From AI Ambition to Execution: Lessons from Workiva Accelerate APAC

In 2023, AI adoption across finance functions climbed from 37% to 58%. Then it stalled. Gartner's 2025 survey found adoption had inched to just 59% over the following year, even as two-thirds of finance teams already using AI reported greater optimism about it than they had the year before[1] Confidence is rising. Action is not. That widening gap between belief and behavior was the defining theme of this year's Workiva Accelerate events across APAC, with VantagePoint joining finance leaders in Sydney and Melbourne to take the pulse of the Australian market.

The headline most expect from an event like this is AI. The more revealing story was hesitation.

A confidence gap, not a conviction gap

Few finance leaders doubt that AI matters. The difficulty lies in execution. "A lot of CFOs are frozen," says Matt Benaron, CEO of VantagePoint. "It's not that they doubt AI matters. They don't know where to start, what good looks like, or how to turn something they conceptually understand into something they're willing to back and deploy in a real business case."

That uncertainty is freezing decisions across the region, and it is rational more often than not. With the landscape shifting so dramatically inside any six-month window, a number of teams have made a deliberate choice to hold position and reassess later.

Three broad postures emerge as a result. At one end are the teams continuing along a traditional route, who will benefit from vendor innovation whether they actively engage with it or not. At the other are the teams that have stopped entirely, persuaded that buying anything today is premature when they could build or wait. In the middle sits the largest group of all: aware that the ground is shifting, but without the confidence or knowledge to move, and so doing nothing

The pendulum is swinging back

Underlying all three is a structural shift in how finance functions think about build versus buy. Organizations once built everything in-house. They then moved to buy SaaS for almost everything. A quieter reversal is now underway, back toward building internally, because the tools have finally made it viable.

Both ends of that spectrum carry merit, and both carry cost. "Going all in on building with AI drives a mentality shift in your team that's genuinely valuable," Matt notes. "You experiment, you take small chunks, you spread it as democratically across the team as you can, and you learn a lot. You get to a better result even when you can't quite describe that result yet." That approach is also expensive, and it sits awkwardly inside governance structures that demand everything to be clearly categorized. The disciplined route has its own logic. Many CFOs operate within accountability structures that require tangible results rather than experiments, and a large share of finance functions remain far enough behind that a methodical approach is itself a strong foundation. The deciding factor is vendor choice. A platform investing with the right trajectory offers close to the best of both worlds: the de-risked ability to execute, alongside an AI roadmap the organization does not have to invent itself.

Why finance still needs technologists

A persistent misconception is that AI removes the need to understand the underlying technology. The reality is the opposite. "The moment you've done any of this hands-on, you see it stall, fail, and do things in a bizarre, sub-optimal way," Matt observes. "Understanding the building blocks is what lets you give that final bit of direction that makes it do the right thing in the right way. It's also your protection against being misguided, and AI is very good at affirming your existing thinking rather than challenging it." The shift this demands is counterintuitive: less technical on the surface, more technical underneath.

The unlock most teams overlook

The most striking observation from the events had nothing to do with AI. It was the sheer number of finance teams still operating with no strategy at all, consumed by keeping the lights on and unable to find time to build a plan, let alone work within one. "If you're still buried in manual work, you'll never find the time to capitalize on any of this," says Matt. "For most teams the biggest unlock isn't AI. It's creating the time first, then diving in."

From ticking the box to taking it further

This is where implementation expertise becomes decisive. Selecting a platform such as Workiva is the starting point, not the outcome. The same deployment can deliver a little value or a great deal, and it can be done poorly. Technology implemented badly ranks among the most expensive mistakes a finance function can make.

Statutory reporting illustrates the range. At a basic level, the platform makes the statutory report more automated and efficient than before. A level beyond that, it returns days of capacity to the team, with clear guidance on where to redirect that time and with controls and risk management built directly into the process. The fullest version goes further still: during implementation, the team steps back and reshapes the platform into a genuine financial reporting hub, drawing in diverse data so it powers several functions rather than the single task it was originally brought in to address. "That's the difference between ticking the box and taking it a hell of a lot further," says Matt Benaron, CEO of VantagePoint.

For teams choosing to pause and assess the market properly, the strategy is legitimate but carries a hidden cost. Assessment consumes time many teams do not have, and the value being pursued recedes further the longer it runs. The right expertise compresses months of deliberation into a far shorter path, so the destination stops moving away.

The takeaway from Sydney and Melbourne is straightforward. Before committing to AI, organizations should buy themselves the time to use it well. Establish the plan, bring the manual work under control, and then move.

References

[1] https://www.cfodive.com/news/cfos-ai-adoption-slows-challenges-mount-gartner/805949/