Oh look, another AI article. But wait. This one is about the one-two punch of AI news from recent weeks that finance professionals need to understand, so keep reading.
Punch 1: Nvidia’s blowout earnings report on August 23. The chipmaker has been favored by many AI developers for its graphics processing units, and its revenue this quarter, which the company expects to rise 170%, shows just how much that’s paid off.
But the full gravity of Nvidia’s report only really makes sense when you couple it with Punch 2: A recent study from S&P Global Market Intelligence, which polled more than 1,500 AI practitioners at midsize to large organizations around the world.
The most frequently cited barrier to AI implementation around the world? Data management, per the survey. And that spices up Nvidia’s earnings report. There’s clearly a shift underway with respect to which data center chips are valued. While the pricey cornerstone of building out a data center may have once been central processors, Nvidia’s report makes a solid case for the increased importance of GPUs. And no matter what, data, and its resources and management, are likely to frame the next chapter of the AI conversation.
“The meteoric rise of data and performance-intensive workloads like generative AI is forcing a complete rethink of how data is stored, managed, and processed,” Nick Patience, a senior research analyst at a division of S&P Global Market Intelligence, said in a statement. “Organizations everywhere now have to build and scale their data architectures with this in mind over the long term.”
Increasingly, that’s what CFOs are thinking about as well. But before organizations can scale up their data infrastructure, they need to prepare the basics first, experts told CFO Brew.
New timeline. “I can’t have a conversation today without somebody mentioning AI, which is a good thing,” Michael Bayer, CFO of cloud storage company Wasabi Technologies, told CFO Brew.
In Bayer’s mind, executives shouldn’t think about what the world will look like tomorrow or six months from now as they design AI plans. Instead, they need to ask themselves what the state of AI might look like “five or 10 years from now, when this curve is really in motion. How will [your] business be transformed by the existence of all these AI technologies? Start working now on what [you] want [your] business to look like as this cycle unfolds.”
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One of the better tactics for doing this is simply developing a targeted AI committee, according to Drew Del Matto, CFO of cybersecurity company Netskope.
“Everybody’s worried that if you start pulling wires out of the wall, you’re going to pull the wrong line,” Del Matto told CFO Brew. “If you’re in that crowd, you need to really form an AI committee.” You want “every department, every function in the company” to at least think about “how they can drive value out of AI,” he explained.
“There’s an old saying that a turkey never votes for Thanksgiving. The point being: If they’re used to doing it one way, they may feel threatened if you make them change,” he continued.
Change management. Handing control over to individual teams “helps people change manage themselves,” Del Matto added. “If you leave it up to each department, you’re going to end up with different results—especially [at] big companies where they have to do a lot of change—and it’s going to take a while.”
At his own company, Del Matto and others “asked everybody to have a three-year plan” when it comes to AI. “Again, change management is a pain,” he said. Three years “gives them time to think about what that is, vet it, vet it with other people, get people on board, and then start executing,” Del Matto explained.
It’s likely time for other leaders to start thinking the same way.
“Just as you wouldn’t expect to use battery technologies developed in the 1990s to power a state-of-the-art electric vehicle, like a Tesla, you can’t expect data management approaches designed for last century’s data challenges to support next-generation applications like generative AI,” Liran Zvibel, co-founder and CEO at WEKA, which commissioned the S&P report, said in a statement.
So, take a look at those metaphorical old batteries.