CFOs are the stewards of investment capital, orchestrating a movement with transformative technology and innovation to evolve businesses, accelerate revenue streams and drive meaningful outcomes.

The current business environment has CFOs facing headwinds for decision-making in less-than-ideal conditions with rapidly shifting regulations, tedious reporting standards, ESG requirements and inflationary pressures; however, the need for growth and profit expansion remains, and as CEOs look for ways to increase productivity, the CFO is emerging as a new advisor on technology and innovation. Despite the headwinds, there are tailwinds in which we can use new technology to enable CFOs to perform in their business partnering roles and drive productivity, cost take out, accuracy, control and business value.

Through new approaches to financial management that incorporate generative AI, this advanced technology can help CFOs make more informed, data-driven decisions for their organization that can have major financial implications. The IBM Institute for Business Value CEO study on decision-making in the age of AI found the top priorities for CEOs are technology modernization and productivity, while the three biggest challenges are technology modernization, sustainability and security. Enter the CFO, whose role is more substantial than ever to unlock value and to scale and fund a technology they are still trying to fully understand.

Unlocking the value

CFOs are not expected to be technology experts. That said, they do need to understand how to measure the business value created from generative AI across the organization while also using the technology to augment their own skills and capabilities. This new technology can help CFOs do their job better, faster and smarter, in addition to increasing productivity and opening new revenue streams.

The recent IBM Institute for Business Value report CEO’s Guide to Generative AI on Finance report found “success depends on how quickly finance can turn data into actionable insights.” Generative AI not only opens the door to other revenue streams but also it unlocks value for the finance workforce. The IBM report found that, on average, AI adopters attribute 40% of finance function FTE redeployment to AI.

Augmenting our day-to-day lives with generative AI and creating a digital version of ourselves allows for the AI to essentially become our assistant. There are benefits to being a consumer of AI but far greater benefits for being a value creator. A generative AI agent or assistant can ingest and summarize structured and unstructured data from internal and external sources, parse through it and generate insights and patterns for financial information that can drive business value and potentially identify untapped revenue streams. This frees up a significant amount of time where finance professionals were previously knee deep in spreadsheets.

Those organizations that have already adopted AI have helped reduce sales forecast errors by 57%, reduce uncollectable balances by 43%, and cut monthly close cycle time by 33%, according to the IBM Institute for Business Value report. By embracing these technologies CFOs can drive efficiencies and better user experiences for internal and external stakeholders.

New operating model, skills and competencies

Generative AI is changing the way that we do business. The office of the CFO needs to adapt to these new ways of working. The combination of a human and digital workforce creates a new operating model in addition to new skills and competencies required for the finance organization. CFOs are not expected to be data scientists, but they are expected to understand how the enablement of this technology can drive business value.

While finance functional skills are still needed, a new suite of skills to optimize adoption and consumption of digital services are also required. By augmenting the workforce with virtual assistants that free up capacity, finance professionals can focus their time on higher-skilled capabilities. Instead of spending a significant amount of time in Excel spreadsheets, one might spend some of their time building AI tools that help derive insights and provide better planning and forecasting.

The good news: it is likely easier to teach a finance professional how to use the technology to drive value than it is to teach a data scientist those finance skills. The finance workforce should be value creators and experience designers, enhancing their analytical and technical skills to be able to train and prompt their assistants—fine-tuning, adjusting and improving the digital service. In addition, senior finance executives need to have higher communication and storytelling skills as business partners for CEOs.  

Governance and controls

Trust is paramount for finance leaders, and CFOs must be able to trust the data needed to make critical business decisions and for required financial and ESG reporting. Technologies like generative AI can spark feelings of skepticism or mistrust of the accuracy of data, particularly for organizations that are reliant on manual processes. Data governance is crucial to ensuring a lack of bias or hallucinations, establishing greater trust in data and giving CFOs the assurance needed to stand behind their reporting. The findings from the IBM Institute for Business Value report suggest that building governance structures across the finance organization can “[…] bridge governance gaps and develop ethical guidance that will support the ethical adoption of generative AI.”

No matter the task, organizations that embrace generative AI should know that with the right governance in place, CFOs and human employees can free up their time to embrace innovation instead of being averse to the changes that are impending.

Getting started with generative AI

It’s important to remember that many organizations are still in early adoption stages and some are hesitant to dive in. But research shows that the further along organizations are in their AI journey, the more value that is delivered.

If your organization is looking to explore generative AI, consider starting with a labor-intensive task, like identifying and mitigating errors in your financial reporting. A good starting point is from a hybrid cloud environment. While most organizations make the shift, cloud infrastructure can become expensive; but with enterprise-scale generative AI, those costs might be compounded. As the report points out, FinOps, or financial management for cloud-based investments, “[…] should play a big part in generative AI investment decisions.”

While implementing new technologies can seem overwhelming, not having a technology strategy in place or avoiding adoption might put an organization at risk of losing the competitive business advantage. CFOs are the strategic transformation partners CEOs need to ensure swift and successful generative AI adoption.