Monthly client reports are important, but they are often repetitive. Someone has to collect metrics, compare them with last month, explain changes, add commentary, format slides or PDFs and chase missing data.
Useful AI assembles the boring first draft. It should not replace the consultant’s judgement or invent explanations for results.
Example workflow: preparing a monthly performance report
An agency exports approved figures from Google Sheets, analytics tools and the CRM. An AI agent reads the previous report template, checks the latest numbers, highlights changes and drafts plain-English commentary. It also flags missing data, unusual movements and questions the consultant should answer before the report goes to the client.
What the agent would use
- Google Sheets or Excel
- Analytics exports
- CRM data
- Previous report template
What it would produce
- Draft report
- Wins and issues
- Charts or graphs
- Questions where data is missing or unusual
Where human approval fits
The consultant reviews the figures, adds judgement and decides what the client should be told. AI should prepare the draft, not provide unreviewed advice.
Likely saving and risk
Likely saving: 1 to 4 hours per report.
Risk level: medium. The biggest risk is confident commentary based on incomplete or misunderstood data.
Practical guardrails
- Use approved data sources only
- Flag anomalies rather than explaining them automatically
- Show the source of each figure
- Keep a review step before any report is sent
A sensible next step
If reporting is eating into delivery time, Stuart Cole Consulting can help you identify which parts are safe to automate and which parts should stay with your team.
