Data about ‘products’ or ‘items’ is the life blood of any retail business. At Target, this data resides within ‘Item Systems’ and cascades down to power different business processes. The quality of this data not only affects our guests’ (customers’) satisfaction levels—spurring joy or causing frustration—but also significantly impacts revenue and operational efficiency.

With the advent and widespread adoption of Generative AI (GenAI), an unprecedented opportunity has emerged to harness AI models to refine and enhance item data, unlocking the possibility of tens of thousands of beneficial modifications. Achieving this on a grand scale necessitates a fluid integration between the item data ecosystem and the AI models being applied.

This talk will cover the principles and architecture implemented in Target’s Applied ML framework to realize this ambition.