Wapner spoke with Sigalos on 'Closing Bell' about the recent earnings spate, specifically scrutinizing how AI spending and valuations are being evaluated by investors. The conversation highlighted a pivotal moment in the AI trade, moving beyond the initial excitement generated by partnerships with entities like OpenAI. While companies such as Oracle, Broadcom, AMD, and Nvidia have seen their shares surge on the back of these collaborations, the market's current focus is squarely on "who is turning those headlines into real revenue," as Sigalos pointed out. This marks a maturation of the AI investment landscape, where the rubber must now meet the road in terms of financial performance.
AMD's recent earnings report served as a prime example of this evolving scrutiny. Despite beating on earnings and guidance, the "AI upside is still missing" in their Q4 forecast, with the guide coming in "light of the whisper number." This sentiment underscores a critical insight for founders and VCs: mere participation in the AI ecosystem, even through significant deals like AMD handing over more than 10% equity to OpenAI "virtually for free" to secure business, does not automatically guarantee investor confidence if tangible revenue growth remains elusive. The market is looking for more than just strategic positioning; it demands evidence of immediate or near-term financial impact.
Conversely, the hyperscalers present a more optimistic narrative, albeit with distinct winners and losers. Amazon and Alphabet, specifically Google, have been "rewarded for their AI infrastructure spend." Shares in both companies reached record highs after demonstrating robust cloud growth, significantly boosted by their investment in custom chips. This strategic move is "helping to offset that Nvidia tax," a crucial observation indicating that large cloud providers are seeking to reduce their reliance on external GPU providers by developing proprietary hardware, thereby controlling costs and optimizing performance for their vast AI workloads. This internal capability allows them to offer competitive AI services and capture more of the value chain.
Google, in particular, possesses "the added upside of Gemini," its in-house large language model, which is reportedly poised to power a revamped Siri in a deal with Apple valued at $1 billion annually. This exemplifies a direct and substantial revenue stream derived from AI innovation, a model that investors are increasingly favoring. The ability to integrate advanced AI capabilities into core products and services, or to license them for significant recurring revenue, sets these players apart.
The market's discerning eye has also cast a shadow over other tech giants. Microsoft and Meta, for instance, "have sold off since reporting." Microsoft's situation is nuanced; while deeply invested in OpenAI, it reportedly lost the "right of first refusal" on certain compute deals, suggesting a potential dilution of its strategic advantage in the AI infrastructure race. This highlights the competitive dynamics at play, even among the largest technology firms. For Meta, the challenge is more existential in the AI context. The company reported a "soft Q4 guide" and is "spending like a hyperscaler without a cloud business to justify the outlay." This stark commentary reflects the market’s concern over Meta's substantial capital expenditures on AI and the metaverse without an immediately evident, large-scale, and profitable cloud-like service to absorb these costs.
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The core insight here is that AI investment is increasingly bifurcating the market. Companies with existing, scalable infrastructure and the foresight to develop custom silicon are better positioned to integrate AI and demonstrate clear ROI. Those relying heavily on external partnerships or making significant investments without a direct, high-margin revenue channel, particularly a cloud platform, are facing greater skepticism. The market has moved past the initial phase of AI enthusiasm; now, it demands quantifiable financial returns and a clear strategic advantage.
The market's current focus is less on the sheer volume of AI investment and more on the efficiency and strategic alignment of that capital. The era of pure AI hype is yielding to a more rigorous evaluation of financial outcomes.
