The user's problem, splitting a master Excel file into personalized workbooks for each manager and emailing them automatically, is a textbook case of a tool being asked to do what a platform should. Power Automate can technically get this done, but the friction of identifying unique emails, filtering rows, generating dynamic workbooks, and attaching them to emails points to a deeper limitation. The spreadsheet is still acting as a database, and the automation is patching a workflow that was never designed to scale.
What this means in practice is that the user is spending mental energy on orchestration rather than insight. They are 90% of the way there conceptually, but that last 10% is the hardest part because Power Automate was not built for this kind of row-level data transformation. The flow becomes brittle: one column name change, one data type mismatch, or one email failure breaks the entire process. The user is not asking for a better spreadsheet; they are asking for a better data system.
The real opportunity here is to reframe the problem. Instead of automating the splitting and emailing of an Excel file, consider a live, shared view that each manager can access directly. An AI-native spreadsheet can filter rows by manager email instantly, without creating 10 new files. It can send a notification with a direct link to that filtered view, not an attachment. The manager gets the same data, the user avoids file creation and email attachment limits, and the master file remains the single source of truth.
This is not about replacing Excel. It is about recognizing when the tool has become the bottleneck. The user's scenario, 1,800 rows, multiple managers, dynamic filtering, is exactly the kind of task where an AI-native environment transforms the workflow from fragile automation to fluid interaction. The solution is not a more complex flow; it is a simpler architecture. Stop moving data around. Let the data stay put and bring the view to the person who needs it.