CFOs should strive to be enablers — not gatekeepers — of generative artificial intelligence adoption within their organizations, beginning with experimental use cases in the finance function, according to a guide published by McKinsey.

While generative AI is still in its early days, the array of possible enterprise use cases is already wide and varied, and the rate of adoption is speeding up, McKinsey partners Ankur Agrawal, Ben Ellencweig, and Rohit Sood wrote in the guide, which was published last week.

“Those realities make it even more important for CFOs to get started in a considered and proactive way,” the authors said. In coming years, generative AI will be “table stakes” for all forward-looking finance teams, they said.

Generative AI could enable automation of up to 70% of business activities across almost all occupations between now and 2030, adding trillions of dollars in value to the global economy, according to a September article from McKinsey.

A recent Gartner survey shows that CFO sentiment towards AI in general is largely positive, with 85% of respondents expressing optimism about using it within the finance function. Yet, when it comes to adoption, most finance departments are taking their time compared with other teams in the organization, like human resources, legal, and information technology, the study found.

However, this is expected to change in coming years as the AI market continues to mature at a rapid pace. Four out of five finance leaders responding to the Gartner poll said they expected to devote more money and effort into deploying AI over the next two years.

By 2026, 80% of large enterprise finance teams will rely on internally managed and owned generative AI platforms trained with proprietary business data, according to separate research from Gartner.

McKinsey made a similar prediction, concluding in its CFO guide that “most, if not all, finance functions in large enterprises will likely be using gen AI in significant ways within the next three to five years.”

According to the guide, a few multinational enterprises have already begun to implement AI for use cases such as creating first drafts of securities filings and stakeholder reports; facilitating collections and payments; and identifying drivers and root causes of budget variances. 

CFOs just embarking on the path to becoming AI innovation champions should experiment with the technology by, for example, uploading and analyzing competitors’ publicly available earnings-call transcripts, the guide said.

The authors also recommended that CFOs budget a “nominal amount” for AI projects in the learning phase.

“[T]he goal is not to let a thousand flowers bloom,” they wrote. “Instead, CFOs should select a handful of use cases — ideally two to three — that could have the greatest impact on their function, focus more on effectiveness than efficiency alone, and get going.”