If we were to describe AI in inventory management in one word, it would be: optimization.
The thing about AI in inventory management is that, for the most part, the technology has been there for quite some time now. While Chat-GPT and other AI models have influenced a meteoric rise in success in some business areas like finance and customer service, inventory management is a different case. This is not to say that AI has done nothing for inventory management and more to temper expectations for what’s to come. AI has changed the game in inventory management more subtly than the complete overhauls we have seen in customer support after LLM’s passed the Turing Test.
We have refrained from speaking about AI in inventory management at length thus far in favor of AI in the finance sector, but it’s now time for your favorite EA experts to lead you down this fascinating rabbit hole.
So, without further ado, let’s dive into the secrets of AI in inventory management. We’ll walk you through all the nuances of where and how AI can be leveraged at various points of the business workflow. Watch out for our bonus advice at the end. It’s especially useful for up-and-coming star entrepreneurs. Grab your popcorn, sit back, and relax as we drift through the world of AI in inventory management.
Table of Contents
Knowing the Battlefield
Much like a good general picking the right battlefield for his troops, it is paramount that entrepreneurs put much consideration on where to deploy AI in inventory management matters. The biggest mistake that can be made these days with all the AI hype is fully transitioning internal inventory management systems to AI control.
Here’s the list of major business sectors where implementing AI in inventory management gets best returns.
The Retail Sector
Retailers will doubtless be the foremost that spring to mind when picking candidates for AI in inventory management. Indeed, much of the brunt of inventory management effort falls to retailers. They must regularly monitor inventory availability, ensure timely restocking, estimate to a reasonable accuracy how much inventory to procure, and perform a myriad of other functions besides.
A good chunk of the data analysis and report generation can be handed off to AI. Employees can take on the overseer role. AI for inventory management is best utilized when employed for tasks that regular people cannot perform easily. For example, things like gathering vast swathes of market data and business performance metrics for demand and supply planning.
The Manufacturing Industry
After retail, manufacturing is where AI for inventory management can shine. Among manufacturers’ major pain points is inefficient inventory management and planning. As a manufacturer, you need to set up a line of dominos just right to achieve the end goal of profit. You need to have raw materials for production available and a constant supply carefully planned out to roughly meet the demands of retailers and vendors.
The same is true for retailers. But a big difference lies in the fact that manufacturers need to procure quantities of different raw materials to put together a single product. To illustrate, go to your pantry, pick up any packaged food product, and read the ingredient list on the back. Even a simple bag of salted chips has ten different ingredients going into it. Manufacturers have to ensure somehow all of those ingredients are available simultaneously to prepare the product. Add onto this the fact that a good chunk of raw materials is perishable. Thus, one can start to see why manufacturers can end up in a pickle if even a single domino, so to speak, is absent from the chain. It could bring the whole production line to a grinding halt.
AI in inventory management for manufacturers can be a godsend. Its ability to keep track of these of different materials is unparalleled. Inventory managers need only check the software and monitor as the artificial intelligence automatically updates supply levels. Plus it sends alerts when materials need restocking. This takes considerable pressure off the manufacturer’s shoulders and can vastly improve business by combatting delays and supply chain breakdowns.
The Logistics Sector
Any supply chain is incomplete without logistics.
Logistics has a lot of use for AI integration. For one, logistics companies handle hundreds and thousands of shipments across unfathomable distances daily. Without AI assistance and semi-automated workflows, the modern logistics industry would crumble in a day.
Have you ever wondered how you can order on Amazon today and get the package tomorrow? That’s because AI recorded and processed the order, and the people involved were there to verify, pack, and ship the product. This drastically reduces lead time and allows logistics providers to fulfill the maximum number of orders.
Plus, AI can analyze the daily delivery workload and suggest the optimal route to deliver the package to truck drivers and shipping professionals. Thus making deliveries faster and customers happy.
Strategies for Leveraging AI in Inventory Management
The biggest hurdle for inventory managers across the business world is ensuring they have enough inventory not to stock out, yet also not be overstocked. This is a hard balance to maintain, as multiple variables are in play and millions of bytes of data to go through.
