Automated report generation

Problem

Data analysts spend 30–50% of their time building recurring reports: pulling data, creating charts, writing summaries, and distributing to stakeholders. Weekly business reviews, monthly board reports, and campaign performance summaries follow the same structure every time but still require hours of manual assembly. Meanwhile, ad-hoc report requests pile up in the backlog.

Solution

The AI agent connects to your data sources (warehouse, BI tool, CRM, marketing platforms), pulls the metrics for each report section, generates visualizations, writes narrative summaries that explain what changed and why, and distributes the finished report via email, Slack, or your preferred channel. Reports run on schedule or on demand, and stakeholders can ask follow-up questions in natural language.

Benefits

• Recurring reports generated in minutes instead of hours
• Narrative summaries explain the 'why' behind the numbers
• Stakeholders self-serve follow-up questions without analyst involvement
• Analysts reclaim 10–15 hours/week for strategic analysis

How to get started

1. 1

   Define report templates

   Specify the structure of each recurring report: which metrics, what time periods, comparison benchmarks, and who receives it. The AI maps each section to data sources and creates the template.

2. 2

   Configure schedule and distribution

   Set the cadence (daily, weekly, monthly) and distribution channel (email, Slack, dashboard). Define the audience and any conditional logic (e.g., only send the alert section if a metric is off-track).

3. 3

   Review and refine

   Review the first few generated reports for accuracy and tone. Adjust narrative style, add or remove sections, and refine the metrics. After 2–3 cycles, the reports run autonomously with periodic spot-checks.

Recommended tools

ThoughtSpot, Databox, Coefficient. See the full list on the AI Data Analyst Agent pillar page.