Generative AI is Quietly Rewiring the Product Data Supply Chain

Generative artificial intelligence is quietly rewiring the product data supply chain. AI can now read, structure and reason over product information at scale, turning product data from a back-office burden into a strategic asset.

Retailers still wrestle with fragmented product data arriving in multiple formats. Teams spend significant time normalizing attributes, resolving gaps, and rewriting content for different channels. Generative AI can ingest unstructured inputs, map them to a defined taxonomy, and generate structured attributes and channel-ready content in a single flow.

When embedded into product information management (PIM) and master data management (MDM) workflows, AI helps centralize and enrich product information, enabling consistent output across direct-to-consumer sites, marketplaces and wholesale channels. Once this foundation is in place, product data becomes more than operational overhead — it becomes the engine for experimentation and growth.

Hygiene Use Cases: Establishing the Baseline

Several foundational applications are already emerging. Automated copy generation transforms sparse specifications into customer-ready product narratives aligned to brand guidelines. Image recognition and semantic models extract and standardize attributes, flag inconsistencies, and fill data gaps, allowing teams to shift from manual creation toward refinement and governance.

On the customer side, enriched product data supports more relevant recommendations, personalized landing pages and consistent answers across digital touchpoints. These applications establish a new baseline of efficiency and consistency. However, they're only the beginning.

Novel Merchandising and Assortment Possibilities

Once product data is consistently enriched, retailers can move beyond static categories and generic promotions. AI can generate intent-driven assortment narratives, dynamically selecting products that fit particular contexts or seasonal themes rather than relying solely on fixed hierarchies.

Scenario-based bundling is another emerging capability. By reasoning over attributes, reviews and returns data, AI can assemble context-specific bundles tailored to price bands, channels or inventory constraints. Micro-bundles that would previously have been uneconomic to curate manually become viable, offering differentiation without a proportional increase in workload.

In this model, merchandisers shift from manually curating countless variants to guiding systems with clear objectives, parameters and guardrails.

Linking Product Data to Operations and Supply

Enriched product data also strengthens operational decision-making. Instead of forecasting demand purely at a SKU level, AI can identify which combinations of attributes drive higher conversion or lower return rates, helping inform buying strategies and marketing priorities.

When inventory is constrained, systems can recommend attribute-based substitutions in real time, matching alternatives to the features that matter most to the customer. This approach helps mitigate lost sales while maintaining transparency and relevance.

A Shift Towards Genuinely Need‑Based Experiences

For customers, the most visible shift is from catalog-driven browsing to need-based journeys. Generative interfaces allow shoppers to describe their situation in natural language, translating intent into structured filters, recommendations and explainable trade-offs. Rather than navigating rigid taxonomies, customers interact in ways that feel more intuitive and context-aware.

At the same time, the marginal cost of experimentation drops significantly. Retailers can test variations in copy, imagery and attribute emphasis across micro-segments or local markets, allowing optimization systems to determine which combinations drive measurable impact.

As generative systems continue to maintain and enrich this product “brain,” the ability to continuously test, refine and adapt propositions may become one of the most meaningful competitive advantages in retail.

Martin Ryan is vice president of retail, Europe, EPAM Systems, Inc., a digital transformation services and product engineering company.