GenAI at Retail: New Technology Upgrades for Inventory and Demand Forecasting

Generative artificial intelligence (GenAI) is revolutionizing retail, providing innovative solutions to real-world challenges like inventory management. In this report, PYMNTS Intelligence examines critical business problems faced by retailers — such as stock shortages, overproduction and shifting consumer demand. It illustrates how GenAI is addressing these matters with insight and precision. By fine-tuning demand forecasting, streamlining stock levels and enabling hyperpersonalized shopping experiences, GenAI is helping retailers unlock efficiency, boost sales and strengthen customer loyalty. Highlighting actionable solutions provided by companies like Alloy.ai, Hypersonix and others, we offer a glimpse at how GenAI is not just changing the industry but also solving some of its most pressing challenges.

The Heart of the Matter: Managing Inventory and Keeping Up With Shoppers’ Demands

From Data to Action: How GenAI Tools Run the Retail Warehouse

The Connection Between Personalization and Inventory Management

Message to the CFO: The ROI Adds Up

The Heart of the Matter: Managing Inventory and Keeping Up With Shoppers’ Demands

A lack of real-time inventory visibility and difficulties in accurately predicting shopper demand often result in overproduction, excess stock or critical shortages — all of which have a direct and detrimental impact on profitability.

Manual inventory processes are no longer sufficient.

Before we get into GenAI, let’s look at what’s at stake for current inventory management systems and processes. The question “Is this product in stock?” is at the heart of daily decision-making for retailers, whether at large chains like Walmart or smaller, local stores. The answer can mean the difference between making or losing a sale. Multiply this question by thousands of transactions across physical and eCommerce channels, and the impact on revenue becomes crucial, depending on the retailer’s scale.

84%

of retail decision-makers say maintaining real-time visibility of stock levels is challenging.

Without accurate data on inventory levels, businesses face two critical risks. Overestimating demand can lead to excessive stock, tying up valuable capital, increasing storage costs and reducing operational flexibility. On the other hand, underestimating demand due to poor inventory visibility results in shortages of high-demand items, leading to lost sales and, more importantly, weakened customer loyalty — an issue with long-term repercussions.

Product availability ranks as the top factor influencing where shoppers choose to buy, while out-of-stock items consistently drive customers to leave stores empty-handed and online shopping carts abandoned. This challenge becomes even more complex when coordinating inventory across multiple sales channels. However, many retailers still rely on outdated practices: 34% of supply chain executives use manual inventory management, and 45% report that lack of real-time visibility is their primary barrier to effective inventory coordination.

To stay competitive, real-time inventory visibility is no longer optional. Retailers must minimize the costs associated with overstock — such as warehousing, security and insurance — while also ensuring they can meet consumer demand. Inventory visibility is just one piece of the puzzle, though. The ability to anticipate changes in consumer preferences and then act on them is now equally vital for effective inventory management in today’s dynamic retail landscape.

Accurate demand forecasting is the key to boosting sales.

If the first critical question for retail decision-makers is whether an item is in stock, then the second, equally essential question is “How many items will we need next week, next month or next season?” Answering this is one of the most complex challenges retailers face. A recent study reveals that 36% of retail executives cite sales forecasting as a top challenge, closely followed by real-time reporting and analytics on fulfillment, at 35%.

Predicting inventory demand over the long term without real-time visibility into stock levels and consumer demand patterns is a recipe for inefficiency and missed sales. Basic access to customer data is not enough if it is not both real-time and accurate. Retailers report that their biggest hurdles to improving supply chain efficiency include rapidly shifting consumer demand volatility (55%) and an inaccurate understanding of customer-specific needs (43%).

This is where GenAI emerges as a transformative tool. By analyzing vast, complex datasets — including historical sales trends, economic indicators and even weather patterns — GenAI can produce precise demand forecasts. With the right tools in place, retailers can move beyond guesswork, gaining actionable insights into fluctuations in consumer demand. This empowers them to plan inventory levels more effectively, ensuring they are ready to meet customer needs without overstocking or understocking.

