How Generative AI Is Impacting Online Retail

More than 50% of online purchases last Black Friday were made on mobile devices, and AI-powered chatbots (generative AI) are said to have contributed to the journey to these purchases. 

And that is just a tiny glimpse into what’s ahead of us. The global market for generative AI in eCommerce is projected to reach $2.1 billion by 2032, with an annual growth rate of 14.9% — and we’re already in the eye of the AI storm. 

Retail managers need to be able to weather the storm and take advantage of the momentum to push their brands ahead of the competition. 

In this post, we look at the four main eCom business elements where generative AI is making the most impact and what you can do now to stay ahead. 

But first, here’s a little recap of the difference between generative AI, LLMs, and machine learning. 

1. Online Retail Content Creation 

The most obvious place where generative AI is having an impact is in content creation. This includes product descriptions, marketing or promotional materials, and visual content creations like product photos and videos. 

The growth in generative AI visual content has been a top talking point these last few months, and considering the quick growth in this tech, it is not hard to see why. Tools like Pebblely, Pixelcut, Adobe’s Firefly, or Claid.ai can all help online retailers create diverse and engaging product visuals, complementing traditional photography with additional creative options.

In terms of content, there is plenty of innovation to go around.

Built-in marketplace generative AI (like eBay’s magical listing tool) is now pretty common, and many retailers are combining ChatGPT and other generative AI tools with automation to help write bulk product descriptions.  

Here’s a prompt example for the latter: 

• You are an expert eCommerce copywriter trained to create on-point product descriptions for [Brand Name]. Focus on [product category] and highlight key features, benefits, and unique selling points that match [Brand Name]'s current format, style, and voice. Generate engaging, SEO-friendly product descriptions aimed at these types of shoppers: [target audience]. Use a [friendly/professional/luxury] tone, include sensory language, address pain points, and finish with a CTA. Keep it between [100–150 words] and incorporate relevant keywords provided, but make sure they fit naturally. 

So, what now for your store? 

There is no denying that adopting AI tools for content generation can streamline product listing processes, enhance accuracy, and free up resources for other essential tasks. 

However, like with any new technology, you must tread carefully. Brands like Pentagram, Shopify, and Coca-Cola have all faced significant backlash for using generative AI in marketing and creative projects that consumers saw as invasive, impersonal, or cold. 

In short, your store’s team will still need a human hand on the wheel. But when done right, you could automate many of your content tasks. Here are just a few examples: 

• Create multiple product image variations  
• Autodraft promotional emails from other content   
• Generate social media captions for new product launches 
• Double-check brand tone across all content channels and internal teams 
• Auto-generate product descriptions 

2. Customer Support and Shopper Interactions

Another big area in which generative AI is impacting online retail is through support and interactions. According to Gartner and Microsoft reports: 

• A whopping 80% of retail businesses are either already using AI chatbots or planning to implement them soon.

With generative AI, retailers are rapidly creating and optimizing chatbots, AI agents, and virtual assistants to provide instant, personalized responses to shopper inquiries. These agents also help with order tracking and even recommend particular products. 

However, generative AI is becoming far more impactful when combined with other technologies. 

For instance, with online merchandising, product recommendations are typically driven by machine learning (ML) and predictive AI. Adding generative AI can enhance recommendations by: 

• Creating personalized content around them, like writing custom product descriptions or generating tailored marketing messages that feature recommended products.

A good example of where this is heading is Amazon, who are developing AI agents capable of generating shopping guides and customized recommendations, enhancing the shopping experience with auto-generated content.

So, what now for your store? 

A lot of chatbot and conversational commerce studies show that 50% of consumers are open to browsing or buying within messaging apps; some reports put it as high as 70–80%.

On the simplest level, this means using generative AI to improve customer experience with tools and apps like Chatty. But if you want to go a step further, consider virtual assistants and AI agents. 

A well-developed virtual assistant can do more than just help answer a potential customer's specific questions more quickly than support or FAQ pages can; it can also personalize responses and product recommendations and improve real-time shopper interactions. 

And there are plenty of tools to help you get there.

3. Inventory and Supply Chain Optimization and Backend Admin 

Generative AI might not be the first thing that comes to mind for supply chains, but it’s making a real impact behind the scenes.  

According to Salesforce, retail executives estimate that 36% of their employees use generative AI, with expectations that this number will increase to 45% by the end of this year! And with the right tools, retailers can use generative AI to:

• Plan where to send stock based on what’s selling and market trends 
• Come up with backup delivery routes if there are delays or disruptions 
• Make simple models to forecast supply and demand changes

So, what now for your store? 

Here are just some of the tasks retailers and teams can use generative AI for: 

4. Your Online Retail Visual Merchandising

Last but not least, let’s talk visual merchandising. 

With generative AI alone, retailers can now auto-generate their product visuals and mockups, on-store banners, and promotion graphics, or design custom product descriptions and tags. They can also: 

• Group products into curated collections automatically (like “Summer Essentials” or “Holiday Gifts”) based on inventory data, trends, or customer browsing history.
• Generate and test different homepage layouts or product arrangements to see which combinations might drive better engagement or sales.
• Help with SEO optimization of your product descriptions and dynamic tags to improve SEO. 

Fast-fashion retailer Shein uses AI to adapt its website content to customer demands in real-time. This allows dynamic visual merchandising, aligning product offerings with current trends and consumer preferences. 

And the payoff? According to Peter Pernot-Day, Shein’s head of global strategy and corporate affairs, “the net effect of this is reducing inventory waste.”

So, what now for your store? 

If you really want to take advantage of the positive impacts generative AI is having on online retail merchandising, you will likely need to pair it with tools that harness other technologies. 

For instance, by using ML, predictive analytics, and generative AI to create, sort, and automate innovative product collections and personalized content for your online storefront — just like our very own AI merchandising strategy engine (AMS) allows you to do!  

Where generative AI excels when creating new content for visual merchandising optimization — like generating product images, banners, or personalized storefront designs — much of the heavy lifting still relies on ML or AR.  

You can read more about these and other AI-powered tools here. 

Final Words 

The AI storm has landed, which means online retail will continuously evolve in parallel at the same pace.

But for brands who adapt quickly (and with AI, we really mean quick!), the wins will be niche dominance and profits! 

And when you consider that, according to a McKinsey study, generative AI has the potential to contribute between $400 billion and $660 billion annually to the retail and consumer packaged goods industries, we are not talking pocket change. 

As retailers continue to adopt and innovate with AI technologies, we are on the road to redefining the standards of efficiency and personalization that even the newest or smallest eCom stores will need to match when they enter the niche. 

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