7 Challenges in Logistics that AI Solves

Updated on Dec 18th, 2023

7 Challenges in Logistics that AI Solves

Artificial Intelligence started affecting the logistics sector along with the supply chain. Moreover, AI has transformed the way people write, think and work, since the last decade. And undoubtedly, it is reaping the huge benefits in the form of revenues, for businesses and organizations all across the world. We can now witness an amazing and significant innovation such as smart roads, autonomous vehicles. And it might sound like a cliche or a buzz, but legions of organizations and companies are adopting AI techniques, machine learning, deep learning, etc. These methods make it easy to evaluate a large amount of data in a sophisticated way. Apart from this, nearly 36% of the companies and organizations are adopting AI and ML in logistics, and productivity is expected to increase by 40% by the year 2035. The primary goal behind implementing AI in logistics and transportation is to automate the time-consuming actions and to save money. The giants like (Google or Amazon) have invested in the technology and reaping the benefits. 




Warehouse operations and functioning are highly transformed by AI. Be it data collection or inventory management, etc. which automatically leads to the rise in revenues. Let’s give it a thought, about why are we using AI in logistics? AI predicts the demand for the product in the market. And accordingly, the products can be modified and can be sent to the warehouses according to the delivery requirements. This means the logistics companies can save a huge amount of money incurred on transportation and can also prevent the wastage of goods. Hence, the automation in the warehouse helps to accomplish day to day tasks, additionally, we can organize the inventory. And because of this, the logistics industry has witnessed a tremendous rise in productivity. For instance, Ocado, a supermarket in the United Kingdom, has built a fully automated warehouse and named the robot “hive-grid” which can carry out approx 65,000 orders over a week. The machine is helpful in product sorting and packaging that too based on the delivery requirements.  



Here comes one more use case of logistics and AI, i.e. smart roads. Nowadays even the cars have become intelligent, so how could we leave the roads behind. Many companies are indulged in the process of smart roads, according to regional needs resulting in the development of the solar panels and LED lights on the highways. The light is to guide the drivers about the road obstacles on the roads and the panels heat the roads to prevent them from greasiness. The integrated roadways created the pavement system, which basically connects all the vehicles on the road to the internet and acknowledges them about road conditions, traffic jams, accidents, etc very much in advance. 



Autonomous vehicles stand for self-driving vehicles. The aim to introduce these vehicles is to reduce the logistics expenses by boosting the supply chain. Includes all the vehicles that are involved in the supply chain. Self-driving cars are undeniably inevitable. Additionally, the complete logistics industry would be benefited from the introduction of self-driving AI. however, the technology is improving, but they’re still a lot of work to do. But the time is not far when there would be fully autonomous vehicles drive on roads that too without human supervision. Here AI is taking an increasingly active role. The sensors and cameras would be embedded to keep track of the vehicles to lessen the time of products in the market. However, Waymo was the first to reach the milestones, in the automation journey.  The vehicle first launched in Arizona, 2018, is the fully-self-driving vehicle is the safest and the most advanced vehicle on the road today, without any human sitting on the seat. The vehicle being equipped with smart sensors, which provide the 360-degree view of the word, which a human sitting on the seat could never get.


We all are aware that the back end tasks of the logistics and the supply chain consume a lot of time and expense. And the introduction of the AI made a lot of things easier. RPA (robotic process automation) combining with AI has modernized the supply chain and automated a lot of back end tasks of the logistics and supply chain. This way, the routine tasks have been customized, eliminating unwanted costs. UiPath has witnessed the success in the Robotics process automation and has been recognized as a leader in the Forrester Wave by achieving the highest scores in the strategy and market presence category as well as in evaluated vendors currently. The robot can carry out 99% of their daily and routine back end tasks and it can “see” screen elements. 

