Gen-AI in Retail: How Retailers Can Elevate Shopping Experience

Dan O'Malley

Expert in 5G

What we are experiencing these days is far different from the late 90s. This 21st century is about modernizing our lifestyle, especially in retail. How people shop, what they expect, and how they interact with brands is evolving. And Gen-AI in retail is a key factor in this change.

Statista estimates the current Gen-AI market may reach $62.7B in 2025. It will gain a market volume of $356.05B by 2030 at an annual growth rate of 41.5% ¹. But what does that mean for businesses and shoppers?

Well, Gen-AI creates new data – like text, images, or recommendations – to solve real-world retail challenges. It should be in every retail store as it creates something new, tailored for its users. You may think of it as a digital artist or writer who learns from existing information and then produces original content.

There is a lot more besides this! In this blog, I want to explore the changing retail experience with some retailer examples using different Gen-AI models. These models can improve customer service, personalize marketing, and even optimize the supply chain.

So, start reading! Wait, I have something exciting for you at the end of the blog. Don’t miss it.

Table of Contents

What is Gen-AI? A Primer for Retailers

It is a contracted form of Generative Artificial Intelligence or Generative AI. In short, it is a type of artificial intelligence that creates new content, such as code, text, images, 3D designs, or music, based on patterns learned from existing data.

Traditional AI focuses on analyzing data and making decisions. However, Generative AI produces original material by identifying and imitating the functionalities, patterns, and structures within its training data. This technology powers applications like chatbots, image video generators, and personalized content creation tools.

For example, tools like ChatGPT generate human-like text, DALL-E creates realistic images from text prompts, and Amazon Bedrock generates dynamic product descriptions ².

Technically, Gen-AI works by training large datasets to understand relationships between inputs and outputs. This allows it to generate coherent, contextually relevant results, such as personalized product descriptions, virtual try-on experiences, or dynamic pricing strategies.

Regular AI might tell retailers what their customers bought last week. However, generative AI can help them imagine what those customers might want to buy next month. It will create the perfect marketing message to get them excited about it. It can even generate new product ideas based on what AI knows about current buying trends.

Benefits of Gen-AI in Retail: Why Retailers Should Integrate It

So, I’ve talked about what Generative AI is and what it can do. Now, let’s talk about the why – why should you, as a retailer, care about this technology?

The short answer: it can significantly improve your bottom line and enhance your customer relationships. Let’s have a look at the benefits of using Gen-AI in the retail industry:

Hyper-Personalized Shopping Experiences

I consider one of the biggest benefits of Gen-AI to be the enhanced customer experience. It makes shopping more personalized, engaging, and convenient. It analyzes customer data (browsing history, purchase behavior) to deliver customized recommendations and offers.

In return, it increases cross-selling and customer satisfaction. Also, Gen-AI can adjust prices (if you want to) in real-time based on demand, competitor activity, and customer experience.

Enhanced Customer Engagement

Tools with Gen-AI integration create immersive, interactive experiences. For instance, some tools (see the latter part of this blog post) use Gen-AI to simulate makeup looks and reduce return rates. Some others provide instant, 24/7 support and resolve queries faster.

These are not just nice-to-haves; they are becoming expected. This way, retailers can build stronger relationships with their customers. Also, they can increase their loyalty and keep them returning for more. After all, satisfied customers lead to better revenue.

Improved Operational Efficiency & Productivity

Generative AI can automate many time-consuming tasks. For example, it automatically generates product descriptions, ad copy, and social media posts. So, your human employees get more time for strategic initiatives by not doing repetitive tasks. Some initiatives include building relationships with key customers, developing new products, and exploring new markets.

Gen-AI models can predict demand trends and manage risks. So, retailers can maintain optimal stock levels, optimize supply chains, reduce waste, and ensure inventory products for customers when needed.

AI-Generated Marketing Content

As I said, Gen-AI can generate things automatically to save more time. Suppose you need an SEO-friendly product description. You can ask ChatGPT to generate it, even in multiple languages.

Similarly, you can get AI-crafted personalized ads to market your products. Some models can draw images and curate videos with a particular product. In these ways, Generative AI reduces manual labor and effort and ensures consistency.

More Sales, More Revenues

I’ve also observed that Generative AI can drive sales and revenue growth significantly. This happens through various means.

Improved product recommendations, targeted marketing campaigns, and optimized pricing strategies benefit retailers and shoppers. This leads to a direct increase in sales and revenue. For example, customers are more likely to purchase products recommended to them based on their preferences.

