AI and IoT work together to give businesses real-time visibility into their inventory. IoT devices, such as RFID (radio frequency identification) tags and smart sensors, track where items are, how they're moving, and in some cases, the conditions they\u2019re stored in. AI uses this continuous stream of information to forecast demand, trigger reorders, and flag issues like missing stock or changes in temperature.<\/p>\n"},{"question":"How does AI improve inventory management in the supply chain? ","answer":"
AI improves inventory management by analyzing demand patterns, predicting supply disruptions, and automating stock decisions. The technology helps supply chain teams reduce lead times, prevent stockouts, and make faster adjustments based on real-time conditions.<\/p>\n"},{"question":"How does Amazon use AI for inventory management? ","answer":"
Amazon\u2019s Sequoia system<\/a> integrates mobile robots, gantry systems, and robotic arms to streamline inventory storage and retrieval, enabling the company to identify and store inventory up to 75% faster and reduce order processing time by up to 25%. Additionally, Amazon uses robotic arms like Sparrow to handle repetitive tasks, improving efficiency and employee safety.<\/p>\n"},{"question":"Can inventory management be automated? ","answer":" Yes, it\u2019s possible to automate many aspects of inventory management using AI, sensors, and connected software. Businesses can automatically track stock levels, trigger reorders, and forecast demand without manual input. <\/p>\n"}]}],"activate_cta_banner":false,"banner_url":"","main_text_banner":"","sub_title_banner":"","sub_title_banner_second":"","banner_button_text":"","below_banner_line":"","use_customized_cta":false,"custom_schema_code":"","parse_from_google_doc":false,"content_doc":" In 2013, US retailer Walmart lost an estimated<\/span> $3 billion in sales<\/span><\/a> due to out-of-stock merchandise. The company blamed poor weather, tax pressures, and a struggling customer base for the loss, but the real issue ran deeper. Inventory was growing faster than sales, yet shelves continued to be empty for customers.\u00a0<\/span><\/p>\n <\/p>\n Problems with inventory management are achingly common for businesses. When internal ops teams can\u2019t see what stock is available, where it is, or when it needs to move, this naturally impacts the customer experience <\/span>and<\/span><\/i> the bottom line. The solution? Artificial intelligence.<\/span><\/p>\n <\/p>\n This guide explores how AI in inventory management forecasts demand, tracks stock in real time, and automates replenishment. We\u2019ll also introduce how platforms like monday service support faster, leaner inventory workflows across your operations.\u00a0<\/span><\/p>\n <\/p>\n CTA\u00a0<\/span><\/p>\n AI in inventory management uses artificial intelligence technologies so businesses can track and manage their stock levels. Instead of setting static reorder points or relying on manual checks, AI inventory systems continuously learn from past sales and supplier behavior to make real-time adjustments and deliver valuable insights.\u00a0<\/span><\/p>\n <\/p>\n AI-powered platforms flag inventory issues early, recommend when to restock, and help operations teams act before shortages disrupt the flow of work. The overarching goal is to manage inventory without the usual guesswork.\u00a0<\/span><\/p>\n Stock control has always been about balance, but AI brings more focus. Instead of reacting to shortages, teams can fine-tune <\/span>what<\/span><\/i> they stock and <\/span>why<\/span><\/i>. As <\/span>Nidhi Chauhan<\/span><\/a> of Digital Romans puts it:\u00a0<\/span><\/p>\n \u00a0<\/span><\/i><\/p>\n \u201cSmarter stock management isn’t about holding more. It’s about knowing what actually moves the needle.\u201d\u00a0<\/span><\/i><\/p>\n <\/p>\n That\u2019s exactly where AI makes a difference, supporting clearer decisions across every stage of inventory planning. Here\u2019s what you can expect by incorporating AI into your inventory <\/span>service management<\/span><\/a> strategy.\u00a0<\/span><\/p>\n <\/p>\n <\/p>\n POLL\u00a0<\/span><\/p>\n Traditional inventory management often involves working with incomplete or delayed information. AI closes those gaps and delivers the following specific benefits:\u00a0<\/span><\/p>\n Inventory is at the heart of every supply-driven business. So, when the numbers are off, everything suffers \u2014 products are oversold, stock is misplaced, and customers end up disappointed. Despite how common these problems are, 58% of retailers and direct-to-consumer brands operate inventories with <\/span>less than 80% accuracy<\/span><\/a>. AI tightens things up by flagging discrepancies early, syncing data across systems, and cutting back on manual, error-prone work.