The very blue results of last week’s midterms have sent technology investors into a tailspin.
With many successful candidates running on platforms opposing data centers and calling for greater restrictions on artificial intelligence, investors anticipate a slowdown in AI spending. Tech stocks fell, with a collective loss of $2.5 trillion in market cap, and the Nasdaq dropped more than 5.5%.
“Yesterday was a bloodbath,” said John Furrier (pictured), executive analyst for theCUBE Research. “It was brutal here and the tech stocks got pounded. 41 states had data centers on the ballot. They all lost or won, depending how you look at it. Now it’s so mainstream, it’s a political football. So you’re starting to see the reality of AI. It’s hitting everybody. Everyone is impacted.”
On the latest episode of theCUBE Pod, Furrier and Dave Vellante (pictured, right), chief analyst for theCUBE Research, discussed the fallout from the midterms and whether or not AI companies will really suffer in the long term. They also explored who will own the “system of intelligence” that will govern enterprise AI.
Midterms puts AI investors on shaky ground
After the “bloodbath” last week, the question remains: Can enterprise AI pay for the boom? Despite the shockwaves from the midterms, theCUBE’s researchers are predicting a longer path toward monetization. A recent analysis identified 2029 as the highest-risk year for the AI bubble.
“There’s a clock in terms of the data center monetization and financing and how long it takes to build data centers,” Vellante said. “We know anybody who can sell GPUs is making money but the enterprises aren’t yet self-funding. I had said that by 2026, this year, you’re going to start to see clear evidence of monetization in the enterprise. I think you see it, but you’re seeing it within tech companies.”
Tech companies are applying AI more effectively, according to Vellante, which should not come as a surprise. He thinks the tech titans are in a solid position while neoclouds are taking on a greater share of risk by pioneering a new software model, although not all of them will make it in the long term.
A GPU-based AI economy will shift in the next several years, Furrier believes, which could lead to surprising winners and losers.
“Supermicro [Inc.], good numbers, [Advanced Micro Devices Inc., Arista Networks, Marvell Technology Inc.],” he noted. “My take is this: the infrastructure is evolving beyond GPU-centric computing. Networking, optics, memory, storage, power efficiency. System-level architecture is becoming the strategic advantage, and those bottlenecks are being solved by the companies I just mentioned. You saw the news that Marvell closed a $115 billion acquisition of Lumentum.”
The stock market plunge shows that not everyone is going to make it through the AI era’s eventual slowdown. Public opinion on data centers is mixed, to say the least, so companies will need to establish a foothold in the developing system of AI intelligence to remain competitive.
“Neoclouds like CoreWeave are going to make it through,” Vellante said. “They’re the first movers and they’ve got some quality advantages but they’re going to go through some pain. Hyperscalers are like an ATM. They could dial it down at any point in time … but right now it’s all about growth, it’s about footprint, it’s about market share.”
Predicting the AI era’s winners
Who owns the “system of intelligence”? This layer, which will bridge the gap between intelligent agents and the data systems they depend on, appears to still be in play. Palantir Technologies Inc. has the ontology that could give it the edge, while Snowflake Inc. and Databricks Inc. are still developing the operational systems — though Vellante sees the latter as having one of the best strategies.
“You need determinism to own that system of intelligence,” Vellante said. “So I think it’s wide open. Right now, I think Ali Ghodsi [chief executive officer of Databricks] has the best vision. He’s going after the client surface, he’s going after the system of intelligence, he’s going after the governance catalog, he’s going after the agent action layer, and he’s partnering … with all the frontier model vendors. Whether or not they can pull it off, we’ll see.”
Frontier models are the “wild card,” as Vellante puts it, but at the moment, all the tech companies are trying to get a slice of the pie. Despite the recent market shakeups, Furrier sees AI-native enterprises as the ultimate result of this current period of growth.
“The AI-native enterprise or businesses is going to be the model,” Furrier said. “Everybody wins in that one. Compute providers, hyperscalers, the data platforms that are on the right side, and the application companies, which are basically going to be agentic. That’s going to be the winners on the profit concentration. The control point … it’s not going to be the models, it’s going to be data and context, and the agents will be the proof point.”
Watch the full podcast below to find out why these industry pros were mentioned:
Tom Lee, investor and entrepreneurDan Ives, technology analystFrank Slootman, former chairman of the board of directors at Snowflake Inc.Ali Ghodsi, co-founder and chief executive officer of DatabricksJohn Roese, global CTO and chief AI officer of Dell TechnologiesLisa Su, chair and CEO of AMDMichael Dell, chairman and CEO of Dell TechnologiesGeorge Gilbert, principal analyst at theCUBE ResearchGeoffrey Moore, principal at Geoffrey Moore ConsultingRob Hof, editor-in-chief at SiliconANGLE MediaStu Miniman, senior director of market insights, hybrid platforms, at Red Hat
Here’s the full episode of this week’s theCUBE Pod:
Photo: SiliconANGLE
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