The traditional inventory management practices you’ve grown accustomed to may be in danger: faster market cycles and geopolitical disruptions are fundamentally challenging supply chains and historical logistics strategies. While these impending realities are threatening many businesses all across the world, it’s natural to question how your business can stand up to the same conditions.
Twenty percent of business leaders believe AI will handle up to 30% of daily tasks, according to McKinsey. Likewise, nearly 70% of CEOs consider AI essential for inventory and stock management (learn more here).
When you’re done reading, you’ll walk away with FIVE tips for using AI to improve your inventory management, and you’ll also gain a deeper understanding of AI’s future impact on your business.
A preview of our 5 tips for AI inventory management:
Other important content in this guide:
One of the biggest challenges of growing any business is anticipating customer behavior. However, when you use AI tools to support your inventory management you will be able to both predict upcoming customer demand trends and react in near real time to changes — rather than responding to demand shifts over weeks and months.
Here are some of the ways AI can analyze customer behavior and maximize your market responsiveness:
With tariffs potentially shrinking the retail market by up to $78 billion, you need a reliable way to control costs and protect margins; this is where AI-powered tools can help your business thrive in the midst of industry chaos.
One of the high-impact ways that AI does this is through its ability to take offline info (such as faxed documents or paper purchase orders) related to your supplier and digitally ingest them — so every important piece of data is usable for predictive analytics. This can help immensely by providing more accurate data for calculating inflation changes and controlling costs.
The specific technology that allows legacy documents to be digitized and used in predictive analytics is called AI OCR (optical character recognition), and it’s something we’ll discuss more a little later.
Learn more about Predictive Analytics in our guide for understanding the pros and cons of the different types of inventory management.
Time is money, and spending your time toiling away at repetitive tasks — like managing purchase orders, tallying bills, and checking inventory levels — keeps you from focusing on revenue-driving projects. Utilizing AI-powered tools in your inventory management means:
Inventory management is a magnet for chaos and reactivity, which can easily put your efficiency at risk. Keeping up with the demands created by this chaos is a huge task for anyone to take on. However, with an LLM tool, you can make high-context, data-based decisions without missing opportunities or overlooking important factors. It’s a significant time saver for making decisions and serves as an invaluable lifeline when stress is high and you need to get ahead of problems.
Sifting through the seemingly endless number of tech stack options to integrate into your business’s backend can be time-consuming, stressful, and certainly confusing. However, by using an AI tool (which can seamlessly integrate into our headless ERP), you can efficiently search for the “hidden gem” software solutions that best fit into your tech stack.
These AI tools include:
While these tools largely work in similar ways, each is created with different uses in mind. We'd like to highlight two in particular, because they excel at research:
Perplexity is an LLM tool, functioning as a high-context search engine capable of giving you detailed rationales for the information it provides, while also giving you citations for each source it crawled to answer your query. ChatGPT (also an LLM tool) is also great for researching topics you don’t know much about and synthesizing bulk information into something much more digestible. While using any of these AI search tools, it’s very important to check the cited sources — it helps to have the fullest picture of whatever you’re researching, whether it’s new tools to integrate or market opportunities based on current events.
With the number of tools that could be integrated into your business growing exponentially, AI search can be a significant help! By parsing the information you need to make your decision — and comparing it to your business needs — it can deliver contextual insights into the tools you should consider. It can also significantly reduce the amount of time you spend researching and ensure that you’re integrating the right fit for your business.
Legacy tools and processes are the leading cause of lost efficiency and skyrocketing costs — according to Gartner, 40% of infrastructure systems have technical debt concerns. However, reorienting your technical infrastructure around AI tools, modular ERPs, and low-code tools can significantly reduce the impact of technical debt in your business. AI integration is especially important as it will impart a competitive advantage to businesses that choose to become fluent in its use.
Since AI is not a passing trend and is being deeply integrated into most major tech platforms, it’s something you cannot afford to ignore as a business leader. Plus, these integrations directly result in the removal of technical debt in your retail ops, inventory management, and supply chain, dramatically lowering a significant element of your operating costs.
To paint a better picture of the future of AI integration, let’s finally dig into what AI OCR is, and how long-term AI data aggregation can ensure deeper insights into your business’s present and future.
Receiving handwritten purchase orders from clients can be a major slowdown for your inventory processes, especially when they’re largely drafted in shorthand with lots of industry jargon. For new people working in your business, purchase orders like these can lead to mistakes, which can cause a number of problems you just don’t have time to tackle. An LLM-augmented OCR (Optical Character Recognition) can easily parse handwritten documentation and can be trained to interpret the shorthand, abbreviations, and terminology unique to your clients and your business.
