Opinion
CFOs face dual pressure: capital markets demand accountability for every dollar, while organizations urge them to actively pursue AI. The problem is that many companies still use cost reduction and efficiency gains as the primary measures of AI ROI, framing AI as a defensive investment rather than a strategic one. This article argues that leading CFOs are directly linking AI to business outcomes, defining success across departments, and rebuilding the ROI evaluation framework across three dimensions: efficiency, revenue impact, and long-term strategic value.
Corporate spending on AI continues to grow, and CFOs face the challenge of evaluating complex technology budgets and uncertain returns. This article suggests that financial leaders ask themselves five questions before investing: whether the workflow will still exist in the future, what the true costs are, whether new supplier concentration risks are introduced, how cybersecurity is factored in, and whether speed truly provides a competitive advantage.
With over 40 U.S. states relaxing CPA exam eligibility requirements, enrollment in accounting programs has grown significantly, but AI is replacing the traditional training tasks of junior auditors. Trullion CEO Artie Minson points out that the industry needs to balance AI deployment with talent development, ensuring new accountants build professional judgment by critically questioning AI outputs rather than through mechanical operations.
Modernization projects are often approved based on short-term payback, but completing within budget and meeting technical standards does not equate to successful capital allocation. Using a $2 million lighting retrofit as an example, the article points out that factors such as operational changes and maintenance costs can make actual savings far lower than projected. CFOs need to adopt a capital allocation perspective, using five key questions and two control points, to ensure investment value is achievable and verifiable.
The application of agentic AI in finance is evolving from a productivity tool into an integral part of financial reporting processes, but most enterprises' internal controls have not kept pace. Based on industry observations, this article identifies three major risks: misaligned ROI benchmarks, arbitrary capitalization treatment, and missing controls. Drawing on the banking SR 11-7 regulatory framework, it proposes three pre-approval questions for CFOs: audit trails, model owners, and validation cadence.
A decade ago, it was rare for data and analytics leaders to report to the CFO, but today it is increasingly common. Behind this lies a fundamental transformation in the finance function: not only to explain 'what happened,' but also to answer 'why it happened' and 'what to do next.' Amid heightened tariffs, supply chain disruptions, and demand volatility, the finance department is leveraging AI to reposition its value—shifting from producing reports to understanding the business, identifying signals, and making forward-looking judgments.
As the U.S. tariff and drawback environment and processes continue to evolve, how enterprises handle their specific situations at the initial stage may produce complex and potentially irreversible downstream impacts. A lack of cross-departmental collaboration, inconsistent data, and incomplete documentation can now lead to unexpected financial, tax, and compliance consequences in the future, and related decisions may trap enterprises in a passive position from which it is difficult to escape. This article focuses on three potential pain points—drawback timing, transfer pricing, and Pillar Two rules—to provide a reference for enterprises in addressing tariff drawback and future trade decisions.
Banking relationships are the most important yet often overlooked strategic asset in a CFO's toolkit. This article explores how to turn technical compliance into long-term trust across four dimensions: negotiating terms, anticipating compliance, report quality, and proactive communication.
As the complexity of corporate financial operations increases, the role of spreadsheets in FP&A has evolved from an efficient tool to a potential source of risk. Based on the practical experience of Goldman Sachs analyst Albin Joseph, this article dissects pain points such as version control and manual reconciliation, and points out that governance is more critical than technology, with the introduction of AI further highlighting the necessity of governance.
The application of generative AI in tax and accounting faces challenges. A 2026 report from the Thomson Reuters Institute shows that only 34% of tax firms use GenAI at the organizational level. General large language models excel at language generation but are not reliable calculators, and they carry risks such as knowledge cutoffs and hallucinations. David Wong proposes four questions to help determine whether AI tools meet professional tax standards.