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Challenges of Implementing AI in Inventory Management

Challenges of Implementing AI in Inventory Management | SolidBrain

It seems that only a few days ago artificial intelligence appeared, but now we see its implementation in almost every business-related tool. Company owners are actively using AI to streamline various tasks in data analysis, customer service, product development, etc. However, does it always bring the desired result? Unfortunately, there are situations when AI slows down business processes instead of boosting overall productivity. That mainly happens because of several reasons, that might be:


  • Data issues 

  • Lack of expertise 

  • Regulatory compliance.


But please note that reasons and challenges differ from one type of implementation to another. In this article we will delve into the question of AI in inventory management, the difficulties that arise during its implementation as well as the benefits and techniques that are highly recommended to use this year.





What is Understanding AI in Inventory Management


By referring to the AI in inventory management we mean the use of machine learning techniques to enhance processes that relate to inventory. For sure, artificial intelligence can’t replace humans in every aspect here and such points as decision-making, quality control, and exception handling are still up to the people. AI in its turn eases routine tasks such as data entry and order processing. As you can see, AI has the role of a so-called helper that lets people focus on the business-related tasks that matter. 






The Benefits of AI in Inventory Management


So, what are the benefits of AI in inventory management? In the situation when AI is implemented in inventory management in the right way, it brings businesses much aid that contributes to the overall success of a company in the long run.



Real-time data analysis


AI inventory management allows you to get real-time insights into the details that you currently need. These might be: 


  • inventory levels

  • product demand 

  • order status 

  • operational efficiency 

  • customer satisfaction.


Such a benefit enables you as a business owner to react quickly to changing conditions and make timely decisions. 





In addition to the immediate access to the needed details, the artificial intelligence ensures the accuracy of the information. 

Machine learning is made to process large volumes of data from different sources, identifying the patterns that can be neglected by people. Furthermore, the implemented algorithms are in the continuous mode of learning from new data and feedback, so over time the accuracy only improves. 



Saving costs


As we have already mentioned above, artificial intelligence in inventory management is used to automate people’s routine tasks which leads to reducing the number of employees. In the ideal perspective, humans are needed to set inventory management strategies that are aligned with business goals, and artificial intelligence will perform the assigned tasks. 



Customer satisfaction 


Speaking of the benefits, it’s difficult not to mention customer satisfaction and the perspective – their loyalty that is achieved thanks to faster order fulfillment, and efficient customer service. Using AI for inventory management helps companies reduce situations when clients encounter out-of-stock products and need to wait long periods for delivery. 






Challenges and limitations of using AI in inventory management 


It would seem impossible if such an implementation would bring only benefits with no challenges and limitations, wouldn’t it? Unfortunately, difficulties and concerns also arise at some point, especially when AI is unprofessionally implemented. To delve into this question, let’s remember how AI and IoT is used in inventory management.

The IoT sensors focus on gathering the overall information, covering the actual quantity of items, their health, and performance. The artificial intelligence algorithms in their turn are focused on analyzing the gathered information while predicting the demand and enhancing the operations. That sounds like a perfect idea, doesn’t it? Well, it could have been. Here we should keep in mind the following points.



Data privacy 


As you can see, to give you the needed result, AI gathers and operates large amounts of our information. This means that while implementing it into your business system, you should ensure to pay much attention to its protection. Here you might benefit from:


  •  data encryption 

  •  minimization of data

  • anonymization of details.


Additionally, you should constantly monitor the AI system and the information it has access to. Regular audits and professional assessments can give you a hand here. 



Complexity of operations


There also might be situations when the used algorithms simply can’t deal with that amount and complexity of information. Does this mean that artificial intelligence is still not good enough? That isn’t always the case. In the modern market, we see the situation when companies want to apply AI as soon as possible and ask specialists to set everything up in a short period. Unfortunately, that isn’t the solution here. The AI implementation requires deep analysis during which specialists will examine the level of mechanisms that your business needs. That’s possible only through examination, otherwise, the result may be not appropriate for your particular case, offering you functionality that is too basic or advanced.





Even though you save money that you could otherwise spend on employees completing the tasks manually, it’s also good to consider the fact that the AI implementation itself costs money. The prices here depend on various factors, still, however, small businesses aren’t likely to afford systems of this kind. Additionally, please note that the implementation can’t be finished after the initial investment. The ongoing maintenance costs are also likely to arise at some point.






