The Fourth Way: Why AI for BI Isn't Delivering on Its Promises
The article argues that current AI implementations in business intelligence largely fail to fulfill their potential because they are superficially added onto existing analytics systems rather than being fundamentally integrated into the analytical architecture from the beginning, leading to suboptimal user experiences.
AI for BI Isn’t Delivering on Its Promises
Some lead with chat interfaces. Others promote automated insights or recommendation widgets. A few have scattered AI features across dashboards, preparation tools, and visualization modules. Almost all of them emphasize AI prominently in their messaging.
For all their differences, these approaches share a common pattern: AI is layered on top of an existing analytics system, rather than designed into the analytical foundation from the start.
The underlying architecture remains unchanged, and AI is added where it is most convenient to attach.
This design choice has consequences for users.