From Marketing to Search: How Generative AI Is Reshaping Retail Giants

Discover how retail giants use generative AI to transform marketing, search, and customer service while driving sales and protecting data.

Generative AI has huge potential in retail.

It’s already being used for customer support via chatbots, but there are many other unfulfilled roles that AI can play in getting more sales through advertising, personal shoppers, and sentiment collection and analysis.

Victoria’s Secret, Swarovski, Saks Global, and Shopify are some of the biggest names using gen AI, but this list is quickly growing across retail markets of all sizes as we see a blossoming AI revolution in e-commerce.

A huge $500B infrastructure investment is likely to be the driver for this revolution, as it makes it easier than ever to adopt gen AI and use it to get shoppers hooked and buying products.

This article explores this investment and how it is driving a generative AI transformation in e-commerce.

AI-Powered Marketing Transformation

Shoppers don’t want a universal experience; they want to be treated like individuals and shown what is perfect for them, based on what they like to do and how they live their lives. Generative AI offers this in a way no other technology can.

It does so by analyzing customer behavior, preferences, and purchase history to create tailored messages, offers, and visuals, delivering highly relevant marketing campaigns that increase engagement, strengthen loyalty, and boost conversion rates.

Two of the best examples of this are Victoria’s Secret and Swarovski, which use generative AI to craft personalized visuals, product descriptions, and promotions, aligning with customer preferences, enhancing brand appeal, and driving higher engagement across digital and social platforms.

Customer Service Reinvented

Gen AI isn’t just great for advertising, it’s also a powerful tool in fast, effective customer service. AI chatbots and virtual assistants are common across even smaller e-commerce markets due to their speed and accuracy at resolving customer queries, from simple product detail questions to giving information on returns.

These tools are also capable of performing more complex tasks, like:

“I need a sustainable cocktail dress under $200, in navy, available in petite sizes, and deliverable before next Friday.”

It instantly searches the inventory, filters by sustainability certifications, size, price, and color, checks delivery timelines, then provides a curated list with direct purchase links — all in a single conversation.

Automating this complex set of processes reduces operational costs while enhancing customer satisfaction, because they get a fast, tailored experience without ever having to wait for an employee to be available.

Smarter Search and Product Discovery

AI offers powerful search query capabilities, as shown in the example above. AI-enhanced search algorithms go beyond simpler algorithms of the past to provide more accurate, context-based, and fine-tuned results.

These tools can even personalize recommendations based on the user intent data they collect from shoppers to show them the products they are most likely to desire. If a user often searches for products associated with DIY, AI can offer more products in this product group to increase the chance of customer satisfaction and closed sales.

A high-scale example of this is Saks Global, which uses generative AI to analyze trends, customer data, and inventory, enabling dynamic product placement, personalized recommendations, and optimized assortments that boost sales performance and enhance the overall shopping experience.

Cybersecurity in the Age of Retail AI

One of the most significant threats gen AI-powered retail platforms face is cyber threats in the form of hackers stealing customer data to use for other online shopping platforms.

AI-powered platforms are often targeted because hackers know they contain large amounts of customer sentiment data that they can sell to other e-commerce sites to gain a competitive edge.

But e-commerce platforms are fighting back. They use advanced threat detection, encryption, multi-factor authentication, and continuous monitoring, ensuring customer data protection and maintaining trust in AI-powered shopping experiences.

Another powerful tool is vendor risk management software, which protects against another risk: third-party AI providers who steal information without the client knowing. These tools assess the risk of a software vendor to ensure vendors are safe and will not compromise valuable customer data.

Conclusion

AI is becoming transformative for e-commerce and will continue to find more applications and ways to please customers and increase sales and revenue over the coming years. These applications will cover marketing, search, and many other functions.

There are benefits and limitations to this widescale adoption of AI. The benefits are that customers can have their queries resolved quickly and accurately without having to wait for employees to be available, and they can receive customized product recommendations based on their search intent.

However, one of the main limitations is that hackers can steal customer data if they know a platform uses AI to collect large amounts of sentiment data that has high value. Risk management software can lessen these risks and keep customers safe as e-commerce platforms use cybersecurity alongside AI to grow and satisfy customers.