Innovation & Competitive Advantage

Adopting Generative AI can position retailers as innovators and provide a competitive edge. You’ll be able to offer unique and personalized experiences that your competitors can’t match. This can attract new customers, retain existing ones, and build a strong brand reputation as a forward-thinking retailer.

Top Generative AI Use Cases in Retail: Real-World Examples

Generative AI drives efficiency, reduces costs, and creates seamless customer journeys. Early adopters gain a competitive edge by automating tasks, enhancing personalization, and unlocking creative solutions.

Here are some top use cases, with specific examples you can check out:

Personalized Shopping with Amazon’s Rufus AI Assistant

Amazon is pushing the boundaries of personalized shopping with its Rufus AI assistant. It leverages Amazon’s extensive product catalog, customer reviews, and information across the web to assist users in real-time ³.

Rufus can answer detailed customer questions related to shopping. It provides personalized product recommendations. It even helps customers compare different products side-by-side. And the impact – it has provided higher conversion rates, increased average order value, and improved customer satisfaction.

Rufus is available to all USA customers on the Amazon Shopping app and desktop.

Interactive Virtual Try-On with Sephora's Virtual Artist

Gen AI is used to create innovative visual shopping experiences, such as virtual try-ons (Sephora’s Virtual Artist) and visual search. This app analyzes facial features and lets users see how different products and shades will look on them without physical applications.

Sephora uses augmented reality (AR) and AI technologies to allow customers to virtually “try on” different makeup products using their smartphone cameras ⁴.They can experiment with various shades and styles to find the perfect look before purchasing. This makes online makeup shopping more engaging and reduces the risk of buying the wrong product.

The impact of Sephora on Gen-AI is shown to be notably significant. It reduces return rates for makeup products, increased customer engagement, and higher online sales.

Smarter Product Discovery with Walmart’s Smart Site Search

Gen-AI predicts demand and automates restocking to minimize stockouts or overstock. Walmart has integrated it into its search functionality to enhance the shopping experience ⁵. The generative AI search experience is live on iOS for all customers with the latest version of the Walmart app.

When you search for a product on Walmart’s website, the AI goes beyond simple keyword matching. It understands the intent behind your search query and generates more relevant and personalized results. This makes it easier for customers to find what they are looking for, even if they don’t know the exact name of the product.

The outcomes of Gen-AI in Walmart are increased product discovery, improved search relevance, and higher sales conversion. Plus, it enhances supply chain efficiency and customer experience by predicting demand and streamlining logistics.

AI Chatbots for Enhanced Support with Carrefour’s AI Chatbots

Carrefour is one of the world’s largest retailers. It has implemented AI-powered Chatbots to provide 24/7 customer support ⁶. These chatbots handle a variety of customer inquiries, from product information to order tracking, providing instant responses and support.

As Generative AI powers these apps, they can understand complex questions and provide personalized solutions. Meanwhile, the human staff can simultaneously focus on more complex tasks due to Gen-AI’s automation.

With the chatbots, Carrefour has reduced customer service costs, improved customer satisfaction and response times, and increased agent productivity.

H&M’s Virtual Assistant for AI-driven Styling and Outfit Suggestions

Like Carrefour, H&M has implemented AI-driven customer service solutions to enhance its online and in-store experiences ⁷. Its virtual assistant manages customer queries about product availability, order status, and return policies.

Customers or shoppers get quick and accurate information and responses from this VA. It enhances personalized shopping experiences by analyzing customer preferences.

Other Real-World Examples

eBay ShopBot, an AI-powered chatbot, becomes user-friendly as it offers personalized product discovery via text, voice, or image search ⁸. Then, Shopify Magic generates product descriptions, summarizes app reviews, and automates marketing content ⁹. It saves time for e-commerce businesses while maintaining SEO optimization and brand consistency.

If you want to try a Gen-AI-driven personal styling service, there is also Stitch Fix 10. It combines machine learning (ML) with human stylists to curate clothing boxes. Shoppers get recommendations aligned with their individual preferences and feedback with Stitch Fix.

The North Face uses IBM’s AI platform, Watson, to power its online shopping experience 11. This AI-powered platform suggests relevant products and virtual outfits based on the weather to customers. Again, customers don’t need to scroll endlessly for this facility.

