Let AI draft the first version of your variance commentary, not the final one. It reads the actuals-versus-budget export, the threshold rules and the notes budget owners send back, then writes a short explanation per line. An analyst checks every number against the ledger, fixes the reasons and signs it off before the pack goes out.
#Key takeaways
- Variance commentary is mostly a chasing and writing job, and AI helps with both, as long as the numbers come from your own reports.
- The model should never calculate a variance; your ERP or Excel model does that, and AI only explains what the numbers already show.
- The reasons come from people: budget owners still say why marketing overspent, and AI turns their short replies into consistent sentences.
- A named analyst approves every line before it reaches the CFO, and the draft keeps a link to the source it used.
- If your pack is small and the same analyst writes it every month, a shared prompt and a template may be all you need.
#What does variance commentary week look like for an FP&A team?
The close is done, the numbers are in the board pack template, and the analyst now has a list of lines over the threshold. Each one needs a reason. The reasons sit in other people's heads, so the analyst sends emails and Teams messages to department heads, waits, chases, and then rewrites half-answers into something the CFO can read.
The writing itself is repetitive: timing difference, one-off cost, volume above plan, a hire that started later than budgeted. The hard part is getting the reason and making sure it matches the number. That is why the AFP FP&A benchmarking survey, 2025 found that 61% of respondents named data reliability, and 60% data accessibility, as the challenge holding FP&A back.
#Which parts can AI do, and which stay with the analyst?
- AI can do: pull the lines above your threshold from the export, group them by owner, draft the question to each budget owner, and turn their replies into one or two sentences in the house style.
- AI can also flag a reason that does not fit the number, for example a 'timing' explanation on a line that has been over plan in every period this year.
- The analyst keeps: the threshold rules, the variance calculation, the judgement on whether a reason is credible, and the final wording for the CFO.
- The CFO keeps: the story of the month, what goes to the board, and anything that touches guidance or covenants.
#What does a practical playbook look like?
- Write down your materiality rule: which lines get commentary, by absolute and percentage threshold.
- Export actuals, budget and last forecast from your ERP or planning tool into one fixed layout; do not paste screenshots into a chat window.
- Keep a short style sheet: tense, length per line, words the CFO dislikes, how to name one-offs.
- Collect budget owner reasons in one place, a form or a shared sheet, so the AI reads replies rather than inbox threads.
- Have the AI draft, then the analyst reviews each line against the source figure and marks it approved or changed.
- Measure the drafts kept with light edits, the lines rewritten, and how long the commentary step takes from first export to sign-off.
Start with the simplest version that works. Anthropic, december 2024 advises adding complexity only when it is needed, and commentary is a good example: a fixed prompt over a clean export beats an autonomous agent that wanders through the ledger.
#When is a template or a ChatGPT team plan enough?
If your pack has a few dozen lines, one analyst writes it and the reasons are mostly known, a well-written prompt in an approved tool such as Copilot or ChatGPT Enterprise, plus a commentary template, is enough. You do not need a build. Train the analyst on the rules and keep the export clean.
A build earns its place when there are several entities, many budget owners, commentary in Arabic and English, or a review trail the auditor or audit committee wants to see. Then the chasing, the drafting and the approval need to sit in one workflow with a log, not in someone's chat history.
#How does Stennir run this for a finance team?
Stennir starts with AI consulting when the team is unsure whether commentary is the right first workflow; the AI Opportunity Audit ranks it against invoice intake, reconciliation and collections. When commentary wins, AI implementation builds it into your Excel or planning tool, hosted where your rules require, with the analyst approving every line and every action logged.
AI training then runs the AI Operator Program with your analysts on the real pack, with usage measured before and after. In AI implementation you pay for finished work, and the terms are agreed on the call.
We are
Stennir drafts commentary from your own reports and keeps a named analyst approving every line, with a log the auditor can read.
We aren't
Stennir is not a planning tool you rent, and does not let a model calculate or publish numbers on its own.
#What should a finance lead do next?
Pick last month's pack and count the lines that needed commentary and the reasons you had to chase. That number tells you whether a template or a build fits. See how this sits with the rest of the close at AI for finance and in AI for financial reporting. Then take the free readiness assessment or book a 30-minute call.
#Common questions
Will the AI invent a reason for a variance?
It can, if you let it guess. The build stops that: the AI only writes reasons that a budget owner supplied or that the source data shows, and it marks a line as 'reason missing' when neither exists. The analyst sees those lines first and chases the owner before anything reaches the CFO.
What do you need from us to start?
A recent pack with its commentary, the export it was built from, your materiality rule and the names of the budget owners. One analyst who writes the commentary today explains the steps and the exceptions. You also name who approves the final wording before the pack is sent.
Does it work in Arabic?
Yes. Stennir builds and trains in Arabic and English, so the draft can be written in either language or both, side by side. Finance terms are checked against your own glossary, so a line reads the way your board expects rather than as a literal translation of the English draft.
Where does our financial data stay?
In your own accounts and the hosting region your rules require. Stennir does not copy your ledger or results into its own systems. The model reads the export through access you grant and can revoke, and you keep the accounts, the data and the off switch when the work ends.
