Artificial Intelligence Transforming Logistics

Artificial Intelligence transforming Logistics

Logistics is stepping to a new era with Artificial Intelligence. It is also promoting itself as a game changer in Logistics just like in many other industries.

Forbes Insights research: Around 65 % of senior transportation, executives accept that Logistics and related industries are amid of profound era of transformation.

Artificial Intelligence Next Big Thing In Logistics
Artificial Intelligence Next Big Thing In Logistics

In order to that organization is looking for the technologies which suit for today. So that we are going to develop that technology. But all these development couldn’t carry such disruption and innovation than machine learning and Artificial Intelligence could.

Actually, we need the technologies which can prove a tangible difference to our communities, customers, and people and AI brags to do same.

Organisation and Artificial Intelligence
Organisation and Artificial Intelligence

Organization and Artificial Intelligence:

Both big, as well as small organizations, are digging into risks as well as opportunities. This seems one of the reasons why dependency on AI has got its craze among most business communities in the past few years.

However leading organizations have already stepped forward to harnessing the machine learning and Artificial Intelligence and tune well and inform the fundamental strategies which include decision making on the key issues on real-time.

So that you can take a decision on costs, inventories, vehicles, carriers, availabilities, and personnel without wasting time.

Making Decision with Artificial Intelligence
Making Decision with Artificial Intelligence

Making Decision with Artificial Intelligence:

Rail, truck, and sea cargo use tracking system using telematics which dominated tracking area for 20 years nearly.

Even though the industry has put its decision-making theory to optimize transit times and costs which are incorporating to high-value cargoes and vehicles.

However, the present scenario is quite different with efficient algorithms and powerful computing power to evaluate and sort the understanding and taking actions.

Although logistics has been data-focused yet we have added computing power such as data mining, machine learning, Artificial Intelligence, and IoT/ telematics data collection.

And using these technologies, compel us to take not only better decisions but also real-time decisions on the basis of resource and strategic planning.

DHL IBM Artificial Intelligence
DHL IBM Artificial Intelligence

DHL and IBM:

While Artificial Intelligence is waving across various industries, so the logistics world is going to benefit more from it.

As per the report of DHL and IBM: The nature of logistics is network-based which provides a natural framework for scaling as well as implementing Artificial Intelligence.

So, those companies who have already experimented AI implementation are ripping small wins and now heading to bigger ones.

These small wins are tested theories and established practices. Everybody is aware of AI now so don’t lag behind in the race to use AI otherwise you may lose from your potential competitors.


Practicle Application of Artificial Intelligence
Practicle Application of Artificial Intelligence

Practical Application of Artificial Intelligence:

Machine Learning and Artificial Intelligence assure business to focus on IoT and multiple data feeds while accessing greater responsiveness and optimization across logistics, transportation, and supply chain.

Stratagic Optimization
Stratagic Optimization

Strategic Optimization:

Business persons in Logistics are seeking sources to gather information to make the best decision developments.  These decisions are not limited to inventories but include the needs of transportation assets to adjoin all the points from the customer’s request to the delivery point.

So, these points will ask things about the location of drivers, vehicles, and customers. Now the question arises whether we have made our commitments or not.

All these data are going to feed to machine learning and Artificial Intelligence platforms which can crunch the data before presenting a range of optimized scenarios.

With these AI sophisticated tools, we are on the process of continuous learning and improvement. Because of it, professionals will become better day by day and decisions will be better minute by minute.

Artificial Intelligence and Real Time Decision
Artificial Intelligence and Real Time Decision

Real-Time decision:

No doubt Logistics teams are more into a wide range of complex tasks but these are quite repeated too. So, these tasks demand a good amount of data for making the best decisions around.

xample: Optimal carrier selection which reflects adjoining through a number of candidates, paths, and schedules.

However, practically workers take 10 minutes or more time to collect the required information. But Artificial Intelligence and supply chain professionals will automate the analysis and within a few seconds, they can narrow it to two or three sections. Eventually, the deal will be closed by human intuition.

Artificial Intelligence and analysis
Artificial Intelligence and analysis

Analysis:

For the supply chain, logistics, and transportation planning, it is vital to know when the customer is going to order. Of course, it is important for the sales team no doubt. Example: As we look on transportation needs, IoT or telematics are helpful to determine the time when a vehicle will go under preventative maintenance so that they can reduce the failure risk to meet customer expectations and needs as well as avoiding breakdowns.

Physical Demands and Artificial Intelligence
Physical Demands and Artificial Intelligence

Physical Demands:

Though the machine has not dominated such a way that the driving delivery vehicles need a robot to get things done just like some science fiction movies. However, AI has proved itself to meet various needed physical requirements.

 For an example:

  • ZenRobotics uses Artificial Intelligence in its algorithm for conveyor belts scanning which is used for mixed recyclable items where materials and labels are analyzed. First Tools pick similar items then sort them efficiently.
  • Intelligence robotic sorting is a process to ensure that right shipments are placing at the right place on the right time by scanning and sorting the packages and letters through conveyors system automatically.

Artificial Intelligence In Logisttics
Artificial Intelligence In Logisttics

Administrative Duties: Assistant

DHL-IBM report mention: Although we are not robotic sound in our financial sector, using machine learning E & Y can detect a list of frauds with 97 percentage of accuracy.

Ernest & Young uses machine learning. Through which it classify the invoices first from international nodes and then go for red flags to review from human experts.

So, we can use this logic of machine learning to various types of business and Logistics is not different from it.

We can say that business software is focusing on avoiding paperwork while digging more into digitization in the organization. Artificial Intelligence can do a myriad of tasks efficiently even though.

Time to call an Action
Time to call an Action

Time to call an Action:

Meanwhile, all of these points are the only the tip of the iceberg, Artificial Intelligence and machine learning are in the game where players will get a never-ending array of cases through which some are potentially disruptive and others are evolutionary.

Work has started with Artificial Intelligence and these small steps turn into wonders which suggest that future transportation technology will be faster than our expectation.

In order to that, we are going to be more intelligent, algorithmic, and automated for our decision-making process with AI. We are still reimagining how we can make our services faster, better, and more cost-effective than ever before.

The Forbes Insights survey and DHL and IBM report assure that the advantages of such cutting edge technologies enhance the speed, productivity, better the response times and ability to see value chain.

Leave a Comment

Your email address will not be published. Required fields are marked *