Management pack preparation
Source reports + commentary → first-pass management pack → CFO review.
Compress the work around the numbers.
Finance and administration teams carry some of the most repeatable document, reporting and coordination workflows in an established business. Identify focuses AI on preparation, reconciliation, exception handling and management insight while keeping financial accountability with people.
FN/
AUSTRALIA / APPLIED AIMonthly cycles, invoices, reconciliations, recurring reports, approvals and document movement create a large amount of work around the actual financial judgement. That surrounding work is often the most practical place to start.
Buyer: CFO · Finance Director · Head of Administration
01 / WHERE TO START
Three workflows worth testing first.
These are not universal prescriptions. They are practical starting patterns with a clear owner, observable work and a measurable outcome.
Invoice / document intake
Incoming documents → extract → classify → validate → route.
Reconciliation exception workflow
Compare sources → flag discrepancy → reviewer action.
02 / 12 WORKFLOWS
Go deeper than a list of AI tools.
Every workflow is framed as work moving from input to action. That is what lets us map systems, context, human review and the business measure behind it.
Management reporting
Source data → narrative → packInvoice intake
Document → extraction → validation → routeReconciliation support
Sources → differences → exception listExpense administration
Submission → policy checks → reviewerBudget commentary
Actual vs plan → drivers → draft commentaryCash / receivables review
Ageing → priority → follow-up supportBoard pack preparation
Inputs → structure → review-ready packContract / renewal calendar
Document → dates → obligations → remindersProcurement administration
Request → policy → workflowRecurring data movement
System → validate → destinationAudit evidence preparation
Request → evidence retrieval → packFinance knowledge assistant
Policy / process → grounded answerThe workflow is the product.
A useful implementation defines five things before it ships: the trigger, the business context, what AI is allowed to do, where a person owns the decision, and what happens when the normal path fails.
TRIGGER→CONTEXT→AI ACTION→HUMAN OWNERSHIP→EXCEPTION→MEASURE
04 / WHAT TO MEASURE
AI usage is not the outcome.
Use operating measures that already matter to the function, then compare the new workflow against a baseline.
01Close-cycle time
02Preparation hours
03Exception resolution time
04Reconciliation backlog
05Reporting latency
06Data-entry volume
07Error rate
08Review effort
Keep accountability visible.
Automation should make the operating boundary clearer, not hide it.
Final financial approvalPayments without authorised controlsMaterial accounting judgementSensitive payroll / employee decisions without appropriate access
06 / FIRST 90 DAYS
Map. Build. Activate.
Map
Choose the business outcome. Baseline the current workflow. Map systems, data, handoffs, exceptions and ownership. Rank the first opportunities by value and feasibility.
OUTPUT: first implementation briefBuild
Design against real context and systems. Define permissions, human review, governance and exception paths. Test with the people who run the work.
OUTPUT: production-ready workflowActivate
Launch, train, measure, fix the operating design and capture the reusable pattern. Use the evidence to choose the next workflow.
OUTPUT: live workflow + outcome evidenceShow me what AI could change in my department.
Select your team, size and pain point. Identify will generate five workflow opportunities, the impact dimensions to test and a recommended starting point.
RUN THE FINANCE & ADMINISTRATION FINDERFORTNIGHTLY AI BRIEFINGWhat matters in applied AI.
What matters in applied AI.
Without the noise.
Practical AI workflows, implementation lessons, Australian market signals, governance notes and upcoming Identify events for leadership teams.
Where should Finance & Administration start with AI?
Start with a repeated workflow that creates visible friction, has a clear owner and can be measured before and after. The strongest first move is usually not the most ambitious use case. It is the one that proves the organisation can Map, Build and Activate a useful change.
Do we need to replace our existing systems?
Usually not. Identify designs around the systems, data, permissions and workflow already in the business. The first question is where AI should sit in the operating model, not which platform should replace everything.
What should we measure?
Use the measures already used to run the function: time, cycle time, throughput, service, conversion, quality, exceptions, cost to serve or another agreed business outcome. AI usage on its own is not the result.
What should AI not own?
Material decisions, sensitive judgement and exceptions need clear human accountability. The exact boundary depends on the workflow, risk and industry.