A consensus seems to be emerging that GenAI is the next wave of transformational technology. Leaders managing any aspect of any company will likely need to integrate it into their business’s strategy and operations. The key: Start asking the hard questions and look ahead to how GenAI can be gradually deployed in both finance and the enterprise.
Why now? The simple answer could be that not adopting GenAI could put companies at a competitive disadvantage, given its capacity for unlocking new business models, identifying new growth opportunities, and accelerating innovation in products or services. But harnessing GenAI’s capacity for amassing and analysing massive quantities of data is hardly simple—or inexpensive. The challenge for CFOs is identifying opportunities for incremental improvement. It’s a lengthy menu, from streamlining financial planning and analysis (FP&A) to improving forecast accuracy—areas where GenAI can demonstrate a tangible impact on the bottom line. Accumulated GenAI “dividends” can then be reinvested in higher-value strategic opportunities, where ROI may take longer to achieve.
It’s difficult to leverage the full power of GenAI without getting the underlying data in order. For some companies, that may mean creating a centralised repository for the aggregated data from each business unit. GenAI’s nearly insatiable appetite for data can only be fed once standardised data is also AI & Digital Transformation consistent, accurate, and complete. Governance issues over handling the data also need to be in place.
Many CFOs have already begun exploring GenAI. In Deloitte’s 3Q 2023 CFO Signals survey, 42% of the 116 respondents said that their companies were experimenting with GenAI. Implementing GenAI tools for repetitive and manual tasks in areas like reporting can free up finance teams to turn their attention to higher-value tasks.
But before companies can unlock GenAI’s full potential, they will likely have to address issues related to talent, governance, and risk. In the 1Q 2024 CFO Signals survey, 93% of the 116 respondents said that bringing talent with GenAI skills into finance is important over the next two years.
Finance leaders will likely face a host of investment decisions over that same time period, including whether to consider building their own GenAI tool or to customise a vendor-supplied model.
Either way, the risks associated with GenAI—including data privacy, intellectual property issues, and model bias—will need to be managed. “Hallucinations,” wherein GenAI produces inaccurate or nonsensical data, also will require monitoring. Combining AI’s capabilities with human knowledge may be the recipe for faster and more accurate decision-making.