AI-driven algorithms provide near-perfect supply chain forecasts through advanced data processing. While there will always remain a chance that things don’t go according to plan due to unforeseen circumstances. But as long as all the variables are considered, AI-driven inventory forecasting is supreme.
Instead of having your poor supply chain team try to account for variables like historical consumer behavior, market behavior, historical product performance, marketing influence, and so forth, you can just give AI all of the data. Then, your supply chain team can focus on operating the supply chain and making decisions based on that data.
Another popular implementation of AI in inventory management is as an organizing tool. AI can be an amazing assistant for organizing for retailers that hold a lot of stock. Many inventory management AI software comes with the ability to categorize goods based on predetermined parameters. So, for example, if you sell perishable and unperishable goods, you can let the AI categorize and organize products by that factor, making it much easier to find and assess stock.
AI enables businesses to manage their inventory across multiple warehouses, retail stores, and online marketplaces, transforming operations for those operating on diverse platforms. It eliminates the necessity for manual updates, minimizes discrepancies, and guarantees consistency. With a centralized, accurate view of stock levels across all locations, AI facilitates more efficient distribution and restocking, enhances customer service, and substantially lowers the risk of overselling.
On top of organizing, AI-driven inventory segmentation can also micro-manage. For example, some perishable products may expire in a week, others in months or years. AI can be instructed to split all products into sub-categories and lay out a supply plan that best fits each item’s life cycle.
Streamlining the Order Fulfilment Process
AI not only helps manage existing inventory; it also helps sell it. You can reap a slew of rewards by employing AI in inventory management to manage order processing. Just on the face of it, the major benefit would be the ability to accept orders 24/7. The automated inventory management and order management system can do everything, from order receipt to payment processing and even shipping.
The customer places an order and makes the payment online to confirm it. The AI receives the confirmation and places the order into the shipping queue. Then, the logistics provider fetches the product from the warehouse and delivers it. This can be completely automated, with only an overseer required to ensure the program doesn’t error or bug out.
AI can also monitor shipments, whether in inventory procurement or outbound sales. This real-time monitoring can be used to manage and ensure timely deliveries while also having a record of the whole process available to review should any hiccup arise.
Should Your Business Implement AI in Inventory Management?
The big question after all that exposition is naturally whether your own business should leverage these advanced artificial intelligence inventory management solutions.
While we cannot provide a general answer to the question, given its subjective nature, we can list some disadvantages that may dissuade using the technology. Remember that no matter what road you take for optimizing inventory management, there will be downsides. It’s all about weighing whether the upsides sufficiently outweigh the negatives.
AI is Not Self-Sufficient
No matter how good AI is, it will always require human oversight to prevent mistakes. Unlike human error, where a mistake can happen once and never again, if AI for inventory management runs into a bug in the algorithm, every algorithm process will be affected. The AI will not notice anything wrong and can result in a lot of damage if left unchecked.
AI can be more of a curse than a blessing for businesses with very light inventory management needs. Leaving things to an inventory manager or management services can be far more cost-efficient. With sufficient monitoring, human error can also be reasonably controlled.
Critical Timing and Data for AI in Inventory Management
If your business does not have sufficient tools at its disposal to provide AI-driven forecasting and analytics the data needed, then it’s better to stay away altogether. AI for inventory management and forecasting is only as good as the data available.
This is very relevant for start-ups, as they have a dearth of historic product performance data. Without this data, AI cannot get anywhere with forecasting. Ideally, businesses that have been operating for a while and have this data stored away are the ones that have the best shot of deriving tangible gains when using AI for inventory management. You have to judge yourself whether it’s too early or too late for your business to get into AI for inventory management.
Why Fix What Is Not Broken?
If your business is already operating successfully and experiencing no significant challenges with inventory management, is it worthwhile to actively integrate AI into the system?
This is a very valid concern; Plenty of veteran business owners may feel that their business is running just fine. Perhaps, here it’s worth it to do a cost/benefit analysis regarding AI integration.
If you are on the fence about whether AI integration into your inventory management system is worth it
EA experts are here to provide a free consultation providing solutions that is tailored to your business.