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Here's how AI and Cognitive Automation are Breaking Barriers in Logistics

By Logistics Tech Outlook | Monday, June 10, 2019

LogisticsFREMONT, CA: Accurate and fast delivery has a special impetus among the businesses owing to the stiff market competition. As a result, enterprises are investing a significant amount of energy and time to achieve new levels of cost, speed, and efficiency in logistics and transportation.

Bettering, in terms of logistics and transportation, is not a new challenge. In the past few years, companies have invested considerable sums in enhancing the supply chain but with mixed results. Many of the leaders recognize that transportation, logistics, and supply chain are amidst profound transformation. Though several technologies will be incorporated for the transformation as mentioned above, the disruptive technologies like artificial intelligence (AI) and machine learning (ML) have the potential to revolutionize the logistics and transportation in the next few years.

Insights into Transportation Data

Currently, the transport managers have limited visibility to the crucial logistics data. Data on demand spikes, on-hand inventory, carrier availability, capacity, locations, and many more are essential to the supply chain dynamics. The inaccessibility to time-sensitive data related to fuel costs, freight rates, port backlogs, fuel costs, and other variables affect the delivery efficiency of an enterprise.

The massive amount of data, even if accessed, is challenging to manage. Hence, it is essential for businesses to increasingly incorporate cognitive technologies like artificial intelligence (AI) in their logistics to compete with market giants like Amazon, which is already using AI across its supply chain.

For the businesses that have built a highly digitized logistics environment, cloud-based cognitive automation will allow them to conduct real-time analysis and suggest modifications.

Here are some of the advantages of cognitive automation:

Transport Capacity

AI unleashes the potential of transportation capacity and helps to manage it with a higher level of efficiency. It covers all the constraints such as volume to deliver, availability of trucks, containers and drivers, and others.

Transport Lead Times

AI enables in better assessment of a situation. It monitors lead times required due to wait-time, volumes, distribution centers, highway congestion, or equipment failure.

Real-Time Decisions

AI offsets the requirement for intuitive or guess-based decisions that often accounted for huge risks. AI’s ability to procure granular details helps managers to decide wisely, with an awareness of what’s at stake.

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