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7 Challenges In Logistics That AI Solve

1. Issues due to scarce resources
2. When The Supply Chain Is Not Effectively Evaluated
3. Face Hurdles To Access a Large Amount Of Data
4. Efficiency Of Supplier Relationship Management
5. Help Companies To Personalize Customer Experience
6. Helps Reduce Supply Chain Dormancy
7. Improves Customer Experiences

1. Issues due to scarce resources

Since we all know logistics often face a number of problems, because of the scarcity of resources. But the understanding of various facets has become way more easy with the implementation of AI and machine learning in the supply chain and logistics. Apart from this management of the inventory and team members becomes easy. Hence, Artificial Intelligence has been offering new insights into the aspects of Logistics and supply chain. 

2 . When The Supply Chain Is Not Effectively Evaluated

As mentioned above, just because of the shortage of resources, logistics companies all across the world are not able to evaluate supply chain performance on a regular basis. And the implementation of Artificial intelligence and machine learning offers an unparalleled assessment of the day to day activities to the logistics companies. Since AI provides the insights into supervised learning, the logistics companies can way more easily identify the aspects affecting the performance of the supply chain, and make informed forecasts as well as take measures to improve the performance of the supply chain. Apart from this, it also helps to take real-ti e decision by providing the pertinent data. 

3 . Face Hurdles To Access a Large Amount Of Data  

Facing the hurdles in accessing a massive amount of data is again a challenge faced by a lot of logistics firms. Typically they lack the capability of accessing the data. But as we have witnessed, Artificial Intelligence can help them with something which seems to be challenging and impossible as well. Long before when AI didn’t come into existence, technologies were not advanced and capable enough to deliver value and not capable enough to understand the consumer traits. Artificial intelligence can dig deeper into all the aspects that can improve the demand predicting precision. In fact, it can provide information and forecast based on real-time sales and weather as well as other factors. 

4 . Efficiency Of Supplier Relationship Management 

AI can improve the efficiency of supplier relationship management. Not having enough supply chain professionals is again the biggest challenge faced by logistics firms and make the supplier relationship management virtually ineffective. Since we all know the supplier-related risks are the major concern of many logistics firms. Artificial Intelligence provides useful insights and can examine all the data related to the supplier and not only this but it also provides the information for current as well as for the future, to help logistics companies to make real-time decisions concerning certain suppliers.  Hence. With the implementation of AI and machine learning the companies can improve their customer services as well. 

5 . Help Companies To Personalize Customer Experience 

The general challenge faced by the logistics companies also includes their lack of providing a personalized customer experience. Implementation of AI in the logistics firms would raise customer experiences. AI is powerful enough to enhance the supplier (the logistics providers) and customer relationships by providing full personalization. 

6 . Helps Reduce Supply Chain Dormancy  

AI in logistics can eliminate the supply chain disruptions, as well as customer dissatisfaction. Years ago, companies use to lack in production, the reason being lack of advanced and classy equipment. Machine learning and AI have provided logistics with all the advanced equipment which can improve production and planning strategies. This automatically helped in reduced freight costs, improved supplier delivery performances, reduced supplier risks and provide highly modified products. Hence, Artificial Intelligence, and its core constructs, are best suited for providing insights into improving supply chain and inventory management performance not available from previous technologies. Therefore, it enables the companies to extend the life of the equipment, machinery, engines, and warehouse equipment, by searching for new patterns in data gathered via IoT sensors.   

7 . Improves Customer Experiences 

AI in logistics helps enhance end-user experiences by improving the supplier quality management and compliance by searching the new ways an patterns in supplier’s quality level, improving production planning, etc. combining the Artificial Intelligence and machine learning with the modern and advanced analytics, IoT sensors and real-time monitoring provides the end-to-end visibility across many supply chain methods and patterns for the very first time. It has become a lot easier for the companies to forecast the goods very much in advance and the current demand for the goods saving the companies from losses. Since the AI algorithms can predict the demand for the goods in the market. Therefore, some constructive changes could be witnessed. 

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Take-Home Message

There’s an undeniable and undoubted importance of Artificial Intelligence and machine learning. And not only this but we have witnessed a high-tech breakthrough in the big data. Machine learning and artificial intelligence in future supply chain management that is revolutionizing every aspect of the logistics and supply chain. 

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