The problem posted by this user is not unusual. It is the kind of request we see every day from people who are perfectly capable with spreadsheets but have hit a wall. They know the data exists on the web. They know the formula exists in their tool. The gap is not intelligence, it is a lack of translation between what they want and what the function expects. That gap is exactly where AI should step in, and the fact that it still requires a Reddit post to bridge it tells us something important about where spreadsheet tools are falling short.
The user has 1,500 names to fill. They have a reference column and a target column. They have heard about INDEX and IMPORTXML, but they do not know how to connect those pieces into a working solution. This is not a failure of effort. It is a failure of design. A tool that requires a user to research nested functions and then ask strangers for help is not an empowering tool. It is a gatekeeping one. The promise of AI in this context is not to replace the user's judgment, it is to remove the friction between intention and execution. When someone says, "I want the Treasury Manager name from Google search," the tool should understand that request and produce the formula. The user should not have to become a developer to get their work done.
What this means in practice is that the spreadsheet industry has been coasting on familiarity. People stay with traditional tools because they know the layout, not because the layout serves them well. The user in this example is clearly willing to explore, they found the function, they tried to understand it, but they ran into a wall of syntax and context. An AI-native spreadsheet would have handled this differently. It would have recognized the pattern: column of identifiers, web lookup, structured extraction. It would have offered to build the formula, test it against a sample row, and then scale it across all 1,500 rows. The user's job would shift from debugging to verifying, which is where human attention adds the most value.
This is not a minor convenience. For someone managing 1,500 rows of treasury data, the difference between a manual lookup and an automated fill is hours of work. Multiply that by every department in every company, and the productivity gain is substantial. But the deeper point is about access. Not everyone who works with data wants to write formulas. Many people have domain expertise and simply need the tool to execute. When we design tools that assume advanced formula literacy, we exclude those people. That exclusion is not inevitable. It is a design choice. And it is one we are ready to see change.