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Marketing Manager
Anastasia Shevchuk


The world of logistics has been completely transformed with the rapid tech evolution of AI that is not a luxury anymore but a necessity for businesses to thrive. Could you have ever imagined driverless cars moving on the roads of your city or robots carrying heavy boxes in warehouses? Sounds like another page of science fiction, right? But it is real life and only a small part of what Artificial intelligence has brought to our world. The time for digitalization and optimization has come.

Let's consider six ways in which Artificial Intelligence is transforming the logistics industry as we know it!


Nowadays, there is a tendency for Artificial Intelligence to transform warehousing operations from information collection to inventory procedures. AI increases productivity, eliminates labor-intensive duties that involve repetitive physical work and manual data and helps to get a bigger profit.

For instance, a warehouse worker may load a robot with heavy packages. Robots move the inventory from one end of the warehouse to the shipping zone and software records the movement of that inventory, keeping all records current. Thereby they improve the efficiency, speed, reliability and accuracy of tasks.

Moreover, there are several types of warehouse automation:

1.Goods-to-Person (GTP)
Goods-to-person fulfillment is one of the most popular methods for increasing efficiency and reducing congestion. This category includes conveyors, carousels and vertical lift systems. When properly applied, GTP systems can significantly speed up warehouse picking.

2.Pick-to-Light and Put-to-Light Systems
These systems use mobile barcode scanning devices synced to digital light displays to direct warehouse pickers where to place or pick up selected items. They can dramatically reduce walking and searching time and human error in high-volume situations.

3.Voice Picking and Tasking
The use of voice-directed warehouse procedures uses speech recognition software and mobile headsets. The system creates optimized pick paths to direct warehouse workers where to pick or put away a product.
warehouse automation


Artificial intelligence in the transportation industry is now being used to build smart roads. Smart roads technology combines sensors and solar panels with software infrastructure like AI and Big Data to make driving efficient, safer and more sustainable.

Smart road technologies are embedded in roads and can improve visibility, generate energy, communicate with autonomous and connected vehicles and monitor road conditions.

Here are a few examples:

1.Traffic detection
Data that helps drivers plan their routes. AI-integrated sensors embedded in highways monitor traffic flow, warn drivers of traffic jams, and automatically alert about accidents.

2.Traffic management networks
Networks of AI-integrated sensors detect weather conditions, provide warning signs for hazardous conditions, and send automated traffic signals that control traffic. Traffic management networks improve safety and energy efficiency.

3.Traffic lights optimization
Systems that use data from smart vehicles to optimize traffic lights and update commuters on jams or bottlenecks.

Most transport-related smart tech focus on individual vehicles, although there have been major advances in technological solutions for smart infrastructure at scale. Worldwide experiments in Vehicle to Infrastructure, Vehicle to Vehicle and Vehicle to Pedestrian technologies will make urban transport smarter in the future.


Artificial intelligence is a great solution for reducing costs in the transportation industry. Self-driving vehicles bring great changes to the supply chain and significant cost reduction in logistics. AI technology is going to automate not only cars but also trucks, vans, buses to transport goods faster and efficiently. However, driverless trucks might not be coming out soon but semi-autonomous vehicles are on the rise of their popularity.

Today, logistics companies are applying autonomous driving systems. Trucks travel in a direction, following a lead truck with a human driver. They synchronize braking, accelerating, and steering, which enables them to enhance freight capacity and minimize costs.
However, in many countries, the government considers that the driver has to be in the vehicle to fully control the situation on the road and analyze possible risks. Of course, this statement may be changed in the future.

The great example of an autonomous vehicle is Rolls-Royce. The enterprise cooperates with Intel to develop autonomous ships. This tool has several interesting features. For example, it can recognize and define objects in the water, monitor engine condition, and choose the optimal routes. As a result, the delivery speed becomes higher.


Due to the integration of AI Chatbots, businesses can reduce consumer response time and also decrease the need for customer service executives.
Today, chatbots can offer in-depth, personalized assistance around the clock.