Traditional OCR technology has existed for a long time, but the integration of large language model (LLM) AI allows the OCR to become flexible, where it was once rigid. Because it understands context, it can more easily adapt to inconsistent formatting from clients or suppliers, while also making sense of non-standard layouts.
It works hand-in-hand with your team by enabling them to review and confirm the AI-generated data — such as order lines, order quantities, and inventory SKUs — which saves their time for more important tasks.
As your business grows, gaining insights into your process efficiency and customer behavior gets increasingly difficult; spreadsheets balloon in size, and there are more departments, workflows, and supply chain steps to manage than ever. By integrating AI tools into your business early — and it becomes better at tasking and delivering predictive analytics — you’ll be able to receive high-context reports and suggestions that fit your business at scale.
For our own AI-powered products, we envision demand forecasting that is flexible enough to get beyond linear statistical models — instead utilizing many non-linear datapoints to achieve higher accuracy in sales and inventory estimates. As LLM technology continues to evolve, the sky may really be the limit for the impact AI insights can make on your inventory management and retail ops.
You’ve certainly seen the decline of big-box retail giants in recent years, and in 2025, it’s been getting worse. Big-box retailers weren’t able to quickly react to the shift in market sentiment toward online shopping — they incorrectly assumed that because they owned the physical space that the market would reward their commitment.
Viewed another way, they let the sunk-cost mindset blind them for too long, when downsizing their physical footprint would have been wiser. Between their slow reaction to market changes and stubborn maintenance of legacy systems, they haven’t been flexible enough to navigate economic downturns.
On the other hand, your business is lean, omnichannel, and agile — but you need operations and backend systems that match your strengths (we understand it’s highly likely that you’re being held back by sluggish legacy technology). If you choose to make the most of AI-powered tools, you can better leverage your strengths and make waves in the market, and continue to outpace big-box retail.
As AI continues to see wide adoption and training models improve, there’s a huge advantage to adopting bespoke tools trained on your company’s data. Having an AI solution that knows your business inside and out — and can contextually parse new data as it becomes available — means you can see massive improvements to your inventory tracking, resource allocations, and operational processes.
With the NRF predicting a 7-9% surge in non-store and online sales (even with the potential impact of tariffs looming), you need every advantage you can get to ensure you capture increased revenue this year.
If your business uses a modular ERP, you can gain access to customized AI-powered modules that can track your inventory in real time. For example, Tailor’s AI model is especially helpful if you’re an omnichannel seller with multiple brands or shared inventories between points of sale.
Operating an omnichannel business often means demand is high, but it also means that business is chaotic. Between siloed data, non-integrated channels, inaccurate inventory, static fulfillment logic, and rigid workflows, there are almost too many challenges to deal with on a daily basis.
Fortunately, AI integrations can be designed to help you win, and it does this through seamlessly integrating the parts of your business that ordinarily wouldn’t talk to each other. Our own AI-powered ERP product is designed to maximize the visibility of these siloed data streams and non-integrated, legacy information channels while also ensuring they are completely accounted for in reports, sales statics, and more.
Tools designed for omnichannel support must be able to account for the unique workflows underpinning your business — this would look like leveraging AI OCR to integrate legacy data, utilizing real-time sync across your sales channels, and leaning on predictive analytics.
Keeping track of when your business traffic shifts from primarily online to in-person can be extraordinarily difficult. Shopping habits often change with factors you can’t control. While you can try to make some educated guesses about which area to focus on, AI-powered tools can help you remove some risk from these decisions.
If you’re using an AI-powered ERP solution, you can track your traffic in real time, and predictive analytics can serve to help you anticipate changes while also giving you the information you need to curate your inventory so you can more predictably balance your omnichannel demands.
The future of business is here — not making preparations to integrate AI will undoubtedly leave your business behind. Thankfully, the tools available to you now are easy to implement and low-cost. Plus, they’ll only gain functionality over time and can alleviate a number of headaches for your teams (and yourself).
These AI tools can help you navigate difficult retail landscapes by:
You can even use LLM-powered tools to help you set new business objectives or find “hidden gem” tools to integrate into your tech stack. Likewise, the future of AI tools is bright: AI OCR can help your business bridge the gap between analog processes and modern workflows, and more advanced predictive analytics can help you find bespoke solutions to utilize in your business development.
If you’re seeking to remain competitive in omnichannel retail, AI-powered tools are going to be the difference makers for businesses that excel and those that get left in the dust.
