The process described, manually cross-referencing SKUs across two sheets, copying and pasting descriptors one by one, is exactly the kind of friction that holds teams back from doing more useful work. It is not a skill problem. It is a tool problem. The user who posted this knows their products inside out. They know the formulations, the ingredient quantities, the subtle differences between sheets. What they lack is a method that scales. And the honest truth is that no amount of careful copy-pasting will turn a 3-to-5-minute per-item chore into something sustainable when you have hundreds of items.
This is where an AI-native approach to spreadsheets changes the math entirely. Instead of treating the merge as a manual lookup exercise, you can describe the goal, "Combine these two sheets by matching SKU, keep all columns from both, and align rows where IDs match", and let the system interpret the structure. The AI does not get bored. It does not accidentally transpose a quantity or skip a descriptor. It reads the patterns in your data and executes the join in seconds. The result is a single master sheet that contains every column from both originals, with rows matched on the common identifier. You delete the duplicates. You move forward with one source of truth.
The practical benefit goes beyond time saved. When you eliminate the second sheet, you eliminate the confusion that comes with maintaining parallel records. No more wondering which version has the updated ingredient list. No more asking a colleague which sheet they pulled their numbers from. The single master list becomes the authoritative reference, and every team member works from the same dataset. That clarity has a compounding effect on decisions, pricing, inventory, compliance, because the foundation is trusted.
The key is to stop thinking of this as a data-entry task and start seeing it as a logic task. The user already knows the logic: match on SKU, retain all fields, merge. That is a simple instruction. The only reason it feels hard is that traditional spreadsheets require you to execute that logic manually, cell by cell. AI removes that execution burden. It takes the instruction and handles the repetition. For anyone managing product catalogs, inventory lists, or any dataset that lives in multiple places, this is the shift that matters most, not a more powerful formula, but a tool that understands what you mean and does the work so you can focus on what the data actually tells you.