Artificial intelligence for inventory management

How Artificial Intelligence is Revolutionizing Logistics?

The benefits of AI: from inventory management to delivery optimization

​​Everyone is talking about artificial intelligence (AI) at the moment due to the spectacular advances seen in the ChatGPT chatbot. But what does AI really consist of​,​ and what benefits can it bring to specialized companies in terms of logistics optimization?​​​ 


First of all, it is worth pointing out that artificial intelligence is a branch of computer science that focuses on developing machines capable of simulating human intelligence, i.e. imitating a person’s cognitive abilities. These systems are able to perform highly complex tasks such as image and voice recognition, decision making​,​ and automatic text translation. 

Central to this set of concepts and techniques are two major disciplines:  


  • Machine learning (ML): also known as automatic learning, this is based on algorithms that can discover repetitions (patterns) in one or more data sets and derive predictive analyses. In short, the machine is able to automatically learn a set of rules based on varying sizes of data flows, without having been specifically programmed beforehand. 


  • Deep learning (DL): this consists of using an artificial neural network, thereby imitating the functioning of the human brain. The neural network is ​composed​ of multiple layers of neurons. Each of these interprets the information of the previous layer and allows the system to progress in its learning. Like machine learning, deep learning needs to be trained with big data sets. The larger the volumes, the more accurate the algorithm becomes. 


Faced with an increasingly complex and unpredictable environment, companies' supply chains are undergoing ​a ​digital transformation and can benefit from what ​artificial ​intelligence ​is bringing​ to the table. 

The benefits of a digital supply chain, backed by Artificial Intelligence 


AI can help operational teams make decisions, thereby helping to optimize operations, reduce costs​,​ and improve the customer experience. 


This applies, first of all, to optimizing delivery routes. From weather conditions to road traffic, the availability of drivers and vehicles, and delivery schedules, AI algorithms propose optimal routes for delivery rounds and schedules, bringing substantial savings in terms of time, mileage, vehicle usage costs and pollution (greenhouse gas emissions). 


Furthermore, inventory management involves a large number of parameters that are not always easy to control. Through a fine-grained analysis of data related to demand, sales trends, product portfolio characteristics and supplier constraints, AI is able to optimize inventory levels for different SKUs, thereby reducing the risks of both shortages and overstocking


Regarding predictive maintenance, artificial intelligence can also ​take in​ and analyze very large amounts of data from sensors on vehicles, production lines or other equipment. This allows it to predict when maintenance is needed, thereby reducing downtime and ​maintenance​ costs. 


AI can also bring numerous benefits in terms of customer service. Until now, AI-powered chatbots could handle a certain number of customer requests and provide more or less accurate answers. With the arrival of generative AI systems such as ChatGPT that can generate new content from an existing database, the quality of communications ​has​ significantly improved. These high-quality interactions with the company's ​current and prospective ​customers help ​to ​reduce wait times and ​to ​improve satisfaction levels. 


As for fraud detection, AI can analyze data from various systems (billing, transaction volumes, supplier databases, etc.) to detect and prevent fraud, thereby reducing the risk of financial loss for any type of organization. 


Lastly, contract management and analysis can be greatly improved through algorithms. AI-based contract document management solutions enable ​legal teams​ to ​operate more efficiently​ and ​to ​ensure a high level of compliance. This is why GEODIS selected the artificial intelligence platform of the French start-up Hyperlex to handle the overall monitoring of its contractual commitments

"By harnessing the full potential of artificial intelligence, supply chain companies can make their processes more efficient, optimize costs and become more competitive." 

Pierre Lenclud, Chief Data Officer at GEODIS 

Emerging AI trends in the supply chain: a promising future 


The future of artificial intelligence in the supply chain industry is very bright​,​ and will continue to shape how companies operate and become more competitive on their markets.  


Some of the future AI trends in this sector​ ​include forklifts, order picking robots, cobots (collaborative robots) and drones. This equipment, which we are used to seeing in warehouses, is gradually becoming more autonomous. Armed with a whole array of sensors, equipped with cameras providing computer vision and guided by AI, ​they​ ​move​ goods, prepare customer orders and can even carry out inventories without human intervention.  


GEODIS has set up small autonomous robots, deployed in a fleet. Instead of pulling a heavy cart through the entire warehouse, the pickers are assigned to a specific area, while the robot moves optimally from station to station according to the order to be picked. The dialogue between robot and picker happens through user-friendly interfaces and the recognition of the employee is handled by the machine. This approach has enabled GEODIS to double the productivity of its teams while reducing employee fatigue. 


On another front, namely sustainable development, artificial intelligence makes it possible to respond to increasingly strong ​consumer ​demand ​concerning​ the sustainability of the goods they buy. The eco-responsibility of products requires the ability to provide flawless traceability of the components used in their ​manufacturing​. 


Lastly, the integration of blockchain, in close association with AI, creates an even more secure and transparent supply chain, thereby reducing the risk of error, malfunction and even fraud. 


During the pandemic, GEODIS conducted a trial with IBM. A blockchain solution offered by the US giant made it possible to automate the retrieval of temperature data from ​transported ​vaccine batches ​     ​and ​to ​certify them. This process prevented the need for manual data verification by pharmacists, saving GEODIS teams valuable hours in the distribution of doses. 


Lastly, AI can automate the processes of monitoring suppliers, which are increasingly intertwined and dependent on each other within a globalized supply chain. By scrutinizing information related to their financial health, the contracts they sign, or any climatic, political or social events related to their geographical locations, AI identifies the weak signals that make it possible to detect a potential risk of inability to deliver all or part of their services​  further up the line​. 




AI is already playing, and will continue to play, an important role in the far-reaching transformation of the enterprise supply chain. By providing valuable analytics, automating operations and improving the customer experience, AI gives organizations that adopt it and exploit its potential a significant competitive advantage in the marketplace.  


Are you interested in exploring our warehouse intelligent automation solutions? 

Pierre Lenclud Chief Data Officer at GEODIS

Pierre Lenclud

Chief Data Officer

He ensures that data becomes and is regarded as a decisive asset, which can be leveraged on and shared to achieve these ambitions. He is in charge of moving GEODIS towards a Data oriented vision and fully unleashing the data potential with an efficient data governance, able to address the necessary transformation needs and challenges. His team is impelling the global data strategy methodologies, principles and policies to allow all stakeholders to manage their data and ensure its quality.