From Data to Action: How GenAI Tools Run the Retail Warehouse

GenAI is transforming inventory management by enabling accurate demand forecasting, optimized stock levels and streamlined replenishment processes. Solutions like Alloy.ai, Hypersonix and Maiven provide real-time tools that empower retailers to make data-driven decisions and respond swiftly to market changes.

GenAI is offering real solutions — in real time.

57%

of retail, consumer packaged goods and wholesale executives plan to invest in GenAI technologies over the next three to five years.

Beyond the buzz, GenAI offers specific applications for inventory management. By analyzing customer data, sales patterns and market trends, this technology can predict future demand for specific products, empowering managers to make informed stocking decisions well in advance — or even in real time.

GenAI also enhances the precision of inventory allocation by analyzing demand at the store level. Floor and warehouse managers gain access to real-time insights on stock levels, along with suggestions to adjust orders based on evolving sales patterns. Some of the advanced tools highlighted below take this a step further by automating order adjustments dynamically, preventing overstock or understock scenarios and replacing time-consuming manual processes with automated efficiency.

Companies to Watch

GenAI for Inventory Management

Household names like Walmart, H&M, Zara and Zalando are already using GenAI to improve inventory management and better predict consumer demand. Here are some notable examples:

H&M

H&M, the Swedish fashion retailer, has implemented AI-powered tools to analyze data from search engines and blogs, enabling precise demand forecasting and trend analysis. This approach allows H&M to respond swiftly to market shifts, minimize lead times and make data-driven decisions on purchasing and inventory placement. The company’s AI systems also optimize its supply chain by tracking shipments, monitoring real-time inventory levels and identifying potential bottlenecks, resulting in improved operational efficiency and reduced costs. Moreover, H&M’s AI-driven demand forecasting contributes to its sustainability efforts by reducing waste and minimizing unsold items.

Walmart

Walmart has partnered with Google Cloud to develop an AI-driven supply chain management platform that integrates data from various sources, providing a comprehensive view of its entire supply chain. This system enables accurate demand prediction and inventory level optimization, offering real-time visibility into stock levels and allowing for quick adjustments based on demand fluctuations. Walmart’s AI capabilities extend to anticipating demand cycles, particularly during peak or unexpected events, and simulating scenarios for major shopping events like Black Friday. By leveraging AI to balance its network and place inventory strategically, Walmart has significantly enhanced its ability to meet customer demand efficiently.

Not all retailers have the developers, time or expertise to create in-house AI solutions, however. Smaller retailers can partner with specialized software providers offering predictive and GenAI features to tackle challenges in inventory, forecasting and supply chain management. Below, PYMNTS Intelligence spotlights a list of companies providing innovative solutions:

Alloy.ai

Alloy.ai delivers real-time visibility and actionable insights, enabling manufacturers, distributors and retailers to optimize inventory, improve demand forecasting and enhance decision-making. One of its standout features is its user-friendly dashboards, which allow decision-makers to quickly identify potential problems and act on them. The platform collects and analyzes point-of-sale (POS) data from retail and eCommerce channels, synchronizing it with inventory and supply chain data from ERP systems. Alloy.ai not only identifies sales opportunities and revenue growth potential but also quantifies how many sales a company may be losing due to inventory inefficiencies.

Hypersonix

Like Alloy.ai, Hypersonix offers a GenAI platform designed to analyze consumer trends, sales data and inventory levels to provide actionable insights in real time. Its no-code integration makes it easy to implement within existing systems. Beyond inventory management and demand forecasting, Hypersonix also delivers intelligence for pricing and promotions, representing a comprehensive tool set for retail optimization.

Mojix

Mojix provides inventory management solutions across industries and recently introduced Maiven, a GenAI-powered tool specifically tailored for retail. Like Alloy.ai, Maiven detects anomalies in stock levels, forecasts future demand and predicts the economic impact of sales fluctuations. Additionally, it offers recommendations to transfer or replenish stock, helping retailers boost revenue.

The Connection Between Personalization and Inventory Management

If managing inventory is retail business managers’ top priority, delivering personalized shopping experiences is a close second. Offering consumers exactly what they want can drive sales, but it also demands precise control over stock levels to ensure a seamless and satisfying customer experience. Personalized offers fall flat without available inventory.

Hyperpersonalization is the holy grail for retailers.

