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These headline numbers, however impressive, are only part of the story. What matters equally is what is happening inside the boardroom. CFOs across the globe have undergone a striking change in their orientation toward AI. According to a Salesforce study, 70% of CFOs described themselves as ‘conservative’ on AI<\/a> as recently as 2020. By 2024, that figure had collapsed to just 4%. Today, 33% of CFOs describe their approach as ‘aggressive’. The sceptic has become the champion. <\/p>\n\n <\/p>\n\n Meanwhile, 96% of global CFOs and senior finance leaders now prioritise integrating AI into their business operations<\/a>, with 63% classifying it as a high priority, while 60% of CFOs believe AI will be one of the most impactful technologies in the finance function<\/a> over the coming years.<\/p>\n\n <\/p>\n\n The single most consistent theme across CFO surveys is the desire to remove manual, repetitive work from the finance function. Accounts payable processing, bank reconciliations, invoice capture, journal entries and expense management are all in scope. <\/p>\n\n <\/p>\n\n One CFO at a multinational packaging manufacturer, quoted in L.E.K. Consulting’s 2025 Office of the CFO Survey<\/em>, described the impact of early AI adoption on cash flow management: it had ‘greatly increased productivity, enabled better forecasting and lowered costs.’ Another CFO at Fanatics Betting and Gaming noted that automating accounts payable workflows had reduced month-end close tasks that previously took 20 hours per month to just two hours. <\/p>\n\n <\/p>\n\n Fifty per cent of CFOs cite ‘digital transformation of finance’, primarily through automation, as their single top priority for 2026<\/a>, while 49% say automating processes to free employees for higher-value work is their top priority for finance talent strategy.<\/p>\n\n <\/p>\n\n Economic uncertainty, from geopolitical tensions to shifting trade policies, has made accurate forecasting both more valuable and more difficult. CFOs across the region are turning to AI-driven predictive models and scenario planning tools to build resilience into their financial outlooks. <\/p>\n\n <\/p>\n\n Machine learning-based forecasting allows finance teams to run dynamic cash flow scenarios using historical patterns and real-time inputs. Unlike static spreadsheet models, AI systems can simultaneously process multiple variables, including currency movements, supply chain signals, and customer payment behaviour, helping surface early warnings before they become balance sheet problems. <\/p>\n\n <\/p>\n\n The month-end close is one of the most labour-intensive and error-prone processes in any finance team. For businesses operating across multiple Southeast Asian markets, each with its own tax rules, currencies and regulatory requirements, the complexity compounds significantly. <\/p>\n\n <\/p>\n\n AI-driven reconciliation tools, now embedded in leading ERP platforms, can match transactions automatically at rates approaching 98%, flagging only genuine exceptions for human review<\/a>. The shift from a reactive, end-of-period scramble to a continuous, AI-monitored close is one of the most consequential changes CFOs can make to the operational tempo of their finance function. <\/p>\n\n <\/p>\n\n CFOs are increasingly expected to serve as strategic advisers to the business, not just custodians of the ledger. That role requires access to financial insights in near real time, the ability to drill into anomalies, and the ability to communicate findings clearly to non-finance stakeholders. <\/p>\n\n <\/p>\n\n Generative AI tools that can transform dense financial data into plain-language narratives, chart summaries and executive briefings are gaining rapid traction. One key statistic illustrates the scale of the productivity opportunity: generative AI currently saves daily users an average of 4.4 hours per working week, according to Deloitte’s Asia-Pacific survey of 11,900 individuals<\/a>. When that saving is concentrated in a finance team already under pressure, the impact is material. <\/p>\n\n <\/p>\n\n Perhaps the most strategically significant finding from recent CFO research is where finance leaders prefer AI to live: inside their existing ERP platforms, not as standalone tools that require integration and create data silos.<\/p>\n\n <\/p>\n\n L.E.K. Consulting’s 2025 CFO study found an overwhelming preference for AI capabilities embedded within broader finance or ERP<\/a> platforms. Embedded AI requires less IT effort, integrates with existing workflows, delivers faster time-to-value and preserves the familiar interfaces that finance teams have invested years in learning. For finance leaders evaluating AI strategy in 2025 and 2026, the choice of platform is therefore inseparable from the choice of AI. <\/p>\n\n <\/p>\n\n The investment case for AI in the finance function rests on a clear set of expected outcomes. CFOs are not pursuing AI as an exercise in technological novelty; they are seeking measurable returns across several dimensions. <\/p>\n\n <\/p>\n\n In a Salesforce survey of CFOs, 74% estimated that AI agents would cut costs or boost revenue by up to 20%<\/a> in their operations. Bain and Company’s research shows that more than half of CFOs plan to increase enterprise-wide AI investment by more than 15% in 2025, with 83% planning budget increases above that threshold over the next two years<\/a>. The expectation of a meaningful return is driving this commitment. <\/p>\n\n <\/p>\n\n Speed and accuracy are the twin engines of strategic finance. CFOs who have already adopted AI consistently cite ‘increased speed of analysis’ as the primary benefit. Companies that have fully scaled AI in finance report satisfaction rates of 41%, compared to just 25% among those still in pilot mode<\/a>. <\/p>\n\n <\/p>\n\n With AI continuously monitoring financial transactions, the prospect of detecting errors, fraud signals, and compliance breaches in real time, rather than discovering them during periodic reviews, marks a qualitative shift in financial governance. CFOs operating across Southeast Asia’s diverse regulatory environments place particular value on this capability. <\/p>\n\n <\/p>\n\n AI exception management tools that continuously scan financial data, identify anomalies and recommend corrective actions are now available as native features within leading ERP platforms. For finance leaders managing entities across Thailand, Indonesia, Malaysia, the Philippines and Vietnam simultaneously, the governance benefit is not incremental; it is transformative. <\/p>\n\n <\/p>\n\n Perhaps the most human outcome of AI in finance is the reallocation of talent away from manual processing and toward strategic work. Deloitte’s research shows that 64% of finance employees believe their tasks will be automated<\/a> or augmented within five years. The CFOs who manage that transition well will retain their best people; those who do not will lose them. <\/p>\n\n <\/p>\n\n Fifty-three per cent of CFOs identify AI as the technology most likely to transform their role over the next five years. The tools that drive this transformation are the ones being chosen today. <\/p>\n\n <\/p>\n\n For businesses expanding across Southeast Asia, the ability to manage multiple currencies, tax systems and regulatory environments through a single, unified cloud platform is a strategic advantage that extends well beyond finance efficiency. CFOs are recognising that the right ERP, one with native AI and multi-entity capability, can become a genuine growth enabler, not simply a back-office cost centre. <\/p>\n\n <\/p>\n\nWhat CFOs Are Actually Prioritising: The AI Use Cases That Matter<\/h2>\n\n
Automation of Routine Finance Processes<\/h3>\n\n
AI-Powered Financial Forecasting and Scenario Planning<\/h3>\n\n
Intelligent Close Management and Reconciliation<\/h3>\n\n
Real-Time Analytics and Executive Reporting<\/h3>\n\n
Embedded AI Within ERP: The Preference That Is Shaping the Market<\/h3>\n\n
What CFOs Believe AI Will Deliver: The Expected Outcomes<\/h2>\n\n
Cost Reduction and Operational Efficiency<\/h3>\n\n
Faster, More Accurate Decision-Making<\/h3>\n\n
Stronger Financial Governance and Anomaly Detection<\/h3>\n\n
Strategic Time Reallocation<\/h3>\n\n
Cross-Border Scalability<\/h3>\n\n
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