Artificial intelligence (AI) is helping businesses streamline their financial tasks. Using AI carefully is lawful and can be very productive. Directors should understand the systems as, under the law, they remain accountable for the outcomes and compliant usage.

After struggling with outdated spreadsheets and unstable supply chains, a global manufacturing company improved its cash flow forecasting using AI. The finance team implemented an AI-powered tool to integrate real-time data from procurement, sales, and inventory systems. The AI model identified a recurring cash shortfall in the third quarter that had previously gone unnoticed. Consequently, the CFO adjusted supplier payment terms and restructured short-term financing, resulting in a 15 per cent improvement in working capital and reduced borrowing costs. This illustrates the growing trend of finance teams leveraging AI for better decision-making.

Bookkeeping tools use machine learning to sort transactions, reconcile accounts, and identify errors. Xero is the most widely used accounting platform among small businesses in Australia. Its Analytics Plus feature, available on premium plans, provides AI-driven insights such as cash flow projections and trend analysis. While Analytics Plus is not yet widely adopted, it is gaining traction among businesses seeking increased automation and deeper financial visibility.

Cash flow forecasting tools, like Float and Fathom, use historical data and real-time inputs to model future movements. These tools help finance teams anticipate shortfalls and plan more confidently.

Expense management tools, such as Expensify and Dext Prepare, scan receipts, extract details, and check for duplicates. They reduce manual entry and improve accuracy, especially when integrated with accounting software.

Accounts payable and receivable tools, like ApprovalMax and Lightyear, match invoices to purchase orders and enforce approval processes. These systems help prevent unauthorised payments and support internal controls.

Fraud detection and audit tools, such as MindBridge Ai and CaseWare IDEA, analyse transaction data to identify outliers and patterns. They support internal audit functions and reduce reliance on manual sampling.

Most of these tools do not use large language models (like ChatGPT). Instead, they focus on business automation, data analytics, and APIs to integrate with accounting systems. While these tools can improve efficiency, implementing new systems carries risks, such as upfront costs, staff training, and potential workflow disruptions. Businesses should ensure that a tool aligns with their internal controls and reporting obligations, as over-reliance on automation without proper oversight may lead to errors or compliance issues. A clear implementation plan with professional advice is essential.

Financial professionals should identify where AI can improve accuracy and control, choose transparent, auditable, and legally compliant tools, and implement monitoring. If AI aids financial decisions, directors must be able to explain those choices. With the right approach, AI can be a huge asset without being a speculative risk.