Does it feel like artificial intelligence (AI) is at the tip of everyone’s tongue lately?
While talk of AI transformation and innovation continues to take center stage in (seemingly) every business conversation, knowing how and when to leverage AI within your specific industry — and finding the precious time to test and learn — may be the hardest step.
(Unfortunately, AI can’t get you out of back-to-back or should-have-been-an-email meetings — yet.)
Fortunately, we can turn to ecommerce innovators for inspiration and insights into building an effective artificial intelligence in ecommerce strategy. Explore the basics of AI in ecommerce, gain insights into how shoppers and brands use AI, and see real-world examples to ignite your planning.
Within ecommerce, artificial intelligence is used externally with shoppers to enhance the buying journey and internally at organizations to automate processes and optimize operations.
Machine learning (ML), natural language processing (NLP), generative AI (GenAI), and computer vision are the most commonly used AI technologies within ecommerce.
For shoppers, AI shopping assistants and chatbots can help build next-level shopping experiences, allowing for personalization at scale and real-time responses — anytime, anywhere.
Salsify’s “2025 Consumer Research” report found that “17% of shoppers have purchased a product because it was recommended by an AI shopping assistant or chatbot.” Across generation groups, 20% of Gen Zers, 22% of millennials, 16% of Gen Zers, and 7% of baby boomers have made an AI-based buy.
Unsurprisingly, interest tapers off for older shoppers, but as technologies become more readily available and incorporated naturally into shopping experiences, these sales will almost certainly grow.
For organizations, AI can help automate processes, such as repetitive actions like updating properties, sending messages, and publishing to channels — which can offer exceptional time-saving benefits for teams. It can also help optimize operations like pricing, inventory management, and fraud detection.
For both shoppers and organizations, artificial intelligence in ecommerce can offer notable benefits that will continue to evolve as the technologies evolve.
Shoppers are already using AI-powered shopping tools, such as shopping assistants, chatbots, virtual try-on tools, and voice shopping devices like Amazon Alexa or Google Home.
Twenty-eight percent say they find shopping assistants and chatbots “valuable,” according to Salsify’s consumer research report.
It’s simple: AI-powered shopping experiences can mean more sales. Here are some of the ways shoppers are using these AI tools.
According to the “Ecommerce Pulse Report: Q4 2024” from Salsify and the Digital Shelf Institute (DSI), 37% of shoppers will make purchases more often due to personalized product recommendations.
AI offers brands the ability to make these recommendations at scale, leveraging information from customer profiles, past purchases, and other information to deliver tailored, targeted options for shoppers.
Stitch Fix is an online personal styling service that relies on AI-powered personalized product recommendations. Leveraging zero-party data — where shoppers provide brands with personal information in exchange for personalized recommendations — AI-powered recommendations using said data, and a human stylist to fine-tune the recommendations, Stitch Fix offers shoppers hyper-personalized fashion and apparel options.
Online shoppers want detailed product information — and they’ll move on without it. Fifty-four percent of shoppers have abandoned a sale due to incomplete or poorly written product titles or descriptions, according to Salsify’s “2025 Consumer Research” report.
AI-powered shopping assistants and chatbots offer consumers a new way to get the information they need to make final buying decisions, such as:
Rufus, Amazon’s AI-powered shopping experience, offers these features to shoppers using a custom large language model (LLM) that was trained with Amazon data, such as the complete Amazon product catalog, customer reviews, and Q&A questions from the community.
Image Source: Amazon
AI-powered visual search tools give shoppers the ability to shop anything they see — from fashion and apparel products to furniture, home goods, and beyond. By simply snapping a photo on their smartphones, shoppers can find exact matches and similar products in seconds.
These AI-powered visual search tools are a natural fit for the omnichannel state of commerce, where the average shopper moves seamlessly from one touch point to the next without a thought, and these pools give them critical information the moment they need it.
Google Lens is one AI tool that offers shoppers the ability to shop images. Shoppers simply snap or upload a photo to see a list of exact or similar products, complete with prices and links to storefronts.
Image Source: Google
AR has been used for years as a way to enhance shopping experiences, growing alongside shopper preferences for omnichannel commerce, which blur the line between online and in-store shopping.
As AI technology has evolved, it has also been incorporated into existing AR technologies like virtual try-ons, in-room product placements, and interactive in-store displays.
Beauty brand L'Oréal Paris launched a new AI-powered tool Skin Genius, which uses AI-powered AR to make a personalized skincare routine from a skin analysis. The brand also offers makeup and hair color try-on tools, which help shoppers better visualize and color-match products virtually — a historically challenging part of selling beauty products online.
Seventy-five percent of CEOs “believe the organization with the most advanced generative AI will have a competitive advantage” — and 69% already see “broad benefits” of GenAI for their organizations, according to a study from IBM.
As AI technologies continue to become more sophisticated, their benefits will also increase in lockstep. Here are some of the ways ecommerce organizations are currently using AI to automate processes and optimize operations.
For many brands, product content creation is the core area where they have focused their AI efforts. GenAI can help ecommerce teams scale the development of product descriptions, product images, and other essential product content at scale — allowing them to create high-quality content across product catalogs with less time than before.
“What AI will allow you to do is have a perfect product detail page with every bullet SEO [search engine optimization] optimized, with every image set up for conversation, with all of the manufacturer stuff filled out — on every single page where your products can show up,” says Rob Gonzalez, Salsify co-founder and chief strategy and innovation officer.
“You’re giving the entire assortment on every single channel a fighting chance,” Gonzalez says.
Source: Salsify YouTube
AI tools can help ecommerce teams optimize data models, helping them avoid spending weeks structuring product data and ensuring a more accurate and efficient data model.
“A lot of companies for PIM [product information management] implementations will spend a lot of time thinking about data modeling,” Rob Gonzalez says. “Using GenAI can actually decrease the time to get to a model that is compelling for you.”
High-quality product data is essential for shoppers and helps brands meet retailer requirements, ensuring a streamlined go-to-market process. However, for large product assortments, quality assurance is time-consuming.
Gonzalez highlights how many retailer style guidelines have qualitative criteria. For example, retailer guidelines may request that brands avoid unverifiable claims in product descriptions.
“How do you check that if you have a huge product assortment?” Gonzalez says. “You can have an AI do that type of checking for you. ‘Find if this description has claims.’”
By training the AI tool, brands could eliminate much of the manual work required to ensure high-quality product data that meets retailer guidelines.
Thinking outside of the product data box, AI-powered ecommerce tools can help increase efficiency and reduce manual effort for teams through automation of time-consuming tasks.
Using AI-powered automation, ecommerce teams can build scalable, repeatable processes using workflows — avoiding back-and-forth across teams — and can automate repetitive actions like updating properties, sending messaging, and publishing to configured channels.
UMA Home Décor leveraged AI tools to reduce content production time to weeks instead of months, building significant efficiencies in their go-to-market processes and allowing their team to focus on strategic initiatives to book sales.
“We’re so far ahead that we can actually go back to review and optimize old content,” says Rebekka Meters, director of creative and content at UMA Home Décor.
“It’s going to be an amplifier — especially for those longtail products,” Gonzalez says. “And it’s going to make every single person on your team that’s responsible for the digital shelf more productive.”
Undoubtedly, as AI continues to evolve, so will its use in ecommerce.
These technologies will not only enhance shopping experiences — leading to better business outcomes for ecommerce — but will also help ecommerce teams reduce tedious, time-consuming tasks so they can focus on innovation to meet shoppers in the next era of shopping.