Two Models for AI-Powered BI: Dashboards with Agents vs. Agent-First Design

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The author argues that the right AI-driven business intelligence design depends on data scope, user count, and how predictable questions are. For a narrow procurement project called SpendCube, built on Azure Databricks, Azure SQL Database, and Power BI, a dashboard paired with an AI agent is presented as practical. Power BI Copilot is cited as an example, with the key requirement being that the agent use the existing semantic model so its answers match dashboard KPIs. In contrast, BMW's Mobile Data Recorder collects over 10,000 signals from roughly 3,500 vehicles, making it impossible to anticipate every engineering question in advance. For such large, unpredictable datasets, the author favors an agent-first approach in which engineers describe what they want to investigate and the agent generates queries and visualizations.

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