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At A.Team's January Generative AI Salon, CFOs discussed the risks and rewards of AI investment, highlighting its potential to enhance productivity and customer service.
Despite these potential benefits, they recognized the increasing concerns about data security and the challenge of delivering a tangible ROI.
By beginning experimentation now, companies can begin to understand how AI might be involved in each unique area and function of their job.
HungryRoot, the New York-based grocery subscription service, has devised a tasty use for artificial intelligence: Customers feed the company information about their households' dietary needs. In return, AI-powered tools help HungryRoot feed its subscribers by devising personalized meal plans and grocery orders that the company ships out every week.
The AI investment is even palatable to the company's finance department: data shows that more personalized orders lead customers to buy more and cancel subscriptions less, says Wajeeha Ahmed, HungryRoot's CFO. AI can tailor customers' orders by synthesizing their personal requirements (a gluten allergy) with external signals (a blizzard approaching their zip code).
Polar vortex incoming: Cozy chicken stew with rice noodles, anyone?
"There's a very direct business result," Ahmed told an audience at an A.Team salon on The ROI of AI, on January 31 in New York City.
She joined three other seasoned CFOs—Vadicel Joy Abboud of Ceremonia, Chris Asmis of Farmer's Dog, and Varun Athi, formerly the CFO of Luma, Aventri, and Butterfly—to sift through the risks and rewards attached to AI investment.
In 2024, Generative AI is either a magic ingredient or a costly extravagance that’s hard to monetize. Sprinkled into existing software – or served separately via subscription products like ChatGPT – GenAI-powered tools can improve productivity on all manner of specialized tasks, eliminating repetitive work, and improving customer service. But the question of actually delivering ROI remains open.
Early productivity gains are great, but product integration is the bigger game
A recent survey from Deloitte illustrates the contradiction: Seventy-nine percent of corporate leaders believe that Generative AI will transform their industries within the next three years. Yet most are playing it safe by buying with crowd-pleasing off-the-shelf AI products like Microsoft's CoPilot instead of building their own tools—the AI equivalent of eating Sweetgreen (healthy but available to everyone) versus growing your own lettuce (difficult to do but ultimately more profitable).
The CFOs pointed out that AI products still come with a lot of uncertainty. What if, while helping out, the AI confidently supplies bone-headed answers or leaks sensitive information to competitors or even criminals?
Finance departments smell the opportunities—and feel the heat—like few others. They're both weighing AI investments companywide and daydreaming about ways AI can help their jobs. A bean counter's work is rich in both data and tedium—a choice AI combo, after all. But note that same data is also highly sensitive.
"There's lots of things I'd love a machine to do," quipped Ahmed. "But we don't want to put information into the system in ways that would put it at risk."
The risks are front of mind right now, but there’s a sea change on the horizon
"It's too early to quantify a lot of the benefits," added Asmis. "And I'm not sure we can yet contemplate all the bad ways AI could impact us. We need to understand those things, too." Yes, Asmis added, he loves the idea of automating things like budget reconciliation – but not if it means leaking company secrets.
So, how can AI make these CFOs happy? Companies can start by experimenting constantly. "In the future, I really believe GenAI is going to be part of what we do on a day-to-day basis," said Abboud, just as we can't imagine daily life without smartphones. "So just start now and understand how AI might be involved in each unique area and function of your job."
She recently had it write up job descriptions for a new hire and then revised it to make it her own, for example. "It's never too early to play around with AI."
It's never too early to play around with AI.
Be poised to quit playing and move fast: "Once we see use cases with tangible outcomes that we can sell? Those will be adopted, and they'll explode," said Athi.
"In AI, the ball hasn't dropped yet - we haven't been able to quantify material costs or revenues." Meanwhile, Athi added that important "table stakes," namely the security of data going in and accuracy of data coming out, haven't yet been reliably put up. But just wait: "When we have that data, that's when true progress happens."
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