Key AI techniques for inventory management 


So, we already know the benefits that AI in inventory management can give us, but that doesn’t mean that you should go ahead and implement it all at once. As we’ve mentioned, during the implementation there are also some challenges that you should keep in mind. So, first of all, it’s better to decide on the actual level of automation that you need. Your requirements might differ depending on the situation whether you’re running an e-commerce store and need to manage inventory across multiple warehouses or have a small retail shop where you don’t need to analyze large amounts of data. 

Typically, there are three main AI techniques for inventory management. 





Have you ever been in a situation when you’ve ordered something from an online store and waited for the delivery for a few weeks? The circumstances might be even worse while you could be waiting for the parcel but then suddenly get the message that goes “Sorry, the ordered product is out of stock”. Are there any chances that next time you are likely to order anything from that e-commerce store? We doubt so. 

To avoid such situations, online shops often benefit from the forecasting technique. The whole idea lies in the fact that AI mechanisms are used to examine the given data, combining it with individual selling trends and external factors to accurately predict future demand. Business owners use this information to ensure that the amount of goods is enough to meet customer needs. Thanks to this, companies can use resources to continue the selling of particular goods ordering them in sufficient amounts. 






Automatic product procurement


One more technique that helps companies handle their supply chain is automatic product procurement. Here the system not only forecasts the demand but also generates purchase orders.

As some businesses operate on a B2B basis, proper documentation is also often the key. Thankfully, artificial intelligence inventory management systems can be programmed to include all the necessary documentation while ordering products. The designated worker receives information about the order that he or she needs to review before sending it to the supplier. 






Controlling warehouse robots


Those companies that incorporate robots for controlling warehouses, can also benefit from AI-powered robot control. Here the inventory management AI is mainly used for efficient path planning, so that robots can freely navigate around the warehouse, without bumping into shelves or other mechanisms. In addition to this, if there are a few robots in the warehouse, the AI algorithms help to identify the workload and accurately assign the tasks.






Industries that can most benefit from AI inventory management 


More and more companies are starting to understand that AI for inventory management is a necessity, rather than an option. That’s why we see that there is a growing tendency to apply AI in various business industries. But as for now, there are a few of them that benefit most.



Retail and e-commerce 


Companies of this type have to purchase goods in large quantities from manufacturers and even those retailers that are only at the beginning of their business journey need to stick to some kind of AI inventory optimization. Otherwise, there are almost no chances for survival. The thing is, both retail and e-commerce operate in a quite competitive market where attracting customers might be challenging. So, here often win those businesses that anticipate economic trends and make more accurate decisions on inventory optimization. 








AI in inventory management also contributes a lot to logistics. In this industry, AI is widely known for its increased efficiency. Artificial intelligence helps to automate such tasks as picking the products, packing, and sorting them. Additionally, those business owners that are directly involved in logistics, often implement AI mechanisms to keep a constant examination of equipment. That’s how the focus here is on forecasting not only the inventory overstock but also the situations when robots might have some kind of malfunctions. 








Quite non-obvious at first sight, the third industry that is at the top of those that use AI in inventory management is healthcare. Especially in this field, it’s vital to ensure that there are enough products to cover people’s demands. Otherwise, this may result in unfortunate situations. In addition to this, there is a law that healthcare organizations must comply with strict regulations regarding inventory management. That’s why the AI is used to track expiration dates, ensuring that everything remains relevant.






Future Trends in AI and Inventory Management


Analyzing current tendencies, we can say that the use of AI in inventory management will become more and more important not only for medium-sized and big businesses but also for those who have only started their journey. When it comes to our anticipation, we can highlight the following points:


  • AI in inventory management might be even more cost-effective and accessible for small businesses.
  • The mechanisms will become more accurate and sophisticated in data analysis.
  • Artificial intelligence is also predicted to be able not only to supply people with relevant information, but also provide them with data-driven suggestions.


Are you thinking of implementing AI for your inventory management system? Then contact us and we’ll help you to get the most out of artificial intelligence. 


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Andriy Nytrebych - SolidBrain
Andriy Nytrebych Founder
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