The article outlines five steps to turn AI-generated dashboards from eye candy into actionable tools. It covers defining clear questions, matching chart types to those questions, intentional design (colors, layout, context), narrative flow, and thoughtful interactivity. It also shares prompt examples and tips to enforce these rules in any AI charting tool.

• Before prompting an AI for charts, nail down who's looking, what decision they'll make, and the one key takeaway—otherwise you get eye candy that tells you nothing.
• Match chart type to question: line charts for trends, bar charts for rankings, scatter plots for correlations, and skip pie charts with many slices, 3D effects, dual axes, and spaghetti charts.
• Limit dashboards to five meaningful colors, start bar axes at zero, and add context markers like a WHO guideline line or a COVID-lockdown marker.
• In the WHO air quality example, 93% of cities exceed safe PM2.5 limits, and framing the dashboard as normal levels → problem → improvements (e.g., China's Blue Sky Policy) → next steps turns it into a narrative rather than just charts.