Skip to content
AI implementation for finance teams · Free advisory session

What should your finance team automate with AI?

Book a free 30-minute advisory session with a Finance AI FDE: an engineer who is also a finance expert. You'll leave knowing which workflows are worth automating, what's feasible with your data and controls, and what it would return.

42%
of finance activities can be fully automated
+19%
can be mostly automated

McKinsey, "Bots, algorithms, and the future of the finance function", 2018. Activity-level estimates; your potential depends on your workflows.

  • Free, 30 minutes
  • No obligation
  • A finance expert, not a sales pitch
Book your free advisory session

Find out what's worth automating.

Step 1 of 2 · A free 30-minute session with a Finance AI FDE.

Privacy notice
About 2 minutes · No financial files needed.
01

What a Finance AI FDE can automate for you.

These are the workflows finance teams most often bring to their first session. For each one: what gets automated, and what deliberately stays with your team.

Close

Month-end close automation

Automated
Subledger to GL tie-outs, reconciliation prep, close status tracking
Stays with your team
Investigating differences, sign-off
Start with this →
Reporting

Budget variance analysis & reporting

Automated
Refreshing actuals, building the pack, drafting commentary
Stays with your team
Confirming causes, approving the narrative
Start with this →
Cash

13-week cash forecast

Automated
Collecting inputs, refreshing the 13-week view, forecast vs. actuals
Stays with your team
Assumptions and timing judgment
Start with this →
AP

AP automation

Automated
Invoice coding, PO matching, chasing approvals
Stays with your team
Exceptions and payment approval
Start with this →
Tailored

A solution built around your needs

Automated
Your own recurring process: data connections, checks and outputs designed around how your team works
Stays with your team
Defining what good looks like, approving the result
Start with this →
A closer look · Illustrative

Less report assembly. More time explaining the business.

A monthly reporting pack, before and after a scoped implementation.

TodayExport files → reconcile spreadsheets → write commentary from scratch → review.
AfterInputs refresh → defined checks run → a draft linked to the source numbers → finance approves.
Your team stays in controlUnexplained movements stay flagged. Totals are checked. The reviewer owns the final narrative.

Not sure where your hours go? Estimate them with the Time Waste calculator →

02

An engineer who thinks like a Controller.

A Finance AI FDE (forward deployed engineer) is a finance expert who also builds. They work alongside your team to take one workflow, such as the close, variance commentary or the reporting pack, from manual to automated, inside the governance and controls finance already runs on.

Finance AI often stalls when the builder doesn't know finance. A Finance AI FDE starts from how your month actually runs.

Knows the close calendar

Builds around your deadlines, cut-offs and the week everything has to tie out.

Designs for audit

Every number traceable to its source, with a log of what ran and who approved it.

Respects your controls

Segregation of duties, approval limits and review steps stay exactly where they are.

Speaks finance, not tech

Materiality, accruals, flux and FX revaluation, not just prompts and pipelines.

The free advisory session

30 minutes. A clear answer on what's worth automating.

Bring one or two workflows that eat your team's time. You'll leave with a straight view of whether AI is the right answer, and what it would take.

  1. 1What's worth automating. Your workflows ranked by time saved and effort.
  2. 2What's feasible. With your data, your systems and your controls as they are today.
  3. 3What it would return. Hours back each month, and what stays with your team.
  4. 4What it would take. Scope, timeline and the people involved, before any commitment.
03

Why finance teams choose an FDE.

Compared with the other ways finance teams try to get AI working.

ApproachWho buildsWhat you end up withMain risk
Finance AI FDEA finance expert who builds, next to your teamOne live workflow with checks, documentation and a handoverDependency, if the handover is skipped
Traditional consultantAdvisors; the build often goes to IT or a third partyA roadmap and recommendationsThe plan never reaches production
Software aloneYour team configures itA platform and templatesA licensed tool and an unchanged workflow
Do it yourselfOne analyst with ChatGPT or Claude and ExcelPrompts and spreadsheetsNo controls; it leaves with the person
04

AI implementation, step by step.

If you decide to go ahead, a first workflow typically runs like this.

How an engagement typically runs

  • Scope one workflow. The data it needs, who reviews it, and what done looks like.
  • Build with your data. Connect the sources, build the steps and the checks.
  • Run alongside your process. Side by side with the manual version until the numbers match.
  • Hand over. Documentation, a runbook and training for the people who run it.

Exact plan, timeline and price are agreed before you commit.

Built to be owned by your team

  • Every step and rule documented, so it can be checked and changed.
  • A month-end runbook your team can follow without the builder.
  • Review and sign-off stay where they are today.
  • Your team trained to operate it. The Academy covers the basics.
  • Clarity on what it costs to keep running.
05

Is the session a fit?

A good fit if

  • A workflow repeats every month or more often and eats real hours.
  • Your data sits in Excel and an ERP.
  • Someone on your team would own the workflow once it's automated.
  • You'd like to see results this quarter, not in two years.

Start elsewhere if

06

Questions

Straight answers, including the commercial ones.

Find out what's worth automating. In 30 minutes, for free.

A finance expert, your workflows, and a straight answer.