The Future of the CFO: Generative AI as a Finance Growth Catalyst

Artificial intelligence and generative AI are already transforming the way people work—and finance leaders are well-suited to lead their organizations into a high-growth future enabled by the technology.

“Generative AI is the biggest technology that I’ve seen hit companies in the 30 years I’ve been studying it—and CFOs, who have always been more quantitative and analytical, should be leading that charge,” said Erik Brynjolfsson, professor and senior fellow at the Stanford Institute for Human-Centered AI (HAI) and director of the Stanford Digital Economy Lab.

Brynjolfsson joined Michael Schrage, a research fellow with the MIT Sloan School of Management's Center for Digital Business, in a discussion at a past Workday Rising moderated by Sheryl Estrada, editor of the Fortune “CFO Daily” newsletter.

“To be frank, doubling the productivity growth is not even that ambitious because the Congressional Budget Office and economist Bob Gordon think that productivity is only going to grow about 1.4% per year,” Brynjolfsson said. “I think it’s going to be more like 3% and probably even more than that.”

Productivity gains will reach upward of 25%—”and even 100% in some sectors” over a number of years—Brynjolfsson added.

For CFOs, it’s never been more essential to and embrace emerging technologies that will elevate their teams, enable a more agile finance function, and create value for the enterprise.

What’s Your Return on Data?

Treating data as an asset is a critical component of opening up avenues for value creation, said Michael Schrage of the MIT Sloan School of Management's Center for Digital Business.

“Organizations can tell you what their return on real estate, sales per square foot, is,” he added. “Organizations can tell you the return on their talent. Organizations can tell you ROA, return on assets.”

But when it comes to understanding return on data, the answer isn’t always clear.

In the executive education classes he leads, Schrage said he often asks: “What’s the most valuable data that you have? What metric do you use for return on data?’ And I will tell you, nine out of 10—or more accurately, 95 times out of 100—nobody raises their hand.”

The Value of Organizational Data

Brynjolfsson, who co-authored a study finding productivity gains from AI in the workplace, said generative AI and LLMs have allowed access to organizational data that previously may have been overlooked. 

“Probably the most valuable asset that organizations have is the tacit knowledge, the organizational knowledge of how to get things done that is inside of people and inside of the processes,” Brynjolfsson said.

One call-center company employed “a generative-AI-based conversational assistant” trained on the work of more than 5,000 customer service representatives to help other workers get up to speed. Brynjolfsson’s research found that the company saw an average 14% increase in the number of issues resolved each hour. 

For less-skilled workers, the increase in productivity was even higher—34%.

“With machine learning, the machine figures it out,” Brynjolfsson added. “Instead of teaching it step by step what you want to do, you give it lots of examples of inputs, lots of examples of outputs, and if you have digital data for those, the machine figures out the relationships. And this opens up a whole new set of data assets, that tacit knowledge.”

“Use the T-word,” Schrage offered. “You’re not programming; you’re training.”

Watch the video of the entire conversation below.

Finance and planning leaders can learn more about a master class on growing AI and machine learning skills by visiting workday.com/aimlforfinance.