Since the dawn of the internet, the ability to address individual needs and preferences has been a game-changer for marketers and retailers. It turned companies like Google, Meta and Amazon into giants. While targeted ads became the norm, the delivery of truly personalized content for each consumer has remained an elusive goal — until now.

GenAI is ushering in a new era of hyperpersonalized content. This technology not only simplifies the creation of individualized experiences but also aligns with growing consumer demand and executive priorities. According to a recent Nvidia survey, 86% of retailers aim to leverage GenAI to enhance customer experiences — a figure that rises to 100% among C-suite executives. Top use cases include personalized product recommendations and branded virtual assistants, reflecting the technology’s broad potential.

78%

of retailers that plan to spend more than $5M on GenAI identified personalized recommendations as a top opportunity.

In fact, 41% of American shoppers now expect brands to use GenAI, and 58% report that it has already improved their online shopping experience. In this new era of personalization, access to real-time data on what consumers are viewing, clicking and purchasing is nonnegotiable. Such insights empower retailers to forecast demand with precision and adjust inventories in real time. A robust GenAI tool can predict demand at the item level, providing actionable intelligence to streamline inventory management, boost sales and reduce operational costs.

Companies to Watch

GenAI for Shopping Personalization

Many leading companies are leveraging GenAI to produce personalized content that drives sales. In addition to industry giants like Amazon and Walmart, innovators such as Stitch Fix showcase GenAI’s personalization potential:

Stitch Fix

Stitch Fix stands out as a prime example of a GenAI-powered company built entirely around personalization. With nearly 4.5 billion data points at its disposal, Stitch Fix uses customer-provided feedback and preferences to deliver hyperpersonalized style recommendations via email. Its AI-driven approach to fashion not only ensures customers receive tailored suggestions but also highlights the creative potential of GenAI in the retail sector.

As with inventory management, PYMNTS Intelligence has also identified several innovative companies offering GenAI solutions tailored to smaller businesses seeking to enhance their personalization efforts, as follows:

Syte

Syte aims to make product discovery seamless. With its proprietary visual AI engine and GenAI capabilities, users can simply upload a picture, and Syte will identify where to find the item or suggest alternatives based on individual preferences. In addition to improving product discoverability, Syte streamlines back-end merchandising operations, helping retailers optimize both customer experiences and inventory management.

First Insight

First Insight takes a unique approach by focusing on designing the right product rather than just recommending existing ones. With its InsightIQ Sentiment platform, the company collects and analyzes customer feedback to provide retailers with actionable insights on which products have the most potential and which are underperforming. By uncovering consumer sentiment on various items, First Insight also helps brands identify emerging trends, enabling smarter product development and design decisions.

Route

Retail brands work with Route to improve their online shopping experience by providing them with solutions for package tracking, shipping protection and carbon neutral shipping. Route also offers tools for customer engagement, such as AI-powered product recommendations that are intended to help businesses boost their sales.

Message to the CFO: The ROI Adds Up

PYMNTS Intelligence has spent more than a year analyzing the return on investment (ROI) that GenAI delivers to middle-market firms, and the findings are compelling. The trend suggests that the more impactful the tasks assigned to GenAI, the greater the ROI for businesses. This creates a virtuous circle: Companies achieving higher ROI through GenAI are motivated to expand its use, gradually transitioning from routine tasks to more transformative, high-impact applications.

This trend is particularly relevant to retailers looking to use GenAI for inventory management and content personalization. In a recent PYMNTS Intelligence report, companies reported significant cost reductions in inventory management and the successful automation of workflows using real-time GenAI monitoring systems. While these higher-impact applications require deeper workflow integration, they consistently yield higher ROI, making them a valuable investment for businesses seeking long-term efficiency and profitability.

88%

Share of CFOs using GenAI for real-time, automated responses to customers — the leading medium-impact task

Retailers are already harnessing GenAI across various departments and reporting positive ROI, signaling that this technology is more than a passing trend and is instead becoming a cornerstone of modern retail operations. The trajectory is clear: GenAI is here to stay. The real question is not if but when and how retailers will adopt it to optimize processes and stay ahead in an increasingly competitive landscape.