AI Tool of the Week: Google NotebookLM Custom Reports Turn Data Overload into Board-Ready Briefings

AI tool of the week: Google NotebookLM Custom Reports solve the executive data dilemma

3 min read | 27 Sept 2025, 01:30 pm IST

Leaders drown in reports, dashboards, and updates. What you need is the right format at the right moment-board deck, MBR, or a crisp ops brief-without hand-holding a team for days.

Google NotebookLM's Custom Reports feature tackles that bottleneck. It analyses your source materials and proposes the most useful report structure for your context.

What it is

Custom Reports turns a messy stack of documents into an output that fits the room: board presentation, operating summary, or project update. It chooses a format, extracts the signal, and lays it out with references to the sources.

Learn more about NotebookLM here: Google NotebookLM.

Where it fits in your week

• Board prep: Pull KPIs, risks, and decisions needed-no slide-sprawl.
• Ops brief: Yesterday's performance, today's blockers, owner and next step.
• Investor update: Growth drivers, churn drivers, cash runway, hiring plan.
• QBR/MBR: Targets vs actuals, variance analysis, corrective actions.

Fast setup

• Collect sources: QBR docs, KPI dashboards exports, CRM notes, research summaries.
• Upload to NotebookLM and select Custom Reports.
• Pick the intended audience: board, exec staff, or functional team.
• Review the suggested format, edit sections, and request clarifications.

Prompts that save time

• "Create a board-ready summary with 5 slides: growth, profitability, risks, roadmap, decisions required. Cite sources."
• "Operational brief for today: top 3 issues, owner, ETA, and impact on targets. Keep it to one page."
• "Variance analysis for Q3: what changed, why it changed, and the plan to fix."

Governance and accuracy

• Require sources for every claim; spot-check against the originals.
• Freeze inputs for formal reports; keep a log of data versions.
• Sensitive data: confirm access controls before uploading.
• Final review stays with the report owner; AI drafts, humans approve.

Metrics to track

• Time saved from brief to draft.
• Rework cycles per report.
• Decision latency from report delivery to decision made.
• Stakeholder satisfaction score after each report.

14-day pilot plan

• Day 1-3: Define two report types to automate and assemble source packs.
• Day 4-7: Generate first drafts, set citation rules, and standardize sections.
• Day 8-10: Run with live stakeholders; collect feedback on clarity and actionability.
• Day 11-14: Lock the template, document the workflow, and roll out to one more team.

The value is simple: less compile time, more decision time. If your team spends hours formatting updates, this pays for itself in the first cycle.

Want structured upskilling for leadership teams implementing AI reporting workflows? Explore curated options by role: AI courses by job.