The CFO’s Expanding Role in an AI-Powered World
By: Jeremy Ung, Chief Technology Officer of BlackLine
Chief Financial Officers have long been stewards of financial risk management, responsible for keeping the budget in check and enterprises on track. While that aspect of the job hasn’t changed for decades, there’s a new force fundamentally reshaping how businesses manage their data and finances – Artificial Intelligence. In fact, 27% of CFO job descriptions now mention AI expertise, an 8% jump from just last year. This signals a major shift in expectations: Today’s CFOs must not only understand how to leverage AI for financial strategy, automation, and decision-making but also how to govern it responsibly. AI literacy has become a critical skill for finance leaders in driving efficiency and ensuring financial integrity in an increasingly data-driven world.
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AI Hesitancy in Financial Operations
AI adoption is accelerating, with the market set to double to $300 billion by 2027. In today’s tech-driven world, integrating AI into financial operations is becoming necessary for maintaining a competitive edge. However, CFOs remain cautious, recognizing that financial data is among the most sensitive and mission-critical assets in an organization.
While AI excels at automating processes, improving revenue forecasting, and enhancing decision-making, it also raises concerns about explainability and control. AI-driven financial insights must be traceable and auditable to meet strict regulatory and reporting requirements. Without clear visibility into how AI models make decisions, finance leaders risk regulatory scrutiny and the consequences of compliance failures.
This is one reason why AI’s potential in finance remains underutilized, with only 34% of finance operations using or optimizing traditional AI, according to IBM.
Fixing the Foundation – Data
One of the biggest hurdles with AI is data integrity. No matter how advanced the technology, if the underlying financial data is incomplete, inconsistent, or full of errors, AI will only amplify those issues. And when forecasts are off or financial results are miscalculated, it’s the CFO, not the algorithm, who answers for it.
The complexities of managing transactions across multiple subsidiaries, currencies, and regulatory environments often create data inconsistencies, reporting delays, and compliance risks. Today’s top global companies still suffer from pervasive pain points like siloed teams and outdated manual processes, creating a lack of clear financial visibility. These inefficiencies don’t just slow down operations, they disrupt cash flow.
For CFOs, fixing these intercompany issues isn’t just about efficiency, it’s about making AI work the way it should. That starts with strengthening data governance to ensure financial data is standardized and auditable.
That’s why finance leaders are putting data integrity and governance at the center of their AI strategies, with Gartner reporting 76% of CFOs are now leading or co-leading their company’s data and analytics strategy, and nearly half are overseeing AI initiatives. CFOs are ready to help finance teams spend less time resolving errors and more time focusing on long-term strategy and decision-making.
The Most Important Part of AI Implementation: Partnership
As companies invest in their digital infrastructure and streamline their tech stacks to generate greater productivity, the most important part of that tech stack is a CFO’s partnership with the Chief Information Officer to ensure internal systems are fluid and future ready.
In the past, CIOs were often brought into conversation only after key decisions were made. That’s not going to work out well for anybody in today’s modern enterprise. Whether it’s about security posture, data architecture, or automation, CFOs must partner with CIOs to help define how technology can support and drive long-term goals of the business.
CFOs who collaborate through a multidisciplinary approach are better positioned to manage risks and benefit from digital capabilities. This model also creates a culture of shared accountability, authentic engagement, and a joint goal.
Moving Beyond Process Improvements with Intelligent Automation
AI is reshaping the way companies operation, which is why 6 out of 10 CFOs believe AI will have the most significant impact on their industries in the next three years, found Gartner.
When it comes to AI implementation, finance leaders typically focus on three key objectives: reducing costs, minimizing risk, and improving long-term profitability – securely.
To truly drive efficient financial management, more CFOs need intelligent automation and centralized intercompany management. AI-powered financial solutions are reshaping core functions such as financial close, reconciliation, reporting, and cash flow management. By automating routine tasks, integrating data across disparate systems, and generating predictive insights, AI enables finance teams to operate with greater accuracy and agility.
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These key benefits include:
Data Integration & Standardization
Finance teams often struggle with fragmented data spread across multiple ERP systems and business units. AI-driven platforms can integrate, cleanse, and standardize financial data in real time, eliminating errors and ensuring a single source of truth for financial reporting. This not only improves accuracy but also accelerates closing cycles and enhances audit readiness.
Intelligent Automation for Efficiency & Accuracy
Manual finance processes, such as reconciliation, invoice processing, and variance analysis, are resource-intensive and prone to errors. AI-powered automation streamlines these workflows, reducing human intervention and allowing finance teams to focus on higher value activities like financial planning and risk mitigation.
AI-Powered Predictive Insights
Traditional financial reporting is often retrospective, providing insights only after the books are closed. AI enables CFOs to shift to a forward-looking approach by analyzing financial trends, forecasting revenue with greater accuracy, and identifying potential risks before they escalate. With real-time AI-driven analytics, finance teams can improve decision-making and proactively address financial challenges.
Risk & Compliance Management
AI can play a crucial role in identifying anomalies, detecting potential fraud, and ensuring compliance with evolving regulatory requirements. By continuously monitoring transactions and financial statements for inconsistencies, AI enhances risk management and provides greater transparency into financial operations.
Optimizing Cash Flow & Working Capital
AI-driven payment forecasting models leverage historical transaction data to improve cash flow predictability. By reducing uncertainty around receivables and payables, finance leaders can optimize working capital, reduce reliance on short-term financing, and improve overall financial stability.
The future of the Office of the CFO is not just about optimizing costs. It’s about using AI to drive smarter, faster, and more confident decision-making in an increasingly complex and data-driven world.
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