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AI for Finance Teams

Hands-on AI for finance, with the controls-and-risk discipline carried over from our regulated-industry work.

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Finance teams are being asked to do more with AI, but most of the available training skips the controls that finance work depends on. This session shows your team where AI genuinely saves time across analysis, reporting and forecasting, and pairs every use with a check on whether the output can be trusted. The discipline comes straight from regulated-industry work.

Who it’s for

Finance, FP&A and controllership teams.

What your team walks away with

Apply AI across finance work with the right controls — and spot where its output should not be trusted.

Why this matters now

AI tools now sit one click away in the spreadsheets and systems your team already uses, so adoption is happening with or without guidance. The danger is that a confident-sounding but wrong AI answer slips into a report or a forecast, and confidential figures get pasted into tools that keep them. Getting the controls right now protects the numbers your decisions rest on.

What you’ll learn
  • Identify the finance tasks where AI saves real time today, with practical examples
  • Use AI to support analysis, reporting and forecasting without losing rigour
  • Apply controls that keep AI output trustworthy enough to rely on
  • Draw a clear line on what financial information must never be pasted into a chatbot
  • Check AI work properly before it feeds into a number or a decision
  • Leave with a controls-aware AI playbook built for finance workflows
Curriculum

  1. Where AI saves finance teams real time today

    • Which routine finance tasks AI can genuinely speed up, and which it can't
    • Drafting commentary, summarising long documents and tidying messy data
    • Categorising transactions and pulling figures out of statements
    • Spotting the 'Excel ceiling' — when spreadsheets stop scaling and AI helps
    • Quick wins your team can try the same week

  2. Analysis, reporting and forecasting with AI assistance

    • Generating first-draft variance commentary from the numbers
    • Summarising trends and performance for executives and stakeholders
    • Supporting budgeting, scenario and sensitivity analysis without coding
    • Ratio, vertical and horizontal analysis with AI as a second pair of eyes
    • Using AI to draft forecasts while keeping ownership of the assumptions

  3. Writing prompts that get useful finance output

    • The anatomy of a good finance prompt: role, task, context, format
    • Giving the tool the right figures and constraints to work from
    • Asking for output in tables, summaries or commentary you can reuse
    • Iterating when the first answer misses, instead of accepting it
    • Building reusable prompt templates for recurring finance jobs

  4. The controls that keep AI output trustworthy

    • Treating AI output like any other input that needs a control around it
    • Where a human review is mandatory before a number is used
    • Catching numerical inconsistencies and broken logic in AI work
    • Keeping a clear trail of what AI produced and who checked it
    • Carrying a controls mindset from regulated work into everyday finance

  5. Confidentiality: what never to paste into a chatbot

    • The financial information that must never go into an outside AI tool
    • Public chatbots versus approved enterprise tools, and why it matters
    • Understanding when a tool may keep or learn from what you type
    • Safe ways to work with sensitive figures without exposing them
    • Simple team rules everyone can remember and follow

  6. Checking AI work before it reaches a decision

    • Why a confident, fluent answer can still be wrong
    • A quick verification routine for AI-assisted analysis and reports
    • Cross-checking AI figures against the source data
    • Spotting hallucinated facts, stale data and false precision
    • Knowing when AI assistance is good enough — and when to start over

  7. A practical finance AI playbook

    • Pulling approved use cases, controls and rules into one reference
    • A starter prompt library for common finance tasks
    • A short 'what to check' list for any AI-assisted output
    • The confidentiality do's and don'ts on a single page
    • A playbook your team can adopt and keep building on

Bring "AI for Finance Teams" to your team.

A short conversation about your team, your risk, and the session that would move them. No pitch deck — just the right scope and dates.

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