<\/span><\/p>\n When inventory data lags behind reality, it creates friction both internally and at checkout. The most common delay between an inventory change and a system update falls between 31 and 59 minutes; only 7% of businesses manage to <\/span>update their inventory within 5 minutes<\/span><\/a>. That gap has real consequences: 38.6% of retailers cancel at least 1 in 10 customer orders due to stock inaccuracies.<\/span><\/p>\n <\/p>\n AI solves the problem by keeping systems updated in real time to confirm what customers see is actually available.<\/span><\/p>\n Holding too much inventory ties up cash and storage space. Holding too little risks missed sales, and rushed replenishment. So, what’s the right balance? AI finds the perfect middle ground by adjusting stock levels based on actual, current demand. You can expect fewer emergency orders, lower carrying costs, and better use of working capital.<\/span><\/p>\n As your operations grow, so does the complexity of managing inventory across different channels and locations. AI supports growth by handling more variables without adding more manual work. Whether scaling to new markets or expanding your catalog, AI maintains system stability while the business moves forward.<\/span><\/p>\n Inventory management depends on coordination across teams, tools, and timelines. AI gives managers clearer insight into what\u2019s needed, where, and when, so you can focus people and resources where they\u2019ll have the most impact. Instead of reacting to bottlenecks, teams can plan around them.\u00a0<\/span><\/p>\n <\/p>\n IMAGE monday service asset 3\u00a0<\/span><\/p>\n Like any meaningful shift in operations, adopting AI for inventory management comes with a few hurdles. But most of these are practical rather than permanent. Here are some common sticking points you can address early on.\u00a0<\/span><\/p>\n Getting started with AI can seem like a heavy lift. There\u2019s often a perception that it requires a full tech overhaul or a long, complex rollout. In reality, the investment is more about clarity than cost \u2014 choosing the right tool, setting clear goals, and making sure the data is ready. When those pieces are in place, adoption moves faster, and the return tends to show up quickly.<\/span><\/p>\n AI systems rely on access to large volumes of operational data, which makes<\/span> security and integrity<\/span><\/a> top-of-mind for any enterprise. When inventory platforms connect across departments, vendors, and regions, the stakes are higher, especially when customer information, supplier terms, or pricing data is involved.\u00a0<\/span><\/p>\n <\/p>\n According to monday.com\u2019s world of work report, <\/span>52% of larger organizations<\/span><\/a> still don\u2019t fully trust the safety and security of AI systems. Even among smaller businesses, <\/span>23% cite data integrity or security risks<\/span><\/a> as a reason they haven\u2019t yet adopted AI. The concern is valid, but it\u2019s not a dead end. With the right governance, access controls, and vendor transparency, it\u2019s possible to deploy AI without compromising the trust or compliance standards enterprises depend on.<\/span><\/p>\n AI tools need consistent, well-structured data to work properly. But in many organizations, inventory data is spread across systems that simply weren’t built to talk to each other.\u00a0<\/span><\/p>\n <\/p>\n Fixing these incomplete records and mismatched formats often starts with small steps: aligning data sources, cleaning up inputs, and connecting systems through APIs or middleware. Once the flow is reliable, AI becomes much easier to scale and trust.\u00a0<\/span><\/p>\n Even as AI adoption accelerates, many teams still lack the confidence or training to use it effectively. The monday.com world of work report reveals that <\/span>adoption sits at 69%<\/span><\/a> in supply chain and logistics, for example, but drops to just 53% in operations \u2014 often the teams that would benefit most.\u00a0<\/span><\/p>\n <\/p>\n Part of the hesitation comes from uncertainty: 33% of Gen Z workers and nearly a third of millennials and Gen X worry AI could put parts of their jobs at risk. Among enterprise companies, 45% report no AI usage, suggesting skills and mindset are holding things back. Bridging this gap means investing in intuitive tools and training that makes AI feel like a support system, not a threat.\u00a0<\/span><\/p>\n Rolling out AI means asking people to rethink how they work. The shift can meet real friction, especially in large organizations where change tends to move slowly. Our world of work report found that while 45% of senior leaders believe change is handled well, only 23% of individual contributors agree.\u00a0<\/span><\/p>\n <\/p>\n This disconnect can stall adoption before it starts. Resistance usually isn\u2019t about the technology itself; it\u2019s about unclear expectations and a lack of involvement. Conversely, when change is introduced with transparency, context, and support, teams are far more likely to get on board.