Business intelligence was always the quantitative side: rows, numbers, things that fit in a column. The qualitative half, the calls and emails and tickets where the why actually lives, was invisible to it. That half is most of your data, and it is where AI adds value BI never could.
Teams building analytics AI keep starting from a blank page. Meanwhile the most validated business logic they own is sitting in the dashboards they already shipped. Those reports are years of distilled definitions and a ready-made test set. Mine them.
Every BI team has quietly run the same triage for years: is this worth a dashboard, or is it a one-off? Building a dashboard was the only durable option, so the long tail of one-time questions mostly went unasked. AI collapses the cost of the one-off, and that reshapes the whole portfolio.
Most people treat a Power BI report and its semantic model as one object. They are two files doing two jobs. When you point an AI agent at your data, the report is the cheap half and the semantic model is the part that took three years to get right.