Ecommerce teams have long grappled with manually mapping retailer attributes and repetitive processes to update existing and new channels.
The process is time-consuming and error-prone, but AI now gives teams a smarter, more automated, and compliant way to syndicate product content across channels — all while keeping humans in the loop.
Companies like CJ Schwan’s, a leading frozen food manufacturer of well-known brands like RED BARON, are harnessing AI-powered syndication to improve product information management.
Adriana Vaca, CJ Schwan’s digital shelf manager, and Amanda Farley, Salsify’s senior growth product manager, led a session at the 2026 Digital Shelf Summit (DSS) detailing how AI is reshaping syndication, automating workflows to resolve complex mapping, and empowering brands to deliver high-quality, accurate, and more relevant product experiences at scale.
AI is transforming both how consumers shop and how brands manage and deploy their product content.
Agentic commerce is growing as consumers increasingly turn to ChatGPT, Google Gemini, and other generative AI (GenAI) engines as part of the buying process.
According to Salsify’s “2026 Consumer Research” report, 19% of shoppers use AI tools for product discovery, and 22% use them for product research.
“Retailer-specific chatbots will keep the purchasing within their platform to secure those sales with the assistance of an agent,” Vaca says.
These trends make accurate, properly governed product data even more important. Brands now need to prepare for AI search engines and AI shopping assistants that act as recommendation engines.
Both tools pull information from product detail pages (PDPs), ratings and reviews, retailer catalogs, and scrape information from across the web. This means that context-rich, accurate, and well-structured product data is now table stakes.
The Salsify Product Experience Management (PXM) platform’s AI-powered syndication capabilities optimize this process for brands.
Brands are taking advantage of the Salsify PXM platform’s built-in AI-powered syndication capabilities and its AI-powered PXM assistant, Angie, to deliver more compelling product experiences.
Farley, who provided an overview of Salsify’s current tools and future roadmap, says the platform’s auto-mapping and auto-fix capabilities will fundamentally change how brands syndicate out their product data to retail and AI channels.
In other words, these capabilities can significantly reduce the amount of time it takes to set up and manage channels, so your teams can spend less time configuring and more time optimizing and strategizing to drive growth
"AI syndication is the perfect application for the power of AI to tackle the most challenging problems that you're facing day in and day out," she says.
Auto Mapping significantly reduces the amount of time it takes to set up new channels, allowing teams to work faster and expand their reach more easily.
Here’s how it looks in practice: Teams can remove the tedious work of manual configuration by deploying embedded AI to predict and propose mappings for relevant attributes instantly. Instead of burning hours starting from scratch, teams simply select a channel, choose a locale, and let an all-in-one, AI-powered configuration wizard handle the setup, Farley says.
Auto Mapping uses retailer requirements, property metadata, previous mappings, product information, and other inputs to build recommended mappings. However, a human always has final approval.
The technology just streamlines the path to get there. Your team keeps total control with final approval, while the technology supercharges the path to get there.
“You'll never have to start from scratch again,” Farley says.
Auto Fix is being called a game-changer for syndication — and here’s why: Auto Fix simplifies troubleshooting issues such as retailer errors, schema changes, and broken property mappings.
Think of Auto Fix as an automated troubleshooting command center, one that helps you solve publishing issues quickly and get content live faster.
Here’s how it looks in practice: Even with a ready channel, getting products live isn't guaranteed. Retailer feedback often points to deeper issues, like a category mismatch, which normally triggers long delays.
With Salsify and Angie working with you, that process becomes seamless. Angie directly interprets the retailer feedback, identifies the root cause of the error, and suggests exactly how to fix it. This transforms a frustrating roadblock into a quick, actionable solution so your content goes live without the delay.
Angie complements Auto Mapping and Auto Fix with a conversational interface that allows teams to ask questions and get answers that simplify their workflow. The conversational assistant enables teams to set up new channels faster, helping them write, summarize, and troubleshoot formulas.
They can ask Angie questions about the Salsify PXM platform and get a quick response, benefiting from real-time support that empowers them to speed product content creation and updates.
During the DSS session, Farley says current and soon-to-come AI-powered capabilities within the Salsify PXM platform address three major pain points for brands.
Rather than start from zero to map a new retailer channel, the platform streamlines the process.
“We're removing that initial blank page friction for syndication," Farley says. "Instead of starting with a blank page, you're going to be starting with a guided experience."
Teams can reuse the same mappings across multiple retailers in less time.
Traditional oversight processes slow down content deployment. Human oversight is integrated into the platform’s AI-powered workflows.
This means that teams can review and approve content any time — AI acts as an intelligent assistant and thought partner, but is never the final decision-maker.
Companies such as CJ Schwan’s are using these capabilities to scale their three-person digital shelf teams and bring product experiences to market faster.
CJ Schwan’s isn’t just using Salsify’s AI-powered tools to support better product information management; it’s using the technology to showcase the value of human-AI collaboration.
First, the company has pulled conversational language from its reviews and ratings to make its products feel more human and customer-centric.
"We always start with a human, because that's who we're actually selling to,” Vaca says.
“As we're entering into this age of AI slop and just tons of information on the internet being kind of bland, I think it's an obligation as a marketer to stay true to what people really care about, which is authentic brands that want to give good quality products to people to improve their life,” she adds. “That's why whenever we create content, we always start with a human.”
CJ Schwan’s also uses Angie to support its syndication journey, leaning on the conversational assistant to speed and improve mapping accuracy, deliver more robust product information, enrich content attributes and existing formulas with additional details, and extend product content to new channels like Family Dollar.
For example, the company’s digital shelf team has used Angie to create formulas that turn raw ingredient data into compelling, retailer-ready attributes.
“When Angie was introduced, I thought, ‘Great, I don't have to learn anything anymore about formulas, and I can have her do it for me," Vaca says. "So, I said, 'Hey, Angie, give me an example of how I can adjust this for multiple outputs based on the ingredients property.’ She gave me a breakdown of all the cheese types, which was great."
CJ Schwan’s is using Angie and AI-powered syndication to scale the work of its small but mighty team. Vaca and her colleagues no longer have to manually map to different channels, build formulas from scratch, or reconfigure their workflows to meet different retailer requirements. They can use AI to do much of the heavy lifting. Then, apply their fine-tuned skills and industry experience to validate the platform’s outputs.
To get the most value out of these AI-powered tools, Vaca says brands should do some initial legwork. That includes understanding what data they’ve transferred to the Salsify platform and any data gaps they need to address.
“AI loves data, and it loves all kinds of data," she says. "We want to make sure it loves our true data that's actually accurate."
When prompting in Angie, make sure to provide clear and specific instructions and write in what Vaca called “Salsify-friendly language,” meaning use specific terms reflected in the platform, like “property attributes.” Providing retailer context is also important to get higher-quality outputs, Vaca says.
Most importantly, “double-check and test before publishing,” she adds. “Review to make sure you're getting a properly formatted formula that is usable and has a useful output.”
CJ Schwan’s shows that companies can unlock the full potential of AI when they use it to augment and amplify their team’s work, rather than replace it. Farley says that’s exactly what Salsify’s AI-powered syndication tools are designed to do.
“We're excited to introduce the path to touchless syndication, powered by SalsifyIQ, and leveraging AI to scale your expertise,” Farley says. “Let Salsify take care of the hard work, the manual repetitive tasks, and syndication, so that you can focus on the most important thing — growing your business.”