Top 7 Problems Artificial Intelligence Can Solve in Logistics

Top 7 Problems Artificial Intelligence Can Solve in Logistics
Written by Ratnesh

In the last decade, artificial intelligence (AI) has emerged as something that can change how human being think and work. Not only does artificial intelligence power several apps and devices, it is also beneficial for all businesses, and supply chain and logistics is no exception. In fact, a number of organizations have taken advantage of AI investments.

According to a report, artificial intelligence is one of the fields that is reaping a huge revenue for businesses around the world. It won’t be wrong to suggest that with the phenomenal rise in the volumes of data in supply chain and logistics, the urgency for more sophisticated solutions has become more pronounced. Therefore, legions of companies are adopting AI techniques such as machine learning, deep learning, and natural language processing.

These methods make it easy to evaluate massive volumes of data in an effective way to deliver a sophisticated analysis, activate a function or an event based on the consequences of the analysis, deliver requested information, and accomplish many other multifaceted functions.

Trends Hastening the Use of AI in Supply Chain and Logistics

A growing volume of data is not the only drift contributing to the growth of AI technology in the supply chain. In fact, there is a broad range of other vital features driving the trend, including computer power and speed, algorithmic improvements, and raising AI system access to big data.

The swift development of computers allows companies to integrate AI into their operations because the latter requires substantial advances in processing power and efficacy. For instance, one of these advances was the development of GPUs (Graphical Processing Units), which prolonged the characteristic functions of CPUs.

Big Data

While producing lots of big data, supply chain and logistics companies take advantage of artificial intelligence to generate significant volumes of the data to display its full influence. Some new types of data have also emerged in the last many years, and as well as creating an ever-increasing volume of data, AI is provided with enough material to work to its fullest potential.

Algorithmic Developments

Algorithmic growth has also seen an improvement in the last few years. It enables the finding of designs and discovery of associations that were problematic or impossible to find by humans or conventional technology alone. For example, smart algorithms can offer treasured information such as the number of buses available for distribution in advance so customers can know the price and estimated time frames for future deliveries.

These factors are collectively driving progress in artificial intelligence and making it a hugely feasible technology in many arenas. However, it’s yet to be seen how precisely the technology can change supply chain and logistics management. It’s quite an exciting experience to use artificial intelligence to solve logistics problems.

Here are the 7 problems that can be solved by artificial intelligence in logistics.

1. Logistics is faced with limitations of resources

• It goes without saying that companies offering logistics face a number of issues due to scarce or limited resources.


AI offers new insights into all aspects of logistics

The implementation of machine learning and other artificial intelligence technologies offers new understandings into an extensive range of facets, including logistics and warehouse management, teamwork, and supply chain management.

2. Supply chain performance is not properly evaluated

• Due to the shortage of resources, logistics companies the world over are not able to effectively evaluate supply chain performance.


AI provides unparalleled assessment of supply chain performance

Artificial intelligence can provide an unrivaled evaluation of supply chain management performance, which, in turn, helps to find new factors impacting that performance. AI integrates powerful competences of three sophisticated technologies – supervised learning, unsupervised learning, and reinforcement learning – to recognize significant aspects and issues impacting the performance of the supply chain. For instance, oversaw learning and can perceive identity scam and make informed forecasts, while strengthening learning can enable real-time decisions by providing pertinent data.

3. Companies face hurdles in analyzing huge amounts of data

• One of the biggest challenges logistics companies typically face is the capability to assess large amounts of data.


AI offers capability to assess huge amounts of data

Artificial intelligence is capable of analyzing large amounts of data, something very challenging and awash with uncertainty. Long before AI became a trend, technologies weren’t able to deliver value because they didn’t take into consideration this extensive variety of factors such as consumer traits on the demand side. Artificial intelligence enables the tracking and dimension of all the aspects that are required to improve demand predicting precision. In fact, it offers an infinite loop of forecasting, unceasingly fine-tuning the forecast based on real-time sales, weather and other factors.

4. Supplier relationship management is generally ineffective

• Another great problem logistics companies have to content with is a lack of supply chain professionals, which renders supplier relationship management virtually ineffective.


AI improves efficiency of supplier relationship management

Supplier-related risks are a chief consideration for logistics professionals; a company’s reputation is always at stake should a supplier make just one mistake. AI can examine supplier-related data and provide information to use for future decisions concerning certain suppliers. Consequently, a company can make better supplier decisions and improve its customer service.

5. Companies are unable to personalize customer relationship

• A general complaint against logistics companies that they are, due to one reason or another, are unable to personalize customer relationship.


AI raises customer experience

Artificial intelligence transforms relationships between logistics providers and customers by personalizing them. A great example of a personalized customer experience is DHL Parcel’s cooperation with Amazon. The delivery company offered a voice-based service to track parcels and get shipment information using Amazon’s Alexa-powered Echo.

6. Supply chain is virtually dormant

• Since most of the companies have no proper methods to improve production planning, they face dormant or ineffective supply chain.


AI helps reduce supply chain dormancy

Earlier, companies didn’t have classy apparatuses to improve production planning and factory scheduling precision. With the advent of AI, they are able to do that because the technology allows them to examine a broad range of restraints and augment for them. This works particularly well for build-to-order makers because artificial intelligence helps them balance the limitations automatically. For instance, by virtue of AI, businesses can decrease supply chain dormancy for parts used in the most popular or highly modified products.

7. Predicting and improving customer experience becomes difficult

• Scarce resources make it difficult for businesses to predict the number of required goods.


AI helps forecast and improve customer experience

It’s mandatory for companies to forecast the number of needed goods. The company will suffer grave losses if the inventory is limited but the demand is high. In addition, artificial intelligence can use algorithms in order to envisage trends. A number of studies claim that AI algorithms nearly always predict better than human specialists.

Nowadays, AI lets tracking and gauging all essential aspects improve the precision of demand forecast. This data helps make warehouse management easier. Artificial intelligence can also bring constructive changes to the customer experience.


The importance of artificial intelligence in this day and age can hardly be doubted. Although it lacks in some fields, its significance in other areas such as pattern recognition and machine learning is well-founded. The technology already plays a huge role in some of today’s cutting-edge supply chain and logistics solutions, growing efficiency, efficiency, and automating numerous tasks for supply chain managers and planners.

In fact, an explosion of AI technology in the supply chain is inevitable thanks to the recent high-tech breakthroughs in big data.