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Over the past few years, generative AI has transitioned from a futurist trend to a present business imperative. According to McKinsey’s 2025 State of AI survey, 78% of organizations now use AI in at least one business function, with 71% regularly deploying generative AI (gen AI).
Retailers, in particular, are leaning into this new technology. Gen AI adoption has surged in marketing, product development, and customer service functions where it excels in automation, personalization, and demand forecasting for immediate, measurable value.
While most companies aren’t yet seeing significant profits from generative AI, those making real changes, like updating and optimizing workflows, are starting to see financial benefits.
The retail industry has moved past the experimentation phase to using AI-driven retail management systems (RMS), accelerating broader usage. Companies that have adopted AI for one or two business functions are looking for ways to scale this technology organization-wide.
AI’s impact on retail can be felt across nearly every workflow, from automating back-end operations to delivering a highly curated shopping experience. AI solutions streamline retail interactions with customers across all digital touchpoints; on the store floor, AI helps businesses better anticipate consumer demand, optimize inventory displays, and provide better recommendations.
With new solutions like Epicor Retail Management, retailers can access data in-store, online, and via CRM — combined and in real-time — to efficiently streamline internal processes.
Retailers embracing AI-driven solutions are uncovering new advantages that go far beyond data and process automation:
Although the potential in retail is immense, implementing AI has pros and cons. Some common considerations include:
With vast amounts of data at its fingertips, AI can transform the retail customer experience, delivering real-time insights for refined messaging, better customer segmentation, higher-converting personalization, and increased sales.
Armed with AI, retailers can sift through customer behavior patterns, browsing histories, purchasing decisions, and social media activity to help them better understand their audience.
By going beyond what business analysts alone can achieve, this sophisticated insight helps retailers develop more effective marketing strategies with higher-retention loyalty programs.
Generative AI tools from Epicor, like Predictive Analytics software, help retailers quickly understand customer purchasing behavior and optimize targeting. This means the right promotions can reach the right customers at the right moment, not months, or even minutes, too late.
AI’s ability to drive operational efficiency in retail is another primary benefit. Retailers are increasingly turning to AI to streamline supply chains, improve inventory management, and automate routine customer service tasks. These improvements reduce costs and enable retailers to provide better service with faster response times.
One of the most powerful applications of AI in retail is demand forecasting. AI-driven predictive analytics can analyze historical data and real-time trends to accurately predict future demand, minimizing stockouts and the burden of excess inventory.
AI-powered inventory management tools from Epicor help businesses forecast demand more accurately, automate restocking, and reduce waste—all with minimal disruption or need for extensive retraining.
Managing supply chains is often the costliest and most complex part of retail operations. AI can optimize logistics by providing timely insights into shipping routes, delivery schedules, and fluctuating inventory levels. With to-the-moment data, retailers can adjust orders, suppliers, and other levers to swiftly pivot amid impending disruptions or changing market conditions.
AI-powered platforms, like the Epicor Predictive Inventory Assistant, help automate core supply chain functions so businesses can make smarter decisions regarding restocking, shipping, and order fulfillment.
AI-driven chatbots and virtual assistants are becoming standard, essential tools for automating customer service. These assistants help retailers provide quick, round-the-clock responses to customer inquiries, reducing the workload on human customer service teams and helping customers get the help they need when they need it.
In retail environments, AI-powered virtual assistants can handle common customer queries related to product availability, order status, return details, and store locations, freeing up dedicated agents to tackle more complex issues.
AI technology has numerous applications across the retail sector, from inventory management and pricing optimization to fraud detection and security. Here’s a look at some of the most exciting AI use cases in retail today.
Pricing is a critical factor in driving profitability. AI helps retailers optimize pricing strategies by analyzing numerous data points, including competitor pricing, customer demand, market conditions, supply chain trends, and historical sales. Then, retailers can also use AI to automatically adjust prices in real-time to maximize revenue and competitiveness.
As one common household name example, retail giant Walmart uses AI to monitor and adjust pricing strategies daily.
AI’s ability to analyze large datasets and identify patterns makes it a powerful tool for detecting fraud. Retailers can monitor transactions in real-time, flagging suspicious activities and preventing potential fraud before it occurs. AI systems can learn from past fraud incidents, continually improving their ability to detect emerging threats.
At Epicor, our Eagle RMS and POS solution enables retailers to easily monitor all transactions, identify discrepancies, and quickly root out suspicious activity across all POS transactions, including voids, suspended sales, and training mode purchases. Data is mapped in the Epicor Compass tool and can be synced with data or third-party loss prevention companies.
AI is constantly evolving, and its retail applications are expanding in exciting ways. As generative AI tools continue to develop, retailers can expect more innovative solutions, increased automation, and new opportunities for business growth.
The retail industry is seeing an influx of generative AI technologies, which can create everything from personalized product recommendations to customer service scripts. Beyond better ad targeting, AI can even design products based on customer data.
As AI continues to infiltrate the retail industry, it's natural to wonder how it will impact the labor market. While some roles may be automated, AI is also creating new job opportunities in areas like AI management, data analysis, AI governance, and customer experience design.
The demand for workers who can integrate and manage AI tools is on the rise, as companies need skilled professionals to implement and monitor these solutions. In a recent review of U.S. job listings on Glassdoor, over 81,000 posts requested or required experience with AI tools. “AI” was included more commonly in job descriptions than other popular work terms like “spreadsheet” (57,000), “ERP” (45,000), or “Salesforce” (30,000).
With the rise of AI in retail, ethical concerns have surfaced. Data privacy, algorithmic bias, and transparency are top of mind for consumers and businesses. Retailers must be transparent about how they use AI and work to ensure that the systems they implement are free from biases that could harm customers or skew decisions.
Retailers also need to adopt best practices for ethical AI use, focusing on fairness, transparency, and privacy to sustain customer trust. Additionally, human oversight is needed. There are many examples of AI chat agents giving inaccurate information about pricing or service terms, leading to angry customers and high-profile fallout.
As highlighted earlier, AI offers incredible potential, but adoption isn’t always straightforward. Here’s how to overcome common obstacles and make AI adoption as seamless as possible.
Before diving into AI adoption, retailers should carefully assess their existing infrastructure and workflows. Integrating AI into legacy systems requires careful planning, a clear understanding of attainable business goals, and the right technology partner.
Retailers need to invest in clean, structured data and ensure that their systems can support AI tools that require large volumes of real-time data.
AI is only as effective as the data it’s given. To maximize the impact of AI, retailers must foster a data-driven culture where teams across departments value accurate, organized, consistent data. This means ensuring that all systems can communicate with each other, with teams working off a “single source of truth” that enables AI to deliver its full potential.
Tools like the Epicor Enterprise Content Management (ECM) system help retailers centralize data across diverse platforms, making it easier to access and share information. This solid foundation improves decision-making speed, efficiency, and teamwork.
Retailers may encounter resistance from employees due to difficulty in learning and implementing new technologies or just general fear of the unknown.
To overcome these barriers, it’s essential to have leadership that champions AI adoption, provides clear communication about its benefits, and offers adequate staff training.
Best Practices for Successful AI Adoption:
The evolution of retail is unfolding hand in hand with the growth of AI, transforming how retailers operate, manage supply chains, and interact with customers. Businesses can streamline workflow and elevate the customer experience in ways unthinkable even a decade ago. Embracing these capabilities now lays the groundwork for long-term growth.
Ready to explore how generative AI can transform your retail business? Learn more about Epicor AI-driven solutions and discover how we can help you optimize operations, improve customer experiences, and drive smarter decision-making.
