of 7— Gather your raw inputs before opening AI

What you'll accomplish

By the end of this guide, you'll have a repeatable workflow for producing quarterly and annual performance reports in 40–50% less time — using AI to turn raw data and notes into polished draft narratives, then refining them into report-ready language. This turns a 6–8 hour task into a 2–3 hour one.

What you'll need

A Claude account (claude.ai) or ChatGPT account — free tier works, paid tier handles longer documents
Your program's performance data (metrics, KPIs, milestones) in any format — Excel, Word, email summaries
Last period's report as a reference for style and format
Your agency's OMB-required performance indicators and targets (from your APR template or strategic plan)
Time needed: 45 minutes to set up and run your first report; 2–3 hours per reporting cycle thereafter
Cost: Free; ~$20/month for the paid plan if you need longer document handling

How-To Guide: Build an AI-Assisted Performance Report Workflow

Step 1: Gather your raw inputs before opening AI

Before using AI, assemble everything you need in one place. This "inputs first" step prevents going back and forth mid-draft.

Checklist of inputs to gather:

Quantitative metrics: actuals vs. targets for each performance indicator this period
Milestone status: which milestones were achieved, which were delayed, which are on track
Narrative notes: any significant events, program changes, or external factors that affected performance
Challenges: what went wrong or below target, with explanation
Prior period report: the equivalent section from your last report (for continuity and formatting reference)

Tip: Even rough notes work. "Grant processing time was 22 days vs. 18 day target because of system outage in January" is enough for AI to draft a professional narrative.