Gen-AI for Retail Branding

Generative AI can tackle common retail challenges that retailers may always need to solve repetitively with manual labor. Here are some examples of how you may understand how good Gen-AI can be for your business:

Product Description Writing

So, I have chosen one of the newest arrival products on Amazon, a household pressure cooker (check link). Then, I asked ChatGPT to write a product description for it by just inserting the product page’s link. Here’s what I got:

Ad Copy Writing

Let’s move into writing an ad copy for another selected product, a headphone on eBay (check link). At this point, I have used another Gen-AI model called QWEN.

Product Image Generation

Suppose you want to generate an image of a product without copying others. Gen-AI can assist in this case, too. I have chosen another Gen-AI model from Google called Gemini.

Then, I added the next prompt:

Product Recommendations

If you are confused (as a shopper) or have difficulty recommending the right product among hundreds of variations, you can get help from Generative AI. This time, I have chosen another Gen-AI model called CoPilot by Microsoft.

Nybsys Sentra Gen-AI: A Retail AI Assistant Redefining Customer Engagement

So, you have seen a couple of examples of the performance or functionalities of Generative AI. Remember, I told you that there’s a surprise waiting for you at the end of the blog? Yes, that is our Nybsys Sentra Gen-AI.

It is an innovative AI worker or assistant designed to transform retail operations by combining real-time communication, GPU-free efficiency, and multimodal capabilities. Showcased at MWC 2025, it addresses key retail challenges while enhancing customer and employee experiences.

Some key features that outsmart Sentra over other Gen-AI models:

Real-Time, GPU-Free AI

Unlike traditional AI systems requiring expensive GPUs, Sentra Gen-AI operates efficiently without them, reducing costs and enabling faster deployment.

Integration with Sentra PTT Systems

Seamlessly connects to Push-to-Talk (PTT) systems, enabling store associates to access AI-driven insights instantly via voice or text.

Multimodal RAG Architecture

Supports text, voice, and video interactions, allowing retailers to create dynamic customer experiences (e.g., virtual try-ons, video-based product demos).

AI-Powered Collaboration

Enhances teamwork by automating tasks like inventory checks, customer queries, and order updates, freeing staff to focus on high-value interactions.

Here are some cases of Nybsys Sentra Gen-AI in retail:

Instant Customer Support

Shoppers can ask questions via chat or voice (e.g., "Where is the nearest store with this item in stock?"), with AI providing real-time answers.
Reduces waiting times and improves satisfaction, like Amazon’s Rufus but with multimodal capabilities.

Inventory and Supply Chain Optimization

Predicts stock levels using historical data and automates reordering, minimizing overstock and stockouts.

Virtual Product Demonstrations

Uses video processing to showcase products (e.g., demonstrating a blender’s features via short clips), bridging the gap between online and in-store experiences.

Employee Productivity

Acts as a "copilot" for store staff, providing instant access to product details, promotions, and compliance guidelines via PTT.

Nybsys is positioned to lead in Gen AI-driven retail CX and operational efficiency, especially as multimodal AI becomes critical for immersive shopping experiences. Retailers leveraging Sentra Gen-AI can stay ahead in personalization, sustainability, and agility.

Frequently Asked Questions

What is generative AI in retail?

Generative AI is artificial intelligence that creates new content (text, images, recommendations) by learning from existing data. In retail, it powers personalized shopping experiences, automates tasks, and optimizes operations.

What are the benefits of generative AI for retailers?

Some common benefits are enhanced customer experience, faster support, cost savings through automation of tasks, and streamlined supply chain and inventory management.

How does Sentra Gen-AI improve customer experience?

Sentra Gen-AI offers dynamic pricing and targeted promotions for personalized shopping. It also offers visual search and virtual assistant services besides instant responses for better customer experience.

Conclusion: The Choice Between CBRS and Private 5G

I hope this discussion on Gen-AI in retail has given you a clearer picture of its potential.

We’ve seen how it’s not just a futuristic axiom but real technology already transforming how retailers operate and customers shop. From Amazon’s personalized shopping assistant to Sephora’s virtual try-on experiences, the examples are becoming more tangible daily.

The benefits are clear: enhanced customer experience, increased sales, improved efficiency, and a competitive edge in a rapidly evolving market. But, like any technology, it is crucial to approach Generative AI with a strategic mindset. Consider the data you need, the expertise required, and the ethical implications.

To stay competitive, retailers must adopt a strategic approach: prioritize high-impact use cases, address ethical considerations, and invest in tools like Nybsys Sentra Gen-AI for GPU-free, scalable solutions.

What are your thoughts on Generative AI in retail? I would love to hear your predictions and see your examples!