The task
Every Monday morning you write the weekly KPI summary for your team or leadership. You pull the numbers, then spend 60-90 minutes wordsmithing the narrative. The summary needs a TL;DR a busy exec will read, 2-4 wins worth celebrating, 2-4 risks that need attention, and ideally one ask — the thing you need from leadership to move faster. AI can compress the writing from 90 minutes to 15 if you feed it well.
When AI is the right tool
- You write a weekly summary in the same format every time.
- The metrics are stable week to week and the audience is the same.
- You have the numbers cleaned and ready to paste.
- You want consistency in voice across weeks (or across teammates writing on rotation).
When not to rely on AI alone
- For board-ready summaries that get scrutinized line by line — AI as first draft, you finalize.
- When the week had a major outlier event (incident, launch, layoff) — the framing is delicate and personal.
- For numbers that are sensitive or pre-public (earnings, M&A signals). Be careful with what you paste.
What to feed the AI
- This week’s metrics with last week’s and target as comparison points.
- Notable events: launches, incidents, campaigns, holidays, churn.
- The audience: who reads it, what they care about, what they will ask.
- House style: voice, format, what gets cut for being too vague.
- Last week’s summary as a structural reference.
Copy-ready prompt
Write this week's KPI summary.
Audience: {who, what they care about}
Voice: {3-5 adjectives, e.g. "concise, candid, action-oriented"}
This week's metrics (this week / last week / target):
- {metric 1: this / last / target}
- {metric 2: ...}
- {metric 3: ...}
Notable events this week:
- {launch, incident, holiday, campaign, etc.}
Output structure:
- TL;DR (2-3 sentences max — a busy exec must get the week from this alone).
- Top 3 wins (with the specific number that earned each one).
- Top 3 risks (with the leading indicator, not the lagging one).
- 1 ask (specific request — money, headcount, decision, unblock).
- 1 "what to watch next week" sentence.
Constraints:
- Total length under 250 words.
- Every claim must reference a number.
- No fluff verbs ("crushing it", "doing well").
- If something is flat, say flat. Do not dress it up.Recommended output structure
A great KPI summary fits on one screen: TL;DR (2-3 sentences), 3 wins, 3 risks, 1 ask, 1 watch. Each line cites a number. Less than 250 words total. Read it aloud — if any sentence does not earn its place, cut it.
How to check the output
- Read only the TL;DR. Does it tell the week’s story?
- Spot-check three numbers against your source data. AI rounds or misreads.
- Is the “ask” actually specific? “Support from leadership” is not an ask; “approve hiring 2 SDRs by Friday” is.
- Does it match your house voice, or does it suddenly say “leveraging synergies”?
Common mistakes
- Just numbers, no narrative. The narrative is the value-add.
- An “ask” that is vague. If you can’t answer “what changes if leadership says yes,” it is not an ask.
- Burying the lede. The biggest news should be in sentence 1, not paragraph 3.
- Same wins every week. If “growth team shipped X” appears for 4 weeks, your audience tunes out.
Next steps to keep improving
After 4 weeks, ask the AI to look across summaries: “what patterns repeat? what is missing?” You will catch yourself reporting the same metrics that no one acts on. Rotate or cut them. Add the ones the audience keeps asking about in meetings.
Practical depth notes
For Write a Weekly KPI Summary With AI: Numbers In, Executive-Ready Summary Out, the difference between a usable AI result and a generic one is the input packet. Give the model the audience, the current draft or raw material, the desired format, the decision you need to make, and two examples of what good and bad output look like. Ask it to preserve facts first, then improve structure or wording second.
After the first response, do a separate review pass. Look for missing constraints, invented details, weak calls to action, and language that sounds plausible but does not match the real situation. The best final output should be easy to use immediately: clear owner, clear next step, and no hidden assumption that someone else has to untangle. One final check: compare the finished result against the original goal in a single sentence. If that sentence is hard to write, the output is probably polished but unfocused. Tighten the goal, remove decorative language, and rerun only the weak section instead of regenerating the entire piece.
FAQ
- Should I let AI generate the metrics themselves? No — paste exact numbers; AI hallucinates math.
- How do I handle confidential data? Use a model with appropriate data controls, or paste only the deltas/percentages instead of absolute numbers.
- Can the AI suggest the “ask”? Yes, but you finalize — the ask reflects your political judgment.
Related
- AI writes KPI narrative
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- KPI Commentary Prompts: 12 Templates for Numbers That Tell a Story
Tags: #Data analysis #Workflow #Research #KPI