AI to transform the future of finance

For years, finance leaders have been asked to produce faster, more reliable information while maintaining control, accountability and confidence in the numbers. In most boardrooms, finance is still expected to explain yesterday’s performance.

By the time monthly reports are finalised, the underlying business may already have changed. Customer demand may have shifted, inventory may be building in the wrong locations, and cash collections may no longer reflect assumptions made only weeks earlier.

Mohammad Mudasser, partner of Deals Transformation at PwC Vietnam

The question confronting CFOs is whether AI can help finance identify those changes while there is still time to act. More fundamentally, can it help finance move beyond reporting performance to shaping business decisions?

For CFOs, that value will not be measured by the number of tools introduced or processes automated, but by whether AI helps finance identify emerging issues, test scenarios and bring financial and operational information together in time for management to act.

Early investment in AI for finance has focused largely on productivity: automating reports, extracting information, accelerating reconciliations, and reducing repetitive work. These improvements remain valuable, particularly where finance teams spend more time preparing information than interpreting it. But they represent only part of the opportunity.

In our experience, the constraint is rarely the absence of technology. More often, finance, sales and operations are working from different assumptions. A forecasting model may assume inventory is available for sale, while commercial teams know certain stock has already been committed. Credit exposure may appear manageable in finance reports while sales teams are negotiating payment extensions. Introducing AI into that environment can accelerate analysis, but it can also accelerate disagreement.

One misconception is that AI changes finance because it produces better answers. In reality, it changes finance because it changes when questions can be asked. Instead of waiting until month-end to identify a problem, management may be alerted while corrective action is still possible. The challenge then becomes organisational rather than technical: who owns the decision and what happens next?

AI-enabled finance function

An AI-enabled finance function should be judged not by the number of tools it has purchased, but by whether it gives decision-makers better information when it matters. In practice, AI could alert treasury to collection risks, help the financial planning and analysis team test changing assumptions or direct controllers towards unusual transactions.

Treasury and working capital are practical starting points because the outcomes are concrete and measurable. By combining payment behaviour, sales and purchasing data, inventory movements and operational assumptions, AI can flag cash receipts at…