpillar in 2003 – I said you guys know more about the mining of ore from the ground than anybody because you’re selling all the diggers and trucks involved. Surely you should be able to sell excavation as a service. Why are you selling trucks? Ooh, we couldn’t do that — we can sell financial services, but this is a bridge too far. But it’s happening in other industries. So, one of the triggers to that is, when you move from selling the asset to selling the service, you must then have the data so you can now see these trucks in operation.

So, for example, when I was in Denmark for IBM, you got food processing companies whose equipment is full of sensors. The client needs it for quality control and you can use it to identify how the clients are using it. Or Vestas, the wind turbine company — their equipment is full of sensors. You’ll tell your clients whether the machines are working efficiently, and the sensors are working for two purposes. One is for you to service a machine; the other is for them to decide whether it’s worthwhile or not with wind directional data and so on, but you have the database of all of it. So you can advise them what to do, and you can even see a weather front approaching from another country and pre-set the equipment.

Peter: That’s all very well for manufactured products, but what about services?

Dr. Stone:  Most business we sell in the UK is services-related: consultancy and a whole range of different service products — all the work going on in the Middle East, that’s very different; it’s very much human-based, and I can’t see AI working as a delivery mechanism there. There’s still so much that is hand-crafted; writing proposals — you know the story. You would have thought that AI would be able to turn to anything like proposals because there’s nothing new under the sun.

Peter: Just plug it into the web and find all the research!

Dr. Stone:  Absolutely.

Peter: We can dream on about that, and it will become interesting to see how you then actually differentiate between different bids in the future when we’re all delivering the perfect solutions! We’ll need AI Max to then analyze the massively fine detail and show the results in advance of whatever has been proposed … WOW!

Let’s stop here before our heads blow up, and come back to earth in Part III!

Author: Peter Gillett

Peter Gillett is CEO of Zuant where he’s responsible for driving product development and client roll-outs of the company’s award-winning Mobile Lead Capture app across US corporations. An entrepreneur and innovator, Peter created the world’s first web-based CRM system funded by Lucent Technologies in the 1990s. CRM, lead generation and follow-up are still the focus for Zuant and its network of NACCENT call centers around the globe. Contact Peter via email at

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