Australia's reporting crunch exposes finance's data gaps

The end of financial year may be over for most businesses, but across many finance teams the real pressure is only beginning. Once the reports are lodged, scrutiny follows: auditors, regulators, boards and investors all asking the same question – how much confidence should we have in the numbers?  

The Australian Securities and Investments Commission (ASIC) issued a record AUD 350 million in civil penalties in the second half of 2025 alone, a reminder that control failures are no longer treated as administrative oversights but as governance failures with significant consequences.

For decades, the Office of the CFO has relied on Enterprise Resource Planning (ERP) platforms to provide structured financial records, alongside specialised systems for planning and forecasting. As finance teams deploy artificial intelligence (AI) to boost productivity and address talent shortages, they face a new challenge: ensuring AI strengthens data and control processes rather than amplifying existing gaps.

This is where Agentic Financial Operations offers a new approach to finance – bringing together human expertise and digital agents within a governed operating model designed to improve transparency, control and accountability.

AI ambition outpaces governance 

For finance leaders in Australia, producing reports on time is no longer enough and the bar for accuracy, traceability and accountability has risen sharply. Finance is now expected to deliver information that withstands scrutiny amid AI-enabled decision-making. However, efficiency gains can be offset by additional manual oversight within already stretched teams, or by the risks introduced when that oversight is missed.

Compounding the problem is that many organisations still rely on a patchwork of fragmented data environments that require significant manual effort to reconcile, validate, and report. In fact, 88% of Australian organisations report difficulties integrating generative AI into legacy systems, highlighting how data fragmentation is becoming one of the biggest barriers to trustworthy AI deployment.

While finance leaders are under pressure to identify productivity gains and accelerate digital transformation, introducing AI into poorly governed environments can create new risks around accuracy and auditability.

The organisations best positioned to succeed will be those that can establish trust in their data, maintain visibility over their processes and create the governance foundations needed to support both regulatory expectations and the next generation of finance technology.

Why finance needs explainable AI

Finance leaders have moved past the question of whether to adopt AI. The focus now is on how to unlock its potential within the controls and governance frameworks finance demands.
 
Unlike many other functions, finance cannot treat AI as a productivity shortcut. Every output feeds into numbers that are audited, reported to regulators and relied upon for business-critical decisions – and it is finance leaders who carry liability for their accuracy. If a finance team is unable to show how an AI-driven output was generated, it cannot validate it against accounting standards or defend it under audit. Without that explainability, finance becomes reliant on "black box" AI systems that are difficult to understand, challenge or control. 

Different AI approaches have different strengths within finance workflows. Probabilistic AI can identify patterns and surface insights beyond traditional rule-based systems, making it valuable for complex decisions where context and judgement are required. Deterministic AI, by contrast, applies predefined rules consistently and transparently, making it essential for highly controlled financial processes where accuracy, repeatability and auditability are non-negotiable.

The opportunity for finance is combining the adaptability of AI with essential deterministic controls, auditability and human oversight so finance teams can scale operations without sacrificing trust, accountability or compliance.

Governing a digital workforce 

 As organisations move towards implementing a digital workforce, the fundamental nature of workforce management is changing. In the future, CFOs and finance leaders will manage a hybrid workforce where finance professionals and AI agents collaborate – combining human judgement with the speed and execution capabilities of AI.

CFOs cannot simply measure the success of a digital workforce by the volume of tasks it automates. The real opportunity lies in creating a more controlled way of working: reducing manual processes so finance teams can focus on higher-value analysis, continuously monitoring workflows to identify inconsistencies before they become reporting issues, and maintaining a clear digital audit trail that supports assurance, accountability and confidence in every decision.

Achieving this requires an operating model that ensures AI activity remains transparent, governed and aligned with finance's accountability requirements. Agentic Financial Operations provides this foundation through a 'glass box' AI approach, combining the adaptability of AI with deterministic controls to ensure AI-driven decisions are traceable, explainable and auditable. 

The goal is not to remove finance professionals from the process – it's to give finance a more controlled way to scale judgement, oversight and execution across increasingly complex reporting obligations.

From financial reporting to governed decision-making

As finance enters the era of intelligent orchestration, the CFO is no longer defined only by the ability to report historical performance through periodic cycles, but by the ability to shape decisions as they happen. There is an opportunity to build the capacity for accurate, continuous reporting, positioning finance as a trusted source of strategic insight for the organisation.

Organisations that rush to adopt disconnected, generic AI tools will create new layers of complexity and risk rather than solving existing challenges. Only governed, trusted AI will give CFOs the confidence to scale AI without compromising the oversight required for accurate reporting and decision-making.