Amid the generative AI (GenAI) revolution, the role of the CFO is evolving rapidly, from gatekeeper deciding which projects get funded, to key player dictating the future of enterprise strategy. And the next year will be the true test of how well big company finance chiefs navigate that transition.
Nearly 75% of companies have adopted AI, according to a 2024 McKinsey & Co. survey. Meanwhile, in most industries, companies are likely to invest more than 5% of their digital budgets in GenAI and analytical AI. That’s quite a departure from the start of 2023, when GenAI was still a relative novelty and the primary role for CFOs was to find budget to support rapid-fire development of proof-of-concept projects and narrowly focused point solutions. Now, AI is at the center of the corporate budget. As such, CFOs will not only dictate how AI gets deployed—their day-to-day workflows will also be transformed by the technology.
To put this multidimensional experience into perspective, it’s important to first consider the three core functions of the CFO: to serve as the steward of the company, to manage financial operations and required reporting, and to be a strategic partner helping enhance the enterprise value of the business. While these roles will not change, the foundational work of the finance organization, structure, import, and focus of these dimensions will change. AI will inevitably impact how the work gets done. It will strengthen and improve the veracity of financial data, and it will enable and expand the CFO’s work of value creation.
The Changing Nature of What Needs to Be Protected
As the steward of the company, the CFO ensures financial integrity and compliance. The work of the CFO and the finance team protects the company’s assets and reputation and guards against risk. Historically, these assets have been things such as intellectual property, trade secrets, processes, and/or tangible assets such as machinery and inventory.
With the changing tech landscape, there will be multiple additions to what needs stewardship. Data, customer relationships, and brand reputation will become the most valued assets of the company and a source of differentiation. CFOs will be tasked to protect the company in all new ways, such as ownership and access to data, data models, and algorithms. These are complicated things with vastly different characteristics than a proprietary formula, recipe, or piece of equipment.
GenAI also brings black-box risks such as unrealistic expectations for AI capabilities or a general lack of trust in AI technology due to issues such as AI hallucinations. Additionally, the finance team will also need to focus more on cyber risks, especially protecting customer data. A breach of any data asset could hugely damage financial operations and the overall integrity and reputation of a company.
Also, there will likely be more regulation on data and privacy protection as well as ethical use guidelines for AI and other technologies. CFOs will need to take an active role in defining company policies to comply with these requirements.
For example, one of the primary GenAI use cases currently being deployed in large corporations is anomaly detection in the risk management function. When it comes to things like knowing your customer risk and counterparty risk exposures, GenAI is unparalleled in its ability to surface red flags, highlight opportunities to change course, and reduce errors. Thanks to advances in GenAI, companies can analyze 100% of all compliance, profit and loss, tax, and outcomes data, instead of just using sampling methods to conduct risk assessments.
However, that new capability introduces an enormous responsibility for the finance department. Not only does the finance team need to verify its algorithms have been developed responsibly and without bias, but it must also make sure that all customer data and other information being used to populate these models remains secure in the GenAI setting.
Although GenAI is solving many legacy challenges by combing through petabytes of data at a pace that wasn’t previously possible, it also introduces its own set of risks for which the CFO must manage accordingly.
Reengineering Operational Workflows
The fundamental process of managing the books and financial reporting—the traditional work of the CFO—will be greatly impacted by AI.
For example, this is now a very real scenario: an “accounting copilot” reviews account balances in real-time, recognizes anomalies, recommends actions (manual journal entries, credit/payment holds), and executes those actions upon confirmation/research by a member of the finance team. That’s a step change from the conventional method of account review, where teams of analysts would traditionally review reams of spreadsheets looking for potential issues and recommend the next-best action to resolve them. GenAI will no doubt increase productivity and accuracy, but it will also introduce new workflow processes that need to be managed and overseen. As a result, companies will need to redefine job roles and adopt processes to review and respond to the new AI-enabled workflow.
