Capgemini rep says new trends include last-mile drones, route optimization, and robots.
TechRepublic’s Karen Roby spoke with Vikas Shetty, client partner at Capgemini, an IT consulting business, about trucking logistics and the use of artificial intelligence (AI). The following is an edited transcript of their conversation.
Vikas Shetty: If I talk about all logistics overall, it has been used right from the planning phase to the last-mile delivery. Within this entire section, just to give you an example, in planning space for demand forecasting or to find a particular trend, like around weather and all business-to-business runs. All those trends for that, AI has been used extensively. Some of the new trends which we are seeing, if I have to say specific to trucking and logistics, it’s like the last-mile delivery using AI drones, which is still in a very early stage but there will be adoption in near future. There will be a much bigger adoption for that. The other part is warehouse automation. A lot of big players in the market have already started using robots as part of the AI thing.
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Now, coming back, shifting gears to adoption rates specific to trucking and logistics, there has been a slow adoption pre-COVID, I would say, and the main reason for that is the value or the ROI was not justifiable for that industry. In addition to that, the skill shortage and all. In combination, they had seen that the adoption for AI was not to a level it could be adopted. But things have drastically changed post-COVID. COVID was a lot of disruption. If I have to give you an example of a pre-COVID thing, the data was very much static, I would say. When I say static, it means based on my tribal knowledge, there was some prediction I can make. But post-COVID, there was a drastic change, because there was a behavior change in shipper and consignee. There was a focus more on the Asian shelf goods. The pickup and shipment delivery sites were changing due to the pandemic based on the rate of infection in certain areas.
This created a lot of disruption within the industry, and the industry was not ready for picking this disruption. But what we have seen is there was a quick transfer or transformation to digital transactions and all. That’s less shipment and all. And that has now, we can see that there will be a faster adoption of AI in trucking post-COVID, actually, or I can say when we are near to the new normal.
Karen Roby: Talk a little bit about, specifically within trucking. Is AI used more with planning routes, or how will that really help move the industry forward?
Vikas Shetty: That’s a very good question. Karen, one thing which the industry realized very quickly was there was a fluctuation in demand and the resource shortage. That created a need for operational efficiency. One of the area which is heavy manual today is the freight billing area. Though we are using OCR—optical character recognition tools—but OCR coupled with AI, the benefit has been doubled. Or even if you take a standalone AI, natural language processing, all those concepts can be used. It has seen that there is a huge productivity benefit, and that’s where one of the adoption we will very soon see in near future, more and more tracking companies adopting that AI for that space.
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Then the second one which you just mentioned is route optimization. As I was mentioning, that the disruption that was caused due to pandemic, the shipper and the consignee delivery behaviors changed, which created an efficient route requirement for much flexibility in creating an efficient route and all, which in turn gives a benefit in terms of reduction in shipping costs, a better customer experience. So route optimization is one key area. One more important thing about route optimization is that there are a lot of data points which come in the system. Today, not entire data is used to build those intelligence, and that’s where in terms of route optimization and all, which is also one of the critical pieces within the entire ecosystem of this trucking and logistics industry, that’s where AI will come into the picture and we will slowly see a lot of adoption of AI getting accelerated, especially in trucking and logistics business in these key areas.
In addition to this, there are other areas also. Just to give you an example, one of the revenue leakage areas within trucking and logistics areas are the damage that has been caused. Sometimes, it becomes difficult to gauge those damages and all, but using AI image capabilities and those processing, there can be easily detection done on the level of damage and all without too much of manual back-and-forth and all that stuff. That’s one adoption area.
The other thing is the sales team. The sales team needs to be provided with the right tools for in this competitive market with, as I said, correct the focus change all of a sudden from non-essential goods to essential goods. Sales teams had to focus more on customers providing these essential goods and all. With help of AI, using the historic data, that intelligence can be provided to the sales team so they can focus more on the right prospects. Those are a few areas where we see there will be adoption. These are just a few areas, but there are more areas, as I said at the start of my discussion, like the warehouse automation and last-mile delivery using AI drones. Those are some future technologies which will be used in combination with AI.
Karen Roby: I know trucking has been slow to adopt AI. On the flip side of that, is there an industry you can pinpoint that has been much quicker to adopt AI and is seeing results because of that?
Vikas Shetty: In the entire supply chain model, trucking is coming to the tail end. But the initial phase, like the warehouse management or if we talk about the initial planning, those are some players who have initially adopted it very well. Also, outside of this SCM, in all financial sectors and all those areas have also adopted AI much faster than any other areas.
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