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5 AI Solutions for the Logistics Sector

AI solutions

In an era of infinite possibilities, new innovations are reshaping economic, social, and cultural environments.

Of all emerging technologies, perhaps none is as disruptive as artificial intelligence.

It’s still in its infancy, yet its widespread applications are changing many industries.  

Logistics is no exception. 

The sector has always been plagued with inefficiencies.

From supply chains to transportation, AI is changing the way consumer products move around the world.

Here, you can explore current and future possibilities of artificial intelligence in the logistics sector.

Rising AI Solutions in Logistics 

Often, manufacturers experience bottlenecks in production or delays in transportation.

These result in extended lead times.

Due to these inefficiencies, manufacturers end up with dissatisfied customers. 

Defects in the production process are more devastating. Aside from material loss, companies’ productivity suffers.

Mistakes in inventory forecasting might not be as distressing, but it’s still a problem that needs fixing. 

Artificial intelligence is an ideal solution for all of these inefficiencies. Even senior executives from transportation sectors believe so.

About 65% of 433 senior execs are convinced that AI is going to transform logistics, supply chain, and transportation process.

1. Intelligent, Automated Warehouses

Amazon and other large retailers require fast and complex technology for their everyday operations. As a solution, many are adopting automated warehouses where artificial intelligence and robotics are slowly substituting human tasks.
 

Take Amazon warehouses for example. On the warehouse floors, they’ve laid out a series of computerized barcode stickers which enable robots to move around the area.

Each unit is equipped with a sensor that prevents it from colliding with other robots while carrying goods from point A to point B.

Warehouse robots can move an entire pod—stacked with consumer goods—to the human operator, who is tasked to pick orders.  

The benefit to this is the faster processing of consumer goods, which specifically:     

  • Simplifies the order fulfillment
  • Minimizes errors around the picking of orders
  • Accelerates picking and packing of orders

Amazon, after a warehouse test run, has set up machines that can work on 700 orders per hour. This is five times more than the speed of human workers.

Another company that’s taking advantage of artificial intelligence is England-based online grocer Ocado.

Their robots can fulfill around 65,000 orders within a week, which is about 3.5 million grocery products.

Aside from this, Ocado’s robots can also sort the inventory.

2. Smart Roads

AI is now being used to build smart roads.
 

 Colorado, for example, intends to equip highways with sensors and monitors to keep track of passing cars and road damage. Like any smart device, these roads can connect to the internet. 

Smart roads can also increase driver and passenger safety. Whether it’s an accident or a traffic jam, motorists can receive phone notifications, allowing them to choose the safer and most efficient route. 

Also, road monitoring technologies will be valuable for businesses who need to get consumer goods from point A to point B efficiently.

This technology is beneficial to everyday commuters and companies alike:

  • Gives insights on situations that can delay orders
  • Predicts traffic jams before they happen
  • Helps retailers avoid congested areas 
  • Advises on alternative routes for timely order delivery

Smart roads can reduce lapses in order delivery. Delays in transportation have a significant impact on businesses, so much so that a 10-30% effectiveness in commodity shipping can save 100-300 billion in the European logistics industry. 

3. Predictive Capacity Planning

One of the most underutilized assets in the logistics sector is the massive volumes of data that supply chains generate on a daily basis. A human workforce alone wouldn’t be able to sift through all that information and make sense of it. But AI and machine learning can.
 
Predicting fluctuations

Here are some of the changes that AI has brought to logistics management:

Predicting changes in demand used to be so challenging for companies because of a number of factors, including sales numbers, weather conditions, and consumer attributes.

Now, companies can accurately forecast fluctuations by looking into all of the factors that influence demand.

Then, they can use that information to make the necessary adjustments to their operations in real-time.