Overview

Amazon has added an AI‑driven bulk‑listing option that lets sellers upload any XLS or TSV inventory file instead of re‑formatting data to match Amazon’s preset templates. The change, launched in Seller Central this month, is aimed at cutting the hours of manual spreadsheet work that large‑catalog sellers typically endure.

Key Points

• Custom file acceptance — Sellers can drop a native Excel or tab‑separated file into the bulk‑listing uploader, eliminating the need to download Amazon’s rigid template first.
• AI‑based field matching — The system scans column headers, infers product attributes such as title, price, and size, and automatically aligns them with Amazon’s catalog fields.
• Cross‑marketplace compatibility — Files exported from eBay, Shopify, Walmart, or a proprietary ERP can be used directly, removing the re‑formatting step that previously slowed multi‑channel expansion.
• Draft‑first workflow — After processing, the engine creates editable draft listings rather than publishing instantly, giving sellers a safety net to catch mapping errors.
• Scalable for high‑SKU volumes — A seller with 5,000 SKUs reported that the AI completed the initial mapping in under 15 minutes, a task that previously required several full workdays.
• Category‑specific nuance handling — While the AI covers common attributes, it flags fields that lack a clear counterpart (e.g., “fabric composition” for apparel) for manual review.

How the AI‑Powered Bulk Upload Works

1. Upload your own spreadsheet — A seller selects the bulk‑listing option on the Add Products page and drags a 10,000‑row Excel file that contains columns named “ItemName,” “Cost,” and “StockQty.” The system accepts the file without demanding a template conversion.
2. AI scans and identifies columns — The engine parses the header row, recognizes “ItemName” as a product title, “Cost” as the selling price, and “StockQty” as inventory quantity, then maps each to Amazon’s internal fields.
3. Draft listings are generated — For each row, the AI creates a draft entry populated with the inferred data, attaching placeholder bullet points where the source file lacked detailed descriptions.