Another area where AI will transform finance department workflows is in payables leakage, whereby issues such as duplicate invoices, fraudulent claims, and invalid or late payments create errors in accounts payables. Current AI-enabled solutions being used by finance departments are making it possible to intercept and alert finance departments to these problems before they result in costly investigations and account reconciliation processes. While these solutions represent enormous gains in accuracy, they also introduce new risks.
CFOs must keep in mind two key considerations when implementing these types of solutions. First, they must ensure the sanctity of the data by connecting to the right data source. Second, they must engage a “human-in-the-loop” to make sure it’s explainable and to review all transactions before they’re entered/posted on the company’s book of record.
Another facet of the finance chief role that will change dramatically is business intelligence (BI). Historically, the finance team would provide reporting and information to the business by using a conventional BI model. Finance and technology teams would interpret and predict ongoing and ad-hoc requests from a business unit, run queries, and report back information and insights. Success was defined by providing accurate information on time.
All of this will change with AI. Collecting, reviewing, analyzing, and distributing financial data will become self-service and autonomous. AI will now truly allow data analytics to run as close as possible to the business and at hyper speed, turning conventional BI into conversational BI. This new functionality will offer greater insights regarding financial performance, trends, and anomalies, and will allow business and finance executives to make data-driven decisions rapidly. However, CFOs will need to manage their teams and deploy resources thoughtfully to ensure that these newly automated workflows are driving the intended outcomes.
Focus on Value Creation
For years, the most successful CFOs have been those who are able to take an active role as a business partner in improving the overall economics of the company. Now, success will be defined by their ability to embrace AI and use it to accelerate the transition to a true data-driven finance organization.
AI now plays a central role across all aspects of data-driven finance, from real-time insights to more accurate and timely forecasts to better capital allocation and risk management. The ability to effectively harness and manage that transformation is increasingly becoming the mark of success for the CFO function.
Of course, these aren’t new activities for the finance department, but AI is supercharging them, giving CFOs who get the AI formula right a distinct competitive advantage over those who resist. For example, finance teams leveraging AI across their enterprise are now able to ingest internal results, trends, and patterns of customer behavior—along with external macroeconomic, competitor, and mobility data in real time—and fine-tune their forecasts and projections accordingly. Those without this AI assistance will be operating at a distinct disadvantage.
The real difference between leading and lagging will be speed—and AI will enable that for the enterprise. By tapping into real-time data, CFOs will better determine how to allocate capital, developing scenarios quickly and effectively. Finance teams will more easily provide data-driven counsel for or against a new proposal or apply multiple dimensions to improve the efficacy of their forecasting. Rather than just using a risk-based approach to assess new ideas and projects, CFOs will be able to provide a more balanced view of risk.
For example, a finance executive can now replace the traditional net present value/discounted cash flow calculator with multi-scenario models to stress-test multiple different forecasts under different scenarios. Going even further, some of the most progressive finance teams can incorporate sensor-based data from plants, factories, or trucking fleets to prioritize capital expenditures. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapid modelling of multiple scenarios and market conditions.
With these new capabilities come big responsibilities and significant communication and leadership challenges. CFOs won’t be able to flip the magic AI switch and suddenly have access to an instant forecasting and projection machine. They’ll need to make careful, choreographed investments in strategic areas where the technology can generate the most significant positive impact. Along the way, they’ll need to consistently communicate with the rest of the leadership team and employees about why these investments are being made and how these new tools will be integrated into the workflow.
Now more than ever, CFOs have an opportunity to be front and center in helping organizations identify, define, and monetize new sources of value—leveraging data, models, and algorithms. But they will be doing so while navigating relatively uncharted waters, establishing best practices, and learning important lessons along the way. The key at every step in that process is to never lose sight of the core responsibilities of the finance department—to be the steward of the company, to manage financial operations and required reporting, and to be a strategic partner.
Before any investment or enterprise-wide rollout of new AI-enabled technology and processes begins, CFOs must ask themselves: “How is this going to improve the way I deliver on my core responsibilities?” The answer needs to guide the entire AI journey, from onboarding and prototype solution development to results reporting and benchmarking.
