# AI reporting automation that gets the right numbers to managers faster

> Managers waiting while someone rebuilds the same report from spreadsheets? APPSOLN automates regular reports from your existing data, with AI drafting the notes and people making the calls.

Weekly and monthly reports often mean exporting spreadsheets, fixing numbers that do not match, and rewriting the same commentary. Decisions wait while someone pulls it together.

## How the work is done today

- Someone exports data from several systems.
- Numbers are matched up in spreadsheets by hand.
- Commentary is written just before the meeting.
- Questions in the meeting send people back to find missing details.
- Actions are noted loosely and forgotten until next time.

## Where AI can help

- Build regular reports from approved data
- Highlight what changed and what looks unusual
- Draft commentary for a person to edit
- Answer simple questions from connected data
- Track actions from one report to the next

## Where AI should not be trusted

- Decide which number is right when your systems disagree
- Replace formal finance controls or accounts
- Make strategy decisions for you
- Make up for metrics nobody has defined

## Systems

- Data warehouse or BI tools
- ERP
- CRM
- Project or operations trackers
- Spreadsheets

## Human review

Managers and analysts stay responsible for what each number means, whether the commentary is accurate, and any decision about budget, people, or customers.

## Security and access

Only approved data with agreed definitions is used. Draft commentary is kept separate from the published report, and sign-off is logged.

## Integration approach

- **Agree the definitions.** Agree the numbers, who owns them, and where they come from before automating anything.
- **Automate the build.** Pull approved data into the report automatically instead of rebuilding it.
- **Draft the notes.** AI drafts summaries and flags unusual changes for a person to review.
- **Track actions.** Carry decisions and owners into the next report so nothing is forgotten.

## Governance

- Only approved data with agreed definitions is used
- Sources are shown next to AI-written statements where possible
- Draft commentary is kept separate from the published report
- Who signed off each report is logged

## Measures

- Hours spent putting reports together
- Time from month-end to a report ready for decisions
- Number of arguments about what a number means
- Actions completed between reports

## Typical sequence

- **Weeks 1–2.** List who reads each report, the numbers used, and where time is lost.
- **Weeks 3–5.** Automate one regular report with commentary a person edits.
- **Weeks 6–8.** Add unusual-change alerts and action tracking.
- **Weeks 9–12.** Extend to other reports with clear definitions and owners.

## What you leave with

Expect to agree what each number means first, then automatic assembly of one regular report with commentary a person edits. It never becomes the only copy of your numbers.

## Common questions

### Will AI make up our numbers?

No. We agree definitions and sources first. AI works only on approved data, and people stay responsible for published figures.

### Does this replace our BI tool?

Usually not. It saves time building reports and writing notes from the data you already trust.

### Who signs off the report?

Named managers or analysts. Draft notes stay separate from the final report until someone approves them.

Canonical page: https://appsoln.com/solutions/reporting-decision-support