<\/span><\/p>\n Inventory challenges look different across industries, but AI is flexible enough to adapt to any use case. Here\u2019s what AI in <\/span>inventory management<\/span><\/a> looks like in 7 real-world scenarios.\u00a0<\/span><\/p>\n AI helps<\/span> manufacturers<\/span><\/a> predict when they’ll need fresh materials, flags supply risks early, and adjust purchasing based on production schedules. It’s a key tool for keeping assembly lines moving without piling up excess stock.<\/span><\/p>\n In retail, AI supports smarter stocking decisions and keeps inventory aligned with <\/span>customer demand<\/span><\/a>. It also helps retailers shift products between stores or warehouses before stockouts or overstocking can cause problems.<\/span><\/p>\n Hospitals and clinics use AI to manage critical inventory like medications, equipment, and PPE. Tracking usage patterns and expiration dates makes it easier to avoid shortages without wasting valuable resources.<\/span><\/p>\n AI brings much-needed visibility to automotive inventory by predicting which parts are most likely to be needed and when. This intel reduces downtime and keeps dealerships and service centers from tying up capital in unnecessary inventory.<\/span><\/p>\n In distribution centers, AI improves inventory turnover by identifying slow-moving products and optimizing storage layouts. It also enables teams to rebalance their stock between locations based on shifting regional demand.<\/span><\/p>\n Perishable goods add extra pressure to <\/span>inventory management<\/span><\/a>. AI tracks shelf life, predicts spoilage risks, and times replenishment more accurately \u2014 all of which result in less waste and more reliable supply chains.\u00a0<\/span><\/p>\n Construction teams<\/span><\/a> use AI to manage materials and heavy equipment across job sites. Forecasting usage needs against project timelines reduces delays and cuts down on the costs of storing unused materials.<\/span><\/p>\n Choosing the right AI tool depends on how complex your inventory needs are, how your teams work, and how much flexibility you want as your operations grow. Below are 5 platforms worth considering.<\/span><\/p>\n Best for<\/b>: Teams that need flexible, AI-powered workflows across inventory, support, and operations.<\/span><\/p>\n <\/p>\n IMAGE monday service asset 7\u00a0<\/span><\/p>\n <\/p>\n monday service<\/span><\/a> supports inventory workflows through customizable boards,<\/span> AI ticketing<\/span><\/a>, and cross-team collaboration, all in one intuitive platform. Its AI capabilities automate routine tasks like restocking triggers, issue routing, and categorization without the need for custom code.<\/span><\/p>\n <\/p>\n Key features<\/b>:<\/span><\/p>\n <\/p>\n <\/p>\n Pricing<\/b>: Starts at $26\/seat\/month\u00a0<\/span><\/p>\n <\/p>\n CTA<\/span><\/p>\n Best for<\/b>: Large enterprises needing full ERP integration with inventory control.<\/span><\/p>\n <\/p>\n NetSuite offers a robust, cloud-based ERP system with built-in inventory management. It uses AI to support demand planning, cycle counting, and supply chain automation.<\/span><\/p>\n <\/p>\n Key features<\/b>:<\/span><\/p>\n <\/p>\n <\/p>\n Pricing<\/b>: NetSuite platform license pricing is based on company size and configuration.<\/span><\/p>\nWhat is AI in inventory management?\u00a0<\/span><\/h2>\n
How to use AI for inventory management<\/span><\/h3>\n
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What are the benefits of AI in inventory management?\u00a0<\/span><\/h2>\n
Higher inventory accuracy\u00a0<\/span><\/h3>\n
Real-time inventory updates boost customer experiences\u00a0<\/span><\/h3>\n
Reduced costs through smart inventory holding\u00a0<\/span><\/h3>\n
Enhanced scalability\u00a0<\/span><\/h3>\n
Efficient resource allocation\u00a0<\/span><\/h3>\n
What are the challenges of AI in inventory management?\u00a0<\/span><\/h2>\n
Initial investment\u00a0<\/span><\/h3>\n
Potential data security concerns<\/span><\/h3>\n
Fragmented data quality and integration issues\u00a0<\/span><\/h3>\n
Common skill gaps<\/span><\/h3>\n
Pervasive resistance to change\u00a0<\/span><\/h3>\n
7 real-world applications of AI in inventory management\u00a0<\/span><\/h2>\n
Manufacturing\u00a0<\/span><\/h3>\n
Retail and e-commerce<\/span><\/h3>\n
Healthcare<\/span><\/h3>\n
Automotive and spare parts\u00a0<\/span><\/h3>\n
Wholesale and distribution\u00a0<\/span><\/h3>\n
Food and beverage<\/span><\/h3>\n
Construction\u00a0<\/span><\/h3>\n
5 AI tools for inventory management\u00a0<\/span><\/h2>\n
1. monday service\u00a0<\/span><\/h3>\n
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2. Oracle NetSuite<\/span><\/h3>\n
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3. SAP Integrated Business Planning<\/span><\/h3>\n