AI & Content Automation
Prompt patterns for turning raw data into readable business reports
GOSPELTRADER Content Engineering · 27 September 2026 · 7 min read
Quick answer
Give the model the computed figures, not the raw data; tell it the audience and length; require it to quote only numbers you supplied; and ask for a list of claims to verify. These four constraints remove most invented statistics.
Language models summarise well and calculate badly. The safest pattern is to do the arithmetic in a spreadsheet or statistics package, then ask the model to explain results you have already computed.
Four patterns
- • Role and audience: "Write for a non-technical operations director, 200 words."
- • Closed numbers: "Use only the figures in the table below. Do not estimate or round differently."
- • Structure: "Three headline findings, one risk, one recommended next step."
- • Self-check: "After the summary, list every number you used and where it appears in the table."
Always verify
The self-check list makes review a two-minute job: compare each listed number with the source table and correct anything that does not match before the report leaves the team.
prompt engineeringAI business reportAI data summaryLLM prompts for analysis