The CFO in the age of generative AI

For decades, finance teams have created value by gathering information, analysing it and turning it into business decisions. Generative AI is beginning to change that equation. Capabilities that once required specialist teams, significant investment, and considerable time are becoming accessible to organisations of all sizes.

As a result, some of the activities that have traditionally differentiated finance functions may become far less distinctive in the years ahead. The question for CFOs is therefore not only how they can use AI, but where competitive advantage will come from when their competitors have access to similar analytical capabilities.

The biggest shift since the spreadsheet

CFOs have been here before. More than once. Technology has been transforming the finance function. As Carlos Muniesa, Atradius Strategy and Corporate Development Director, explains: “The CFO’s role has been evolving towards strategy and value creation for decades. AI is not changing that direction; it is accelerating it.”

Long before generative AI, the widespread adoption of spreadsheet software revolutionised the way finance teams worked. Financial modelling, forecasting, and scenario analysis became accessible from a desktop computer. Finance functions were able to devote less time to gathering and reconciling information and more time to planning and analysis.

ERP systems brought the next major shift. Reporting, consolidation, and financial control became increasingly automated, giving finance leaders greater visibility over business performance and expanding the CFO’s role beyond accounting and compliance.

Business intelligence platforms, cloud computing, and automation accelerated that evolution. Static reports gave way to dashboards; information became available in real time and finance teams spent less time producing information and more time helping organisations understand it.

Generative AI is the next chapter in that story. Previous waves of technology largely automated processes. AI is beginning to automate parts of the analytical work itself. Once again, a technological change is likely to raise expectations of finance teams and redefine how they contribute to the wider organisation.

Analytical capacity becomes abundant

The early adopters are likely to benefit from faster analysis and better visibility. However, those advantages may not remain exclusive for long. Technologies mature, competitors catch up, and capabilities that once seemed transformative eventually become expected. Generative AI is unlikely to be an exception.

A decade ago, producing a robust financial forecast could require several analysts working across multiple datasets, spreadsheets, and business systems. Running alternative scenarios, testing assumptions, or preparing a board-level report often involved days of work. Today, AI can help perform many of those tasks in a fraction of the time.

The capability itself is not entirely new. What is changing is the cost, speed, and scale at which it can be applied. As analytical capacity expands, finance teams can spend less time generating information and more time understanding what it means for the business.

The CFO as a manager of uncertainty

For all the excitement surrounding AI, the fundamental responsibilities of the CFO remain remarkably consistent. The role has never been simply about producing more reports, more forecasts, or more analysis. Its ultimate purpose is to help organisations make decisions under conditions of uncertainty.

Organisations operating in the same markets and facing similar economic conditions will increasingly have access to comparable analytical capabilities. Yet they will continue to make different decisions and achieve different outcomes. Economic shocks, geopolitical developments, regulatory changes, and unexpected customer failures do not always follow predictable patterns. AI can improve analysis, but certainty is impossible.

As Carlos Muniesa points out, “Much of the conversation around AI focuses on efficiency and productivity. Yet the CFO’s primary responsibility remains the same: managing uncertainty and safeguarding the company’s financial resilience. AI may improve forecasting, but it does not eliminate the risk of unexpected events. In fact, in more volatile environments, the need for tools such as credit insurance that help protect cash flow and reduce commercial uncertainty may become even greater.”

Better data for better decisions

The quality of the underlying information will also remain crucial. AI can only work with the data available to it, and organisations do not all start from the same position. Some have access to broader information, earlier warning signals, or deeper knowledge of particular sectors and markets.

As Carlos Muniesa observes, “AI is democratising access to advanced analytical capabilities. But as those capabilities become increasingly available to everyone, competitive advantage moves away from the technology itself and towards the quality, depth, and exclusivity of the information that underpins it.” 

This is particularly relevant in credit risk management. Many of the signals that matter most to finance leaders do not necessarily appear first in financial statements. Changes in payment behaviour, signs of liquidity pressure, and deteriorating trading conditions can become visible before they are reflected in reported financial results.

Earlier access to these signals can give a business more time to act. It can inform decisions about whether to trade with a customer, how much credit to extend, when to reduce an exposure, or whether the company can pursue an opportunity with confidence, even at regional, country, or industry level. For finance leaders, competitive advantage will not come from AI technology alone. It will also depend on the strength of the information ecosystem supporting their decisions. 

This helps explain why access to sources of intelligence such as Atradius may become more valuable, not less, in the age of AI. Alongside our own investments in AI and analytical capabilities, we have access to something that is difficult to replicate: insight into how millions of companies behave, particularly when it comes to payment performance. 

As AI generates more answers and generates them faster, the ability to trust those answers may become a competitive advantage in its own right. As Carlos Muniesa argues, “The widespread availability of AI will make advanced analysis increasingly accessible to every CFO. As a result, the question will no longer be who has the best model, but who has access to the best information. Advanced analytics can uncover patterns and risks that may otherwise go unnoticed, but their value ultimately depends on the quality of the data behind them. Future financial decisions will increasingly be shaped by the ability to combine internal information with reliable external intelligence. And as AI generates more insights at greater speed, trust becomes more important, not less. The reliability, quality, and explainability of information will be critical. Competitive advantage will therefore shift away from technology itself and towards the quality of the information ecosystem that supports decision-making. For finance leaders, credit insurance can play an important role in that ecosystem, providing not only protection against risk but also valuable business intelligence.”

Knowing the risk is not the same as carrying it

Generative AI will give CFOs access to analytical capabilities that would have been difficult to imagine only a few years ago. Yet better analysis will not lead to infallible decisions. A model may conclude that a customer presents a higher probability of default. However, that does not automatically determine the right course of action. The commercial opportunity may still be attractive enough to justify maintaining the relationship, particularly in competitive or fast-growing markets.

Even the most sophisticated analysis, built on the best data available, cannot eliminate uncertainty or guarantee that a loss will not occur. This is where credit insurance adds an additional layer of confidence to decision-making. It combines risk intelligence with financial protection, helping companies manage the impact that a customer default could have on cash flow, working capital, and the balance sheet.

Generative AI may transform how CFOs analyse risk, but it will not eliminate uncertainty. As analytical capabilities become increasingly commoditised, the real differentiators will be access to superior intelligence, confidence in the quality of that intelligence, and the ability to withstand the financial consequences of unexpected events. In that environment, the value of credit insurance will lie in helping businesses combine better information, better decisions and greater financial resilience.

To explore how to strengthen your own credit risk strategy, get in touch with us and see how we can help you stay ahead.