Practical Applications of Generative AI in Retail Operations

Transforming Customer Engagement and CRM

One of the most visible and high-impact applications of generative AI is in customer relationship management (CRM). AI enables retailers to more profoundly personalise the customer experience by:

• Analysing purchasing behavior
• Anticipating needs
• Recommending tailored products or services

Take e-commerce, for instance. AI can track browsing and purchasing patterns in real-time to surface complementary products, driving upsell and cross-sell opportunities that feel intuitive rather than pushy.

It also automates time-consuming tasks like email targeting, chatbot responses and social media scheduling. That frees up marketing teams to focus on strategy and creativity, while AI ensures consistency, accuracy and responsiveness at scale.

According to a 2025 Forrester report, 20% of retailers in the US and EMEA are expected to launch customer-facing GenAI tools this year, and 15% already have multiple GenAI deployments live. Whether it’s for customer support, loyalty programmes or content generation, the shift from experimentation to execution is already underway.

Enhancing Inventory and Supply Chain Management

AI’s ability to analyse real-time demand data and generate predictive insights is transforming inventory and supply chain operations. Retailers using AI-driven forecasting tools can:

• Predict demand with greater accuracy
• Minimise stockouts and overstock situations
• Optimise delivery routes and lead times

These gains aren’t just theoretical. Machine learning algorithms are already identifying seasonal patterns, responding to external factors like weather or events, and fine-tuning inventory levels in real time. The result? Lower holding costs and better product availability.

Retailers are also starting to experiment with dynamic pricing and AI-assisted replenishment. Using generative AI, businesses can simulate various demand scenarios and adjust strategies accordingly, often faster and more accurately than humans alone.

Empowering Store Teams and Frontline Staff

Generative AI is also revolutionising how work gets done in physical stores. Intelligent scheduling tools now use historical sales data, footfall patterns and employee skill sets to improve in-store communication that leads to smarter rosters and lower stress by preventing scheduling conflicts and improving work-life balance.

Beyond that, retailers using Cegid Retail Live Store are equipping store staff with AI-powered apps that provide instant access to customer profiles, purchase histories and preferences. A sales advisor, for example, can quickly see what size a customer usually buys or which product they liked but didn’t purchase, turning a casual interaction into a conversion opportunity. The result is more empowered employees, more satisfied customers and a stronger bottom line.

Driving Innovation Across Retail Functions

As store formats evolve and omnichannel strategies mature, generative AI is playing a broader role in retail innovation. A 2024 IDC report shows that 63.8% of retailers are investing in GenAI, particularly for use cases like:

• Natural language search and discovery
• Content generation for chatbots and product descriptions
• Knowledge base tools for staff training and onboarding

These innovations are helping retailers accelerate time to market, streamline internal operations and differentiate the customer experience. As Ananda Chakravarty from IDC Retail Insights puts it, “GenAI is taking the retail industry by storm; what we think is an innovative use case now will be routine in less than 18 months.”

Also worth reading: 10 Questions to Help Assess Your Retail Business’ Digital Maturity

Real-Time Responsiveness and Smarter Decision-Making

Retail success increasingly hinges on agility and that’s where GenAI really shines. With tools like Cegid’s real-time analytics platform, employees can input natural language queries and receive dynamic, visual insights to improve task management to ensure efficient inventory management and brand compliance.

This level of responsiveness is particularly critical when managing in-store promotions and high-return items

Dynamic assortments across regions or channels

Instead of waiting for end-of-week reports, store managers and HQ teams can course-correct on the fly, ultimately improving profitability and customer satisfaction.

Cegid’s research reinforces the trend: 51% of UK retail leaders see AI as the main driver of growth for 2025. In a high-stakes, low-margin environment, the ability to act on real-time insights is a game-changer.

A Strategic Imperative for 2025 and Beyond

AI is no longer just about automation—it’s about augmentation. It’s a co-pilot for marketers, a personal assistant for store staff, and a strategist for supply chain leaders.

Retailers who embed generative AI across the value chain, from product development to customer service, will not only drive efficiencies but also unlock new growth models. Whether it’s through better personalisation, smarter pricing or more engaging in-store experiences, AI is enabling innovation at every level.

As Emmanuel Vivier, co-founder of the Hub Institute, recently said, “Artificial intelligence has seen incredible acceleration over the past 18 months with the explosion of generative AI. The opportunities offered in retail were already numerous, but they are going to multiply even further.”

Final Thought: The Retail of Tomorrow Is Happening Now

Generative AI isn’t just a tool for automation, it’s a strategic enabler of responsive, human-centric and efficient retail operations. The organisations that embrace it now are not just keeping up, they’re jumping ahead.

Whether you’re a large enterprise or a niche brand, 2025 is the year to move from pilots to full-scale deployments. Because the future of retail isn’t just powered by AI—it is AI.