AI is proving invaluable in the dynamic e-commerce sector. For retailers, content creation and product launches are quicker than ever. For shoppers, ‘conversational commerce’ is an engaging new way to discover products and find the best deals.
Whether it’s working behind the scenes to generate product descriptions and visuals, or on-screen helping shoppers make confident purchases, AI is only as good as the information it’s given. It needs approved digital assets, trusted brand context, and structured product data – something many e-commerce brands don't yet have.
If this sounds like you, here’s how to get those foundations right, so you’re ready to use AI to enhance the customer experience, make sales, and drive growth.
‘One of the biggest challenges for e-commerce brands will be surviving the shift toward agentic commerce, where autonomous AI agents do the heavy lifting of browsing and comparing products for consumers. This changes the rules of data quality. AI models are risk-averse and require flawless data to generate a recommendation. If a brand’s product data is thin or contradictory across retail endpoints, the AI excludes it to avoid a hallucination. This means that today’s legacy, human-scaled data management leaves massive logic gaps that disqualify products instantly.’
— Rob Gonzalez, Salsify Co-Founder and Chief Strategy and Innovation Officer
Where we are and where we’re going: from generative to agentic AI
Most retailers are at the generative stage of AI adoption.
Between rapidly changing product ranges and the diverse digital assets available to support conversion (such as images, video, spins, lifestyle shots, and UGC), marketers need to create and manage a huge amount of content.
AI is invaluable in this context – creating and translating product descriptions, localizing content, creating retailer-specific adaptations, and optimizing product imagery.
However, to reach storefronts and customers, that content needs fast and accurate distribution. Something manual processes can’t guarantee.
Storefront operations frequently rely on manual asset workflows, disconnected systems, and inconsistent processes – undermining the impact of one of your most influential brand touchpoints.
This is where automation and agentic AI must enter the workflow. Otherwise, AI simply generates more content for e-commerce and marketing teams to manage manually, undermining the productivity gains it initially created.
‘The biggest future differentiator will come down to data architecture. Winning brands will use AI to build a robust underlying context layer. Instead of burning hours cross-referencing files, teams will use automated AI workflows to map rich assets to product specs, pushing contextualized product experiences out to every digital shelf much faster.’
‘In comparison, struggling brands will still treat AI as a glorified front-end copywriting tool to spin up quick descriptions – an outdated approach that leaves them trapped in a cycle of manual adjustments.’
— Rob Gonzalez, Salsify Co-Founder and Chief Strategy and Innovation Officer
The hidden gap in e-commerce brand governance
As AI becomes more deeply embedded in e-commerce workflows, it's exposing a long-standing challenge for retailers: disconnected product information, digital assets, and brand processes.
These legacy ways of working have long created inefficiencies, but AI raises the stakes. Without connected, trusted information, it simply can't deliver reliable, on-brand results.
Generative AI doesn't understand your brand on its own. To produce accurate, on-brand content at scale, it needs access to approved digital assets, structured product information, clear metadata, and the rules that define how your brand should appear across every channel.
But brand governance doesn’t stop when an asset is approved. For internal AI agents to automate merchandising and content distribution (and for external AI assistants to surface and recommend products to customers) brand context needs to travel with every asset, wherever it goes – from storage and management systems, to distribution and publication on storefronts.
But many brands don’t have the infrastructure and AI-ready brand intelligence to make this possible yet.
‘To future-proof your commerce strategy, you must treat data structure as a survival mechanism. Turning raw product information into a machine-legible ground truth ensures that when AI agents go shopping for your customers, your brand is actually on the invitation list.’
— Rob Gonzalez, Salsify Co-Founder and Chief Strategy and Innovation Officer
The legacy disconnect between DAM and PIM
The challenge for many retailers is that there isn't a true single source of truth powering either their e-commerce storefronts or their AI workflows.
Product information typically lives in a Product Information Management (PIM) system, storing structured data such as product names, specifications, dimensions, pricing, SKUs and attributes. Meanwhile, product imagery, videos, lifestyle photography and other approved creative assets are managed separately in a Digital Asset Management (DAM) platform.
Both systems describe the same product, but from different perspectives. They’re two sides of the same coin. Yet, in many organizations, they remain disconnected. This leaves teams to manually link assets with product information every time content is published or updated.
Wondering where the boundaries lie between DAM and PIM? Learn which system owns what.
‘Connecting PIM and DAM systems is more than important – it’s foundational. Winning in this new era of commerce requires two things: driving radical efficiency in today's digital operations, and building the structural foundation for a future where AI agents run product discovery. That foundation starts with connecting product truth to brand assets.’
‘Without this connection, AI commerce tools break down because engines require a deeply integrated mix of structured metadata and high-quality multimodal proof to build recommendations. Integrating your PIM and DAM creates a singular system of record that eliminates manual, siloed workflows. ‘
— Rob Gonzalez, Salsify Co-Founder and Chief Strategy and Innovation Officer
An integrated tech stack is the answer
This challenge – or let’s say opportunity – is why leading e-commerce teams are building connected ecosystems that bring together DAM, PIM, CMS, brand, and commerce platforms such as Shopify.
Instead of relying on manual handoffs between disconnected systems, they create seamless workflows where product information and digital assets flow automatically to the teams and channels that need them.
This connected architecture:
- Improves generative content creation by giving AI tools the brand context and approved assets it needs for on-brand content every time
- Transforms content distribution by ensuring approved assets and product information can move automatically from brand systems to e-commerce storefronts, marketplaces, and retail partners
This reduces duplication, accelerates product launches, and ensures every customer sees accurate, up-to-date content – whether they’re shopping your brand on owned properties, third parties, or via AI intermediaries.
Frontify’s enterprise-grade DAM and brand management platform integrates with Shopify, Salsify, Akeneo and other e-commerce tools to empower seamless automation AI workflows.
‘Successful brands will view AI not as a replacement, but as the ultimate co-pilot to human ingenuity. Over time, e-commerce teams will move past the transactional chore of manual data manipulation and shift to a strategic, outcomes-driven discipline. Technology naturally automates the tasks at the bottom so human teams can shift up a notch. The only way to figure out what these workflows look like is to start actively using them today.’
— Rob Gonzalez, Salsify Co-Founder and Chief Strategy and Innovation Officer
The future: governed brand execution
With a connected tech stack, e-commerce brands don't have to choose between governance and automation.
The most successful organizations combine both, using AI to create, adapt, localize, tag and distribute content at unprecedented scale, while ensuring every output is grounded in approved assets and trusted product information.
The brands that win won't simply use more AI. They'll build the connected brand infrastructure that allows AI to work autonomously within secure guardrails. This will free people to work on higher-value tasks that further elevate your brand.
Learn how e-commerce teams keep thousands of product assets accurate and on-brand with Frontify