6-lesson course · about 6 hours

Use AI for variance commentary without letting it outrun your numbers

For CFOs, controllers, FP&A teams, accountants and finance operations professionals

Everything for Finance teams

Frame the question, check every figure the AI writes about, and explain a scenario where each driver is a stated assumption. Six self-paced lessons on sample tables, with an AI tutor.

Try lesson 1 freeSee what you’ll learn

What you’ll be able to do

By the end, you can…

Frame the question before anyone answers itTurn a vague request like 'why is margin down?' into a framed question that states the reporting period, currency, units and calculation method, ready to paste at the top of a prompt or workpaper.
Calculate a variance a reviewer can followWork out absolute and percentage variances from a sample P&L and budget using a stated sign convention, and show the working so someone else can check it.
Check AI commentary line by lineGive an AI tool your checked figures and a reviewer's brief, then mark each sentence of its output as supported, unsupported or wrong before the note is used.
Tie out a ledger without inventing entriesCompare ledger totals with P&L lines, and document any reconciling item with its amount, location and the evidence still needed, without posting or making up a correcting entry.
Build a scenario comparison with explicit assumptionsChoose a short list of drivers, state each assumption with its value, unit, period and basis, and compare the effect on measures such as profit and cash.
Explain what the figures can and cannot decideWrite a decision-ready explanation that names the assumptions that move the result, how confident each one is, and which decisions still need further evidence or judgement.

How it works

A tutor that meets you where you are

  1. Lessons that adapt to your levelSix lessons across two modules. The material adjusts to what you already know, so an experienced controller and a newer FP&A analyst each work at a useful pace.
  2. An AI tutor you can ask anythingAsk about a sign convention, a reconciling item or a prompt that went wrong, typed or out loud. The tutor works through each exercise with you one-on-one in place of a live trainer.
  3. Quizzes and flashcards for each lessonShort quizzes and flashcards tied to each lesson help you check your understanding of terms, steps and checks before moving on.
  4. Practical outputs on sample tablesYou produce a ledger tie-out, a reconciling item, a variance note, a cash assumption sheet, a forecast cell check and a driver comparison, all from supplied sample data.
  5. Progress tracking and a certificateTrack where you are across the course and receive a certificate of completion when you finish.

Curriculum

The curriculum

The course follows two connected tasks: explaining what changed in a sample P&L against budget, then comparing the choices behind a forecast. Each lesson builds a piece you use in the next.

Module 1Explain what changed3 lessons

  1. 1Frame the financial question
    • Rewrite a vague variance request as a framed question that states period, currency, units and calculation method
    • Identify which sample tables and lines are in scope for the question and which are not
    • Choose what data may go into an AI tool, using only supplied sample tables in an approved tool
    • Write a framing block that can be pasted at the top of a prompt or workpaper
  2. 2Calculate and explain a variance
    • Build a ledger tie-out that compares ledger totals with the sample P&L lines and shows any difference
    • Document a reconciling item with its amount, where it appears and what evidence is still needed, without posting or inventing a correcting entry
    • Calculate absolute and percentage variances for the in-scope lines using the stated sign convention
    • Explain in plain words what each material variance shows and what it does not yet explain
  3. 3Prepare a reviewer’s brief
    • Write a reviewer's brief that sets out the framing, the checked figures, open reconciling items and the known evidence for causes
    • Build a prompt that gives the AI tool the brief and the checked figures and asks it to separate facts from possible causes
    • Test each sentence of the AI output against the calculations and mark it as supported, unsupported or wrong
    • Produce a variance note in which every figure traces to a checked calculation

Module 2Compare the choices behind a forecast3 lessons

  1. 4Define the scenario drivers
    • Choose a short list of drivers for the sample forecast and explain why each matters to the result
    • State the assumption for each driver with its value, unit, period and basis
    • Separate assumption cells from calculation cells in the spreadsheet
    • Build a cash assumption sheet that documents timing assumptions such as collection and payment periods
  2. 5Compare the financial effects
    • Test forecast cells for hard-coded values, broken references and inconsistent units or periods
    • Calculate the effect of each scenario on the chosen measures, such as profit and cash
    • Build a driver comparison table that shows each scenario's assumptions alongside its results
    • Identify which assumptions change the result most and which have little effect
  3. 6Write a decision-ready explanation
    • Write an explanation that leads with the question, the scenarios compared and the key result
    • State which assumptions change the result and how confident each assumption is
    • Explain clearly which decisions the figures cannot make and what further evidence or judgement is needed
    • Check the final explanation against the driver comparison so every figure and assumption traces back

Who it’s for

Made for you if…

Made for: CFOs, controllers, FP&A teams, accountants and finance operations professionals

Controllers and accountants

You tie out ledgers and review commentary, and want a way to use AI that keeps every figure traceable and never papers over a reconciling difference.

FP&A team members

You write variance notes and build forecasts, and want AI drafts that separate facts from possible causes and scenarios where each driver is a stated assumption.

CFOs

You need commentary and scenario packs you can rely on, and want to know what to ask for and what checks to expect before figures reach a decision.

Finance operations professionals

You handle the data behind the reports and want a clear method for framing questions and checking forecast cells before AI is involved.

Questions

Good to know

What do I need to know before starting?

Working knowledge of P&L structure, budget versus actual and common variance terms; spreadsheet skills including formulas, simple lookups and basic tables; and the ability to read a short cash or forecast table.

Do I need a particular AI tool?

You need access to an AI tool your organisation has approved for use with sample data. The course teaches prompting and checking methods rather than one specific platform.

Will I use my company's real data?

No. The course uses supplied sample tables only. Lesson 1 covers deciding what data may go into an AI tool, and live customer data, account credentials or nonpublic reporting information should stay out of unapproved cloud tools.

How long does it take?

About 6 hours across six self-paced lessons in two modules.

Is there a live trainer?

No. You work through the course one-on-one with an AI tutor, which you can ask questions typed or out loud.

Does it cover accounting standards or tax reporting?

No. Accounting standards, policy interpretation and statutory or tax reporting are outside this course, as is building a full budgeting model or long-range planning process.

What comes after this course?

Your checked calculations and explicit assumptions become the foundation for Intensive, where you create proactive reporting agents and learn to hand suitable recurring work to OpenAI Dots or Claude Duet. Hands-on platform practice starts in Intensive, not in this course.

Finance AI Intro: checked variance commentary and scenario assumptions

$197

One payment · lifetime access

  • Six self-paced lessons in two modules, about 6 hours
  • An AI tutor you can ask anything, typed or out loud
  • Quizzes and flashcards tied to each lesson
  • Supplied sample P&L, budget, ledger and forecast tables
  • Six practical outputs: ledger tie-out, reconciling item, variance note, cash assumption, forecast cell check and driver comparison
  • Progress tracking and a certificate of completion

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Refunds: Full refund if you ask before you open your first lesson. Once you’ve started, purchases aren’t refundable, except where the law gives you that right.

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