Furthermore, chatbots can direct clients to knowledge base articles or transfer them directly to a live agent that specializes in handling their issue. In addition to being polite and practical, chatbots are also beneficial when dealing with foreign customers who do not speak the languages supported by the business locally. So, Artificial Intelligence technology ensures efficient and fast customer service.


The term 'Big Data' was already a buzzword a few years back but the number of ways in which businesses can benefit is only getting bigger. Big Data with Artificial Intelligence in the logistics industry helps predict shipping volumes and plan for the future taking into account such important factors as weather, political landscape, etc.

Moreover, Artificial Intelligence helps to gather data from all touchpoints, analyze it and come up with patterns that can help make significant changes in supply chain management.

Logistics companies receive the possibility to make clear predictions and optimize their performance using the power of Big Data. The high volume of structured and unstructured data is generated by supply chains on a daily basis. Big Data enables logistics companies not only to exploit this information but also to adopt advanced predictive analytics and increased automation which drives strategic decisions.

Big data is revolutionizing many fields of business, and logistics is one of them. Big data in the logistics industry can be used to optimize routing, streamline factory functions, and give transparency to the entire supply chain.

Furthermore, Big Data can help to ship sensitive goods of higher quality. Keeping perishables fresh has been a constant challenge for logistics companies. However, Big data and the Internet of Things could give delivery drivers and managers a much better idea of how they can prevent costs due to perished goods.

For example, let's imagine a truck transporting a shipment of ice cream and desserts. You could install a temperature sensor inside the truck to monitor the state of the goods inside, and give this data along with traffic and road work data to a central routing computer.

This computer could then alert the driver if the originally chosen route would result in the ice cream melting, and suggest alternative routes instead.


Robotic automation in logistics is the application of robots to one or more of these processes. Robots automate the process of picking, packing, storing and moving goods as they make their way through the supply chain. They operate in prescribed pathways, moving products for shipping and storage around the clock.

Robotic process automation brings clear benefits to the logistics industry:

1.Improved performance
By using robotic technologies, warehouses can improve their productivity without affecting the quality. Robots increase accuracy and accelerate repetitive processes when used side-by-side with human employees.

2.Improved working conditions
Warehouse workers can rely on machines to carry heavy loads. This advantage reduces the risk of serious injuries that can affect the worker's health and safety.

3.Cutting staff costs
Using robots in a warehouse optimizes the need in the human workforce. It also significantly reduces the number of paid sick leaves, for example, or work-related accidents that represent significant costs for employers.

So, robotic process automation offers more flexibility because it can run continuously and only stop for maintenance needs.


Although the concept of Artificial Intelligence is appealing to shippers, carriers and others, there are several challenges with AI in Logistics that need to be carefully considered and taken into account.

The cost of training

Like any other new technology solution, training is another reality. This will cost companies money, time, and an initial reduction in business efficiency. Logistics partners will need to work with the AI provider to create a training solution that is impactful – yet affordable during the integration phase.

Fewer Human Jobs

With more automation comes the inevitable reality of reducing the workforce. Unfortunately, victims of this improved efficiency are the people who currently occupy these positions. When jobs are eliminated due to the integration of AI solutions to the logistics industry, the company needs to either find new positions for their employees to take on or dismiss them together.

The Operational Costs of AI

An AI-operated machine has an exceptional network of individual processors and other components. Each part requires replacement from time to time to maintain operational integrity. These parts can be rather expensive. Besides, AI machines require constant updates, which also includes replacing internal batteries which also cost a lot of money.

If you want to learn more about digitalization in logistics, have a look at our article "The Changing Face of Logistics: What Changes to Expect in the Next Decade?"


The future of Artificial Intelligence in logistics looks extremely promising. Even now the role of AI is significant as it offers a variety of advanced solutions. Companies of all sizes are integrating this powerful technology into their daily operations. As a result, automation of routine tasks in logistics speeds up processes, reduces the probability of human-error mistakes and increases customer satisfaction.