· 4 min read
What a difference a year can make.
Last year, when hundreds of CFOs gathered for the annual MIT Sloan CFO Summit in Boston, talent strategies were top of mind: how to keep your people, how to train the next gen.
This time around, there was a new ingredient added to the talent mix: generative AI. And while AI didn’t dominate all discussions, it was the steady undercurrent of a slew of conversations about the CFO’s role in managing talent and driving innovation.
Ankur Agrawal, partner at McKinsey, told CFO Brew the most prominent new topics at this year’s conference centered around automation and data analytics, the latter likely because of generative AI, he explained.
“Automation was there last year, too, as a theme, but this year people are talking about automation in newer and different areas,” Agrawal added.
But there was a crucial guardrail on most tech-forward conversations: CFOs were keenly eager to develop AI tools that could help retain and attract talent, rather than replace jobs.
Here are highlights from some of the panels where CFOs discussed how their orgs are using automation and AI—and how finance professionals should think about emergent technologies at this inflection point for the industry.
The CFO take. “Most people probably don’t think of Johnson & Johnson as a tech company,” its CFO, Joseph Wolk, said as he segued into a conversation about the health giant’s AI and tech explorations. He noted that the company employs “about 3,000 data scientists; we’ve got a thousand different people writing code” for innovations like medical devices for robotic assisted surgery.
Wolk noted that he was “heartened” by MIT Sloan entrepreneurship professor Simon Johnson’s front-and-center declaration that an effective tech stack was one guided by human hands. “You can diagnose things [with AI], but unless you have somebody looking over that medical chart…it could be a wrong diagnosis,” Wolk agreed.
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Similarly, Delta CFO Dan Janki said on a panel that he sees humans working with AI toward efficiency improvements for the airline industry in the future, particularly around pesky flight scheduling. That has always required vast amounts of data and analytics, he noted, but machine learning could enable commercial and revenue management teams “to even do it better.”
“Think about how we run our operations every day—not only how you schedule it, but when there is a disruption, how do you reschedule it and reset it? The ability to use machine learning to do that is incredibly powerful,” he said.
Artificial intelligence could speed up other parts of the travel process, he noted. If you’re traveling and need a quick answer, he envisions eventually being able to “self-service you with machine learning and analytical engines, or at least help our reservation specialists get the answers faster.”
Meanwhile, Carolina Dybeck Happe, finance chief at GE, noted how her unique career trajectory informed her AI outlook. “I probably did something unusual because I was actually in a tech company, and then I moved to an industrial company, but everybody else was going from industrials to a tech company,” she said in a panel discussion. “I saw the opportunity of what digitization can do for industrial companies.”
She drew a parallel between what the Industrial Revolution did for manufacturing jobs and the “safety, quality, delivery, and cost” improvements this new machine learning technology can bring to industrial companies.
“We’re getting into a phase where we have the opportunity of doing the same kind of improvements.” she said. “It’s still early days, but we were joking that our next script will be written by ChatGPT…But seriously, there’s a lot of work that has not been the best part of all of our jobs that will go away, so we can spend our time on more important things.”