In future, CFOs and finance professionals will use AI to interact with those systems in different ways. They will use natural conversational language to create reports, run analyses, and produce forecasts. The skill will lie in knowing what questions to ask and recognising where the data’s potential value might lie.
Use of GenAI to be a competitive differentiator
A new approach to data gathering will also be required in many instances. CFOs will need to look beyond finance to other functions and departments to source data for use in forecasts and strategic guidance, and very importantly to understand those departments’ key needs. That will require an understanding of where data gets sourced from, how it flows from one system to another, where the bottlenecks lie, where data is leaking or getting lost, and what issues need to be addressed to improve data availability. Having access to that data from across the business and from outside the business in the form of external market reports and so on, will be of crucial importance to realising the benefits of GenAI in the finance function.
This applies to all areas of an organisation. Department and division heads will need to understand not just their own area of the business, but all business functions and ensure that data flows between them as appropriate and required.
GenAI is far from faultless, however, and trust is a major issue. For example, no CFO will be willing to sign-off on financial statements if the finance team does not know how to check the GenAI outputs they are based on.
Explainability is another challenge. If a certain system is being used to produce statements or reports, the CFO must be able to explain how it works and how it comes to its conclusions. And therein lies another issue, inconsistency. At present, you can ask GenAI the same question 50 times and get a different answer on each occasion. That may be acceptable for marketing content, but it certainly will not work for financial statements and forecasts, where trust and data integrity is of utmost importance.
Fortunately, GenAI developers and organisations integrating the technology into other software systems are addressing these issues and the technology is improving at a rapid pace. But it is still not at a stage where it can be fully relied on. Humans will need to be kept in the loop at all times to verify the outputs and ensure that the systems are not hallucinating or being creative when they should not be.
The use of GenAI by CFOs and finance functions to support strategic decision making in their organisations will soon be a competitive differentiator. This means that even if they are not currently using GenAI in their organisations, CFOs need to experiment with it, understand how it works, what it can do, and the value it can bring to the business.
More importantly they need to help instil an experimental culture within the organisation where employees at all levels are encouraged to bring forward ideas for use cases without fearing repercussions for aborted pilots or lack of investment. Prioritisation and piloting of potential use cases will allow organisations to swiftly assess where GenAI can deliver value internally, to customers and shareholders. CFOs who fully embrace this early-stage trial and error will ensure that they are not left behind when the technology evolves to a point where it can be trusted, is consistent in its outputs and is fully explainable.
Summary
GenAI has the potential to transform the way finance functions operate and the strategic insights and guidance that CFOs can bring to their organisations. To realise that potential CFOs will need to understand the business needs across different departments, gain access to data from across the organisation, develop basic data science skills, and perhaps experiment with the technology to understand how it works, how to interact with it, and how it can deliver value to the business.