The Finance Team Blueprint for FY27: What to Hire First (and What to Automate)

Nearly one in three finance job ads in Australia now list AI skills as a requirement. Ask the hiring manager what that actually means in practice and the answer usually trails off somewhere around “comfortable with new tools.”

That is where finance hiring sits in August 2026. Everyone agrees AI needs to be part of the team. Almost nobody has done the thinking about what that actually changes regarding who they need to hire, and for what.

This matters right now because FY27 headcount is being locked in. The EOFY dust has settled, budgets are signed off, and a lot of finance leaders are about to go to market with job descriptions that are last year’s role plus a bullet point about AI. That is not a strategy. It is a placeholder for a decision nobody has made yet.

“AI skills” is not a requirement. It’s an admission.

When a brief lists “AI skills” without specifying what the person will actually do with them, it usually means one of two things. Either the business hasn’t worked out which parts of the finance function should be automated, or it has, and hasn’t worked out what that leaves for a human to do.

Either way, that ambiguity ends up in the shortlist. Vague briefs produce vague candidates. I see it constantly: a spec that lists every buzzword going gets applications from people who are confident with buzzwords and thin on the actual judgment the role needs. Good candidates, the ones with real options, tend to read a woolly brief as a sign the business hasn’t thought it through, and they self-select out. You end up interviewing the wrong six people for the wrong reasons.

The shortage isn’t where most people are looking

The data backs this up. Junior and graduate-level finance roles in Australia are reasonably well supplied. The genuine scarcity sits at manager level and above: FP&A, commercial finance, tax, senior audit. These are the roles taking longest to fill, and they are also the roles least likely to be replaced by a tool.

That is the part getting missed. Businesses are chasing “AI-fluent” hires broadly, when the actual bottleneck is commercially sharp, senior judgment. AI does not replace someone who can sit across from a sales director, pull apart a pricing decision, and tell them honestly why the margin story does not add up. It might do the modelling faster. It will not have that conversation.

Automate the plumbing. Hire for judgment.

The businesses getting FY27 planning right are doing a genuinely simple exercise: listing what the finance function needs to deliver over the next twelve months, then sorting each piece into one of two buckets.

Automate or outsource: reconciliations, standard month-end reporting, expense processing, most of the transactional workload. This is where AI tools and better systems earn their keep, and where the productivity case is real and immediate.

Hire for: forecasting that the business actually trusts, commercial storytelling, stakeholder influence, and the judgment calls that come with genuine ambiguity. This is where a person, not a tool, is the answer.

The temptation is to try to hire your way to both at once, by finding one “AI-fluent” senior person who can do the modelling and the judgment. That person is expensive, rare, and usually better used building capability in the team you already have than being hired in from outside. The Gartner data on this is blunt: the businesses actually closing the AI skills gap are mostly upskilling existing staff, not importing them. External hiring for this specific mix is slow, costly, and often disappointing when it lands.

Get the structure right before you go to market

None of this is complicated, but it does take doing before the job ad goes up, not during the third round of interviews when it becomes obvious the brief was wrong.

At Recruitment Labs, we tend to see the best outcomes when the structure, the split between what’s automated and what’s hired, and the actual decision the new person needs to improve, are worked out before the market is engaged. Everything downstream gets easier: the brief is sharper, the shortlist is stronger, and the interview process actually tests the right thing.

The takeaway

FY27 headcount decisions are being made now, over the next few weeks, while the memory of budget season is still fresh. Get the split right at this stage and the hiring process that follows is straightforward. Get it wrong, bolt “AI skills” onto an unchanged job description, and you’ll be back in the market in six months wondering why the shortlist was thin and the hire didn’t stick.