After reaching the peak of the hype cycle last year, the AI fatigue is setting in. Modern retailers are done talking. They want practical ways to deliver value from AI.

The truth behind the buzz is that AI can help you achieve success with inventory as you scale — if you know how to use it.

With an unmatched ability to crunch vast amounts of data, AI can drastically improve your forecasting, save your team hours in manual data analysis, and help you make profitable business decisions in a fraction of the time.

Here are four ways modern brands and inventory planners can start using AI to improve operations.

1. Data analysis

With the power of machine learning to rapidly crunch terabytes of complex data, AI is a perfect fit for a problem like inventory.

From pricing to promotions, to weather events and product seasonality, inventory encompasses more data points than any other aspect of your business, and there is a huge amount of variance.

Unlike traditional tools and spreadsheets, AI can process a much broader and deeper data set, including:

• Current and historical sales
• Promotions
• Pricing
• Seasonal variations
• External factors (like weather and extreme events)
• And much more!

No matter how strong your Excel skills, there isn’t a spreadsheet in the world that can give you robust predictions in each one of these areas — spreadsheets simply weren’t built to process that much data.

Rather than spending hours collecting, centralizing, and analyzing your data manually, AI can account for more of the factors impacting your sales and inventory and help you identify the right patterns faster.

2. Forecasting

The more complex the data, the more accurate the output. AI’s ability to handle complex data sets with ease means that it can also deliver massive value to your forecasting processes. 

That’s because machine learning doesn’t just process your data, it can also understand:

• Intricacies within the data
• Relationships between various data points
• Where the anomalies are
• How to correct them

With the right AI tools, you not only have the power to analyze past data. You can also clean and correct your data to add context around anomalies such as sudden spikes or drops in sales due to flash sales or low-in-stock inventory.

By training your AI algorithms to understand the patterns in your data, they can use new information to generate better and better forecasts over time.

For example, if you’re chronically over- or under-stocking, you can train your AI to automatically identify the problem and adjust its model to become more accurate as more data comes in.

3. Time saving

With a little help from AI, manual inventory tasks that used to take hours can be done with a single prompt.

Here are just a few of the inventory processes AI can help you accelerate:

• Gather data from multiple sources automatically
• Project your forecasts (and improve them over time!)
• Make quick calculations based on vast amounts of data
• Create and compare likely scenarios
• Suggest the best decisions for your business

If you’re like most multichannel brands with vast amounts of data across multiple channels and inventory locations, the time savings could be massive. 

A number of retailers are even building custom AI chatbots trained on their own data and language learning models (LLMs) so that what would have taken hours or even days with a spreadsheet-based system can now take place in a matter of minutes with AI.

4. Decision making

Last but in no way least, AI can be an extremely powerful tool for workflow automation.

By using AI to suggest actions based on your data, you and your team can go from ‘what’ to ‘how’ much faster. Think less: ‘let me analyze the data and figure it out,’ and more, ‘hey AI, what do I need to do based on this information?’

At the end of the day, inventory planning is all about next decisions. Your inventory is a living organism that constantly requires you to make the best next action you can make.

With AI, you can get faster answers to questions like:

• What was the last decision I made with the data that I have today? 
• What is going to be the outcome of that decision in the future? 
• Has that decision changed based on the new data received since I made it? 
• Is it better to do something else?

Say you made a decision to purchase 1,000 units to send to the US, but now you’re getting to the end of production in China.

You can ask your AI: Based on all the data that I collected in the last 30 days while the item was still being produced, is 1,000 units to the US still the best option?

Perhaps now the answer is 800 on a vessel to the US, and 200 to Europe. Or maybe you need to increase the price because you don't have time to replenish and it's going to be too expensive to send by plane.

By using AI to rapidly reveal the next best action for your inventory, you get a done-for-you decision tree that maps all the possible outcomes for you, so you can decide what’s next.

Better decisions at every step

AI has the power to identify patterns from a virtually endless stream of past data. From simple tasks like understanding your inventory levels to more sophisticated use cases, such as making the best replenishment decision in a complex inventory scenario, AI can help.

It may take a little patience and experimentation, but over time, the benefits of AI will begin to compound, leading to better forecasts, stronger decisions, and increased profitability.

But for all the hype, AI isn’t a substitute for inventory planners. We’re still years away from being able to use AI to get real-time data in a single location and standardized format, but adding AI to your inventory planning can still be a gamechanger for your business.

Start training your AI today. Try the inventory algorithm that’s been tested on over 3 million SKUs. Learn more